Capture Once and Analyze EverywhereStream or export Xsens motion data into the biomechanics, modeling, and ergonomics software your research already runs on. Capture movement once. Send it everywhere your analysis lives. <h3> </h3><h3>Why connect Xsens to your existing tools?</h3>Your study rarely ends with raw kinematics. You need joint angles in Visual 3D, muscle forces in AnyBody, or an ergonomic verdict in Siemens Process Simulate. With Xsens integrations you can stream accurate, full-body motion data into those packages directly, so you spend your time on analysis instead of file wrangling. Xsens Analyze records lab-quality kinematics anywhere, then streams the data live or exports it in the formats your software expects. The result is a shorter path between a recording session and a finding you can publish. <h3> </h3><h3 id="isPasted">Integrations at a glance</h3>A quick map of the research integrations and what each one gives you. Featured connections are shaded. <table><tbody><tr><td>Intergration</td><td>Category</td><td>Connection</td><td>What it produces</td><td>Primary use case</td></tr><tr><td>Delsys</td><td>EMG hardware</td><td>Live + export</td><td>Muscle activity synced to kinematics</td><td>Gait, sports, rehab</td></tr><tr><td>BoB Biomechanics</td><td>Musculoskeletal modeling</td><td>Export</td><td>Muscle forces, joint loads, activations</td><td>Load estimation</td></tr><tr><td>AnyBody</td><td>Musculoskeletal simulation</td><td>Export</td><td>Internal loads, muscle and joint forces</td><td>Simulation studies</td></tr><tr><td>Siemens Process Simulate</td><td>Manufacturing ergonomics</td><td>Export</td><td>Reach, posture, ergonomic risk</td><td>Workstation design</td></tr><tr><td>Visual 3D</td><td>Biomechanics analysis</td><td>Export</td><td>Joint angles, kinetics, custom models</td><td>Clinical and sports research</td></tr><tr><td>OpenSim</td><td>Musculoskeletal modeling</td><td>Export</td><td>Modeling and simulation outputs</td><td>Open-source research</td></tr><tr><td>Scalefit</td><td>Ergonomics</td><td>Live / export</td><td>Ergonomic risk scoring</td><td>Workplace assessment</td></tr><tr><td>C-Motion</td><td>Biomechanics</td><td>Export</td><td>Visual 3D processing pipeline</td><td>Kinematics and kinetics</td></tr><tr><td>Cometa Systems</td><td>EMG hardware</td><td>Live + export</td><td>Wireless EMG synchronization</td><td>Muscle studies</td></tr></tbody></table><table><tbody><tr><td>StretchSense</td><td>Hand mocap hardware</td><td>Live + export</td><td>Finger and hand motion</td><td>Manipulation studie</td></tr><tr><td>Dassault Systèmes</td><td>Digital human / ergonomics</td><td>Export</td><td>Ergonomic simulation</td><td>Product and process design</td></tr><tr><td>D-Lab</td><td>Behavioral analysis</td><td>Live + export</td><td>Multimodal data analysis</td><td>Human factors</td></tr><tr><td>ViveLab Ergo</td><td>Ergonomics (cloud)</td><td>Export</td><td>Cloud ergonomic simulation</td><td>Workplace assessment</td></tr><tr><td>Moveshelf</td><td>Data platform (cloud)</td><td>Export</td><td>Movement data storage and sharing</td><td>Collaboration and review</td></tr><tr><td>NAWO Live</td><td>Ergonomics</td><td>Live</td><td>Real-time ergonomic risk</td><td>On-site assessment</td></tr><tr><td>HTC VIVE Ultimate Tracker</td><td>Positional hardware</td><td>Live</td><td>Positional data</td><td>Space referencing</td></tr></tbody></table>Connection method varies by tool and software version. Confirm the exact live-stream and export options with our team for your setup.<a href="https://www.xsens.com/integrations/analyze" target="_blank" rel="noopener noreferrer">Explore all integrations</a><h3> </h3><h3 id="isPasted">Why do researchers build on Xsens integrations? </h3>Outputs are validated through peer-reviewed research, so the joint angles, segment positions, and accelerations you import are ready for in-depth analysis. <ul><li>Live stream or export, your choice：Send motion data in real time for closed-loop setups and biofeedback, or export recorded sessions for offline processing. </li><li>Hardware and software in one workflow：Combine Xsens motion capture with third-party hardware such as EMG, so kinematics and muscle activity land in the same recording. </li><li>Capture beyond the lab：Sensor-fusion algorithms maintain accuracy even in magnetically disturbed environments, which allows you to collect data at home, in the field, or outdoors and still do the analysis with clean data.</li></ul> <h3 id="isPasted">Live stream or export, the choice is yours </h3>Xsens Analyze gives you two ways to connect, and you can mix them across a project: <ul><li>Live stream. Push real-time kinematics into compatible software for instant visualization, biofeedback, or synchronized capture with other hardware.</li><li>Export. Save a recording and bring it into your analysis package for joint kinetics, musculoskeletal modeling, or ergonomic assessment.</li></ul>Both paths use the same validated data, so a quick live session and a deep offline study draw on one source of truth. <h3 id="isPasted">Integrations built for research </h3>Five connections cover the workflows most labs ask for first. Each one takes Xsens kinematics and turns it into the specific output. Delsys Surface EMG. Synchronize muscle activity with full-body kinematics so you can see how movement and muscle effort relate inside the same recording. Useful for gait, sports performance and science, and rehabilitation studies. BoB Biomechanics Musculoskeletal modeling. Drive a Biomechanics of Bodies model with Xsens motion to estimate muscle forces, joint loads, and activations from movement you captured in the field. AnyBody The AnyBody Modeling System computes internal loads, muscle forces, and joint reactions. Feed it Xsens kinematics to ground a musculoskeletal simulation in real, recorded movement. Siemens Process Simulate Digital manufacturing and ergonomics. Bring real human motion into Process Simulate to validate workstation reach, posture, and ergonomic risk before a production line is built. Visual 3D Biomechanics analysis. Process Xsens kinematics in Visual 3D to compute joint angles, kinetics, and custom biomechanical models for clinical and sports research. <a href="https://www.xsens.com/integrations/analyze" target="_blank" rel="noopener noreferrer">See the full integrations overview</a> to learn more about the wider set of research and ergonomics tools that can be connected with Xsens. <h3> </h3><h3>Does it hold up in real research? </h3>Researchers use these workflows in published work. The University of Innsbruck assessed the reliability of Xsens Link for running kinematics. At Auburn University, Iván Nail-Ulloa measured the strain of lifting heavy manhole covers to make the task safer. At Saxion University of Applied Sciences, teams combined Xsens motion capture with pressure sensor data to quantify kickboxing rehabilitation. More than 500 universities, institutes, and research facilities use Xsens today.  <h3 id="isPasted">The hardware and software behind your data</h3>XSENS LINK<ul><li>Full-body eSuit for high-intensity movement, with a wireless range up to 150 meters and offline capture for work outside the lab.  </li></ul>XSENS AWINDA<ul><li>Easy-to-wear, strap-based system for everyday movement analysis.</li></ul>XSENS ANALYZE  <ul><li>Software that visualizes movement live, then streams and exports into third-party analysis tools.</li></ul><a href="https://www.xsens.com/health-sports/research-education" target="_blank" rel="noopener noreferrer">See Xsens products for research </a> <h3>FAQs</h3>Which software can I connect to?  Xsens Analyze connects to biomechanics, modeling, and ergonomics tools including Delsys, AnyBody, BoB Biomechanics, Siemens Process Simulate, Visual 3D, OpenSim, and more. The table above lists the current set, and the integrations overview holds the full list. Can I export my data to other tools? Yes. Xsens Analyze exports recordings in formats used across research so your analysis software can read the data. Common research exports include C3D and MVNX. Confirm the exact formats for your version with the Xsens team. Can I stream motion data in real time? Yes. For compatible tools you can live stream kinematics for instant visualization, biofeedback, or synchronized capture with other hardware. Do I need a lab to collect usable data? No. Xsens captures lab-quality kinematics anywhere, and the sensor fusion holds accuracy in magnetically disturbed environments, so you can record at home, on the field, or outdoors. Is the data accurate enough for publication? Xsens outputs are validated through peer-reviewed research and used by more than 500 universities and research institutes. Can I record muscle activity alongside motion? Yes. Through EMG integrations such as Delsys and Cometa Systems, muscle activity and full-body kinematics land in the same synchronized recording.

With MVN Analyze

Xsens Integrations for Research

Humanoid Robot (Shanghai) Co., LTD uses Xsens mocap and AI to train humanoid robots to mimic human movement and perform complex tasks. &nbsp;Key takeaways:<ul><li id="isPasted">Humanoid robots are here to stay: The humanoid robotics market is projected to grow significantly, from $1.32 billion in 2023 to $38 billion by 2035, showcasing robust growth.</li><li>Advancements in robot precision: Modern humanoid robots are increasingly mimicking human motion with high precision, thanks to the unique tandem of motion capture technology and AI learning algorithms.&nbsp;</li><li>Role of motion capture technology:&nbsp;Motion capture technology is essential for accurately training robots by capturing and replicating human movements in real-time, though the processes of teleoperation and human shadowing.&nbsp;</li><li>Humanoid Robot (Shanghai) Co., LTD’s success:&nbsp;The company excels in humanoid robotics by leveraging Xsens motion capture technology, enhancing robot precision and capabilities for various industrial tasks.&nbsp;</li><li>AI and scalability in robotics:&nbsp;AI, combined with Xsens scalable motion capture, allows robots to learn from human data, adapt to different environments, and continuously improve performance.</li></ul>The word robot was first introduced by Czech writer Karel Čapek in the 1920’s to describe creatures that looked and moved like humans but used only to perform hard labor. In recent history, the human mind has been captivated by robots, both in science and science fiction. Our pursuit of creating machines that mimic or surpass human capabilities to fulfill tasks, both mundane and complex, has brought us a long way. &nbsp;The humanoid robotics industry is one of the fastest growing sectors in 2024, contributing a whopping $1.32 billion in market share as of today and projected to reach <a href="https://www.goldmansachs.com/insights/articles/the-global-market-for-robots-could-reach-38-billion-by-2035" target="_blank" rel="noopener noreferrer">$38 billion in 2035</a>. Major players such as Tesla, Ubitech, Nvidia, Boston Dynamics, and others have been giving us sneak peaks and flaunting their intelligent robots, quickly bridging what was once considered science fiction and today's reality. &nbsp;In the near future, robots are expected to perform a broad range of tasks, from folding laundry to operating complex machinery. While household helpers and robot first responders are still in development, the gap between fantasy and reality is narrowing. These robots are becoming more intuitive, adaptive, and human-like. &nbsp; &nbsp;Modern humanoid robots not only resemble humans more closely but also mimic human motion with remarkable precision. A key to this rapid advancement is their ability to learn from humans in real-time through a process often referred to as human shadowing. <a href="https://www.movella.com/products/motion-capture" target="_blank" rel="noopener noreferrer">Motion capture</a> technology plays a critical role in this process. This is how it works: a person performs tasks multiple times, while every detail of his movement is carefully captured using motion capture technology. In the process of teleoperation, a robot performs the same operation next to the person, literally learning how to move through recorded motion data, and, using AI and deep learning, incurring all the possible options for future movement. By analyzing data from human motion, these robots can be trained to improve their dexterity and coordination, making them more prepared for real-world applications.&nbsp;Humanoid Robot (Shanghai) Co., LTD has been a prominent player in this field, gaining attention at the recent World Robot Conference. The company has developed several generations of highly bionic humanoid robots designed for tasks in the manufacturing industry, including product sorting and assembly. Its focus on precision, adaptability, and artificial intelligence positions Humanoid Robot (Shanghai) Co., LTD as a key player in meeting future demands across various sectors.&nbsp;In the pursuit of building humanoid robots capable of replicating human-like actions, the company has chosen <a href="https://www.movella.com/products/motion-capture" target="_blank" rel="noopener noreferrer">Xsens motion capture</a> technology to train and refine its robots’ movements. This collaboration has enabled the company to make significant progress. &nbsp;&nbsp;We sat down with the team at Humanoid Robot (Shanghai) Co., LTD &nbsp;to talk about its use of motion capture to train humanoid robots, the role of AI and what the future holds. &nbsp;The importance of accurate motion data&nbsp;Data precision is crucial in training humanoid robots, as it directly affects their ability to replicate human movements accurately. Even minor errors in motion data can lead to mishandling or damage, especially tasks requiring fine motor skills or in robot-human interactions. &nbsp;Any inaccuracy in the initial data can compound errors in learning, leading to inefficient or imprecise movements. &nbsp;With this in mind, and after testing several alternatives, Humanoid Robot (Shanghai) Co., LTD selected Xsens inertial motion capture solution for the task. As the team explained: &nbsp;"We tested a lot of different motion capture solutions, both optical and inertial. The optical solution had problems of space limitation, so we wanted to use inertial motion capture. With inertial systems there is a problem of drift – when the motion data doesn’t align perfectly with the real movement. Xsens turned out to be the only inertial solution that had no data drift issues."&nbsp;The robots are currently being taught various tasks, such as handling small objects and walking with great precision. One demonstration of the robots' abilities is its fine work with object identification and transfer: "We can control the robot to achieve the fine work of sorting out red beans from soybeans."&nbsp;AI and motion capture: A perfect partnership&nbsp;The second critical aspect of the learning process for humanoid robots is Artificial Intelligence. &nbsp;&nbsp;As noted by Humanoid Robot (Shanghai) Co., LTD, motion capture and AI are used in tandem to give robots the human capabilities to move, interact with their environment, make autonomous decisions, and perceive, recognize, and respond to external stimuli intelligently.AI uses data from motion capture to create models that help robots learn how to interact with their surroundings. A key component of this process is building a large data pool for training—covering a wide range of movement patterns, responses, and problem-solving techniques. Xsens allows for unlimited scalability by enabling multiple workers wearing Xsens suits to simultaneously perform tasks. These tasks are then captured and replicated by humanoid robots, while creating a rich data foundation that allows robots to adapt and respond to diverse situations.&nbsp;By scaling data collection with Xsens, robots can mimic human actions with remarkable accuracy while dynamically adjusting to different environments and tasks. Additionally, AI optimizes this motion data by learning from errors, enabling continuous improvement without human intervention.&nbsp;As Humanoid Robot (Shanghai) Co., LTD explains, AI further streamlines its processes by automatically annotating collected data, significantly improving the efficiency of its training programs. The combination of AI and Xsens’ high-precision motion capture has allowed the company to push the boundaries of what’s possible. &nbsp;Looking ahead: the robotized future&nbsp;The company sees humanoid robots as a transformative force across industries. "Humanoid robots have a very large potential, and there will be a huge demand in the future in industry, business, and eventually in the consumer side. For example, many countries are currently facing the problem of aging populations and insufficient labor. Future humanoid robots can solve these problems well, and it can also create more new jobs and form a new industrial revolution." The company predicts that robots will not only fill workforce gaps but also create new jobs and revolutionize entire sectors.&nbsp;Achieving this vision of the future starts with teaching robots how to be more human-like, and Xsens motion capture that has typical use in areas such as animation and healthcare, is now playing a vital role in teaching robots how to move like us, humans. With its high precision, scalability, real-time data processing, and freedom to capture movement in any environment, Xsens meets all the critical requirements for a tool to train humanoid robots. &nbsp;Humanoid Robot (Shanghai) Co., LTD’s collaboration with Xsens highlights the potential of advanced motion capture in shaping the way humanoid robots move in the future. Combined with AI, <a href="https://www.movella.com/products/motion-capture" target="_blank" rel="noopener noreferrer">Xsens motion capture</a> is helping the company make massive strides in realizing a long held human ambition – creating robots in our own image. &nbsp;&nbsp;

With Xsens MVN Analyze

Motion capture: Teaching humanoid robots how to move like humans

<h3 id="isPasted">Building a cinematic experience with a small indie team</h3>A six-person college team brought a branching sci-fi adventure on Venus to life with <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens motion capture</a>, Manus gloves, and Unreal Engine 5, capturing 83 pages of performance in six days.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1785322794225-Vesperi+Indie+Game+Post+-+Main.jpg" style="width:100%px" class="fr-fic fr-dib" /><pre>Behind the scenes: an actor Dareionte’ Kinder up in the Xsens system during a Project Vesperi capture session</pre><a href="https://store.steampowered.com/app/2536670/Project_Vesperi/" target="_blank" rel="noopener noreferrer">Project Vesperi</a> is a cinematic, branching-narrative sci-fi game set in 2083, where Earth's resources have run dry and the Unified Nations of Earth have turned to the solar system in search of life. Players step into the boots of Dr. Evelyn Roth, an astrobiologist sent to a research outpost on Venus called Geyser Canyon Station to investigate a possible sign of life. When an intruder threatens the only habitable station on the planet, every choice the player makes reshapes the fate of the crew, and of humanity itself.What began as a thesis project for Chapman University students grew into the debut release of indie studio <a href="https://www.lastpraetorianinteractive.com/" target="_blank" rel="noopener noreferrer">Last Praetorian Interactive</a>. The game launched on Steam and the Epic Games Store with movie-length scope, lifelike character performances, and more than ten endings, all built by a small student team using accessible tools and a lot of determination."We always played choose-your-own-adventure games where your choices matter. We really wanted to make our own branching narrative, and in this case, one about a sign of life on Venus. That was the inspiration at the onset, and it evolved from there."Brandon Hill, Director and Creative Lead, Last Praetorian Interactive<h3 id="isPasted">Cinematic ambition on a student budget</h3>Brandon Hill and Trevor Gore came from a film background, not a games one. They wanted Project Vesperi to feel less like a typical video-game cutscene and more like cinema, with real actors delivering real performances. That ambition collided with the reality of student life: a tiny team, no dedicated capture stage, a borrowed equipment window, and almost no prior motion capture experience between them.Hill first proved out the tone of the game by building a concept teaser in Unreal Engine using animations he found online, simply to show people what the project could become. The teaser did its job, the professors got behind it, and one animation professor pointed the pair toward a motion capture suit that was sitting unused for the summer. There was no class on how to operate it, no in-house games pipeline for it, and no second suit to pair actors together. The team had a single suit, a cast of five or six actors, and an 83-page script to capture."Nobody on the team had any experience with motion capture. We came in a little blind and eager to learn the whole process."Trevor Gore, Writer and Production Lead, Last Praetorian Interactive<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1785322909171-Vesperi+Actor+run.jpg" style="width:100%px" class="fr-fic fr-dib" /><pre>Actors Sophia Khan and Julia Cornell run a scene in a folded-open research pod, with the capture station and taped floor marks in view. The portable Xsens system meant no permanent stage was needed.</pre><h3 id="isPasted">One portable Xsens suit, a whole production</h3>The team used the suit from the film school's equipment room and held onto it for the entire summer. Hill taught himself the system from the Xsens documentation and tutorial videos, then ran his own tests at home and across different locations to dial in strap placement and connection quality. By the time the capstone class started in the fall, the plan was to walk in on day one with all the mocap already done, so there would be no question about whether the game could be made.Because the Xsens system is inertial and portable, the team did not need a permanent stage. They shot inside the Fowler School of Engineering's bookable research pods, folding back a partition wall to open up a long corridor with enough runway for the script's running and action beats. The portability also let them keep all the sound in one place: lavalier mics went on the suits, a boom operator worked the room like a film set, and most of the dialogue players hear in the game was recorded live on the day of the shoot rather than replaced later."We wanted voiceover-booth quality sound in an interior space. Most of the dialogue you hear in the game was recorded with the mocap on the day, as opposed to going back and replacing it later. We really wanted to get it all in one go."Brandon Hill, Director and Creative Lead, Last Praetorian InteractiveWith only one actor in the suit at a time, the team rehearsed each scene like a stage play, marking positions with tape on the floor, then captured the same scene several times, once per character, and synced the performances together in the same space. In six days, the studio captured roughly 83 pages of script using that single suit. Each take was processed in the Xsens software and imported into Unreal Engine 5, where the team checked for foot slide before committing it.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1785322961450-Vesperi+Indie+Game+Post+-+5.jpg" style="width:100%px" class="fr-fic fr-dib" /><pre>The team worked the room like a film set, adjusting an actor's facial-capture rig between takes.</pre>The part that mattered most for a two-person animation team was cleanup, or rather, the lack of it. Going through 83 pages of motion across multiple characters by hand was not feasible at the team's size, and other mocap solutions they had looked at demanded heavy manual correction on nearly every take. The Xsens HD reprocessor removed that bottleneck entirely."That was the incredible part. The Xsens HD reprocessor was a game changer. Any of the jitters or pops or things we would normally have to go back and clean up were suddenly fixed. I set it up and ran it on our school laptop, came back, and all the mocap was polished. I thought, this is incredible."Brandon Hill, Director and Creative Lead, Last Praetorian InteractiveWith jitter and foot-pop handled automatically, the remaining animation work came down to creative choices and specific prop interactions rather than technical firefighting. For a later pickup shoot, the team upgraded the pipeline further, adding Manus gloves for finger capture and an iPhone with Epic's MetaHuman Animator for higher-fidelity facial performance, focusing on the key moments that needed it most. For Gore, the low-cleanup workflow was decisive in choosing Xsens in the first place."Production-workflow-wise, additional cleanup would have been next to impossible to factor in. Keeping that low-stress was a big deal, and it was one of the big reasons we went with Xsens."Trevor Gore, Writer and Production Lead, Last Praetorian Interactive<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1785323261417-Vesperi+Indie+Game+Post+-7.jpg" style="width:100%px" class="fr-fic fr-dib" /><pre>Fitting the Manus gloves for a follow-up pickup shoot, which added finger capture to the pipeline.</pre><h3 id="isPasted">A shippable, cinematic indie game</h3>Project Vesperi grew from a capstone assignment into a full indie release under Last Praetorian Interactive, developed in the team's free time around full-time jobs and graduate studies. The finished game delivers movie-length, replayable storytelling with more than ten endings, lifelike performances, and tense action sequences, all built by a small student-turned-indie team using largely free and accessible tools.Motion capture was central to that outcome. The Xsens system gave a tiny, first-time team the portability to capture anywhere, the audio flexibility to record performances live, and an automated cleanup workflow that removed the single biggest bottleneck for a two-person animation crew. The result is a game that punches well above its budget, and a team that came out the other side with real production experience and a debut title on Steam and Epic."This grew into a full indie project that people were really excited about. At this point it has been a passion project for everyone involved."Brandon Hill, Director and Creative Lead, Last Praetorian Interactive

how Last Praetorian Interactive made Project Vesperi with one Xsens suit

From student thesis to indie debut

Creature combat needs more than movement.For Lords of the Fallen, the dark-fantasy action-RPG developed by HEXWORKS, a CI Games studio, <a href="https://www.creaturebionics.com/" target="_blank" rel="noopener noreferrer">Creature Bionics</a> helped deliver motion capture and casting for a world built around weapons, monsters, cinematic movement, and heavy combat. At the center of that work was Ace Ruele, founder of Creature Bionics, whose background brings together acting, motion capture, creature performance, casting, and direction.For a project like Lords of the Fallen, that mix mattered. The team needed performers who could handle swords, creatures, combat systems, and unusual body mechanics. They also needed a capture workflow that could move fast, work remotely, and deliver high-quality motion data for AAA-ready character work.<a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens</a> helped make that possible.<h3>When fantasy combat needs more than clean movement</h3>Lords of the Fallen is built around dark fantasy, medieval-inspired worlds, creatures, and intense combat. Ace described the project as a fantasy game with a strong focus on combat systems, creature work, and the feel of dark, Soulslike worlds.That kind of production puts real pressure on motion capture. The work is not only about recording clean movement. It is about finding the right performer, shaping the action, reviewing the result, and repeating the process until the motion fits the character.For Ace, motion capture was the right foundation because it gave the team access to real performance.“Motion capture makes it more real,” Ace explains. “You can get the real emphasis of character performance, those nuances that you may not find in hand animation.”The challenge was to keep that realism while capturing fast combat, creature movement, falls, rolls, jumps, and weapon-led action across a flexible production setup.<h3>How Xsens kept capture flexible across locations</h3>Xsens gave Creature Bionics a way to capture performance wherever the action made sense.Shoots could happen in different spaces, from halls to larger rooms, smaller rooms, outside areas, and quick recapture setups. Much of the work was handled remote mocap game studio, with the team tuning in while Ace operated the Xsens setup and directed the performance capture on the floor.Instead of being tied to a fixed stage, Creature Bionics could adapt around the movement. If a character needed more room to run, the team could go outside. If a move needed to be captured again, it did not require rebuilding a full capture volume.Ace recalls how simple the working setup became: “All you needed was a space and one operator.”That flexibility made Xsens part of the creative feedback loop. Before a shoot, Ace would align with the team on characters and reference material. During capture, he could direct the performer, operate the system, and share the Xsens screen with the remote team. After delivery, the game team could test the data on the character and request specific adjustments when the performance needed to change.“We never really did a reshoot on a whole character,” Ace explains. “We might just reshoot movements if there was a better way to do the movement.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1783500107504-Ace+Ruele+-+Lord+of+the+Fallen+Customer+Case+-+Xsens+Link+2.jpg" style="width:100%px" class="fr-fic fr-dib" /><a href="https://www.xsens.com/motion-capture/xsens-link-specifications" target="_blank" rel="noopener noreferrer">Xsens Link</a> gave Creature Bionics the freedom to capture physical creature movement in a flexible production setup.<h3 id="isPasted">Making high-impact action easier to capture</h3>For Creature Bionics, the priority was always the performance. Some combat actions required performers to change grip, release props, or work through fast choreography. In those moments, the team made practical production choices around each move, so the performer could focus on body mechanics, timing, weight, and intent.That approach helped keep the movement natural. The team could focus first on how a character attacks, recovers, absorbs impact, or changes direction. From there, the wider animation pipeline could support the final character and weapon work.For impact work, the team also planned around the performer and the suit. If a performer needed to drop onto a crash mat or roll, they adjusted the setup to protect the hardware and keep the movement safe. The value was that these moments could be seen, reviewed, and solved during the session.“There was nothing really specific to Xsens where we couldn’t do something,” Ace says. “We would always see it anyway. We would just reshoot it.”That same production feedback connects naturally to the next-generation Xsens Link. With modular hub placement, teams can position the hub where it fits the performance best, including high-impact movement where back placement may not be ideal. For stunt, combat, and creature work, that gives performers more freedom while helping productions keep the reliability and data quality Xsens is known for.<h3>What Xsens made possible for Creature Bionics</h3>For Lords of the Fallen, Xsens helped Creature Bionics support a large volume of character movement with speed, flexibility, and remote production support.The strongest outcomes were clear: capture could happen across multiple locations, the remote team could review motion during the session, and reshoots were mainly used to improve performance choices rather than fix broken data. Ace estimated a typical Xsens setup at around 20 to 30 minutes from laptop and suit setup through calibration, which helped keep the process practical and efficient.That changed the role Creature Bionics could play. Ace was not only arriving as a performer. He could provide motion capture, help cast performers, direct movement, and support production from a broader creative and technical position.“Having the suit gave me the opportunity to be like a coordinator,” Ace says. “It was being a part of the production rather than just being the actor.”For human and creature performance sessions, Xsens gives teams the speed, flexibility, and high-quality motion data needed to keep production moving. For Creature Bionics, that flexibility helped turn motion capture into a broader production service. It was not only about data. It was about performance, casting, direction, and giving the team a way to keep characters moving.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1783500171042-Ace+Ruele+-+Lord+of+the+Fallen+Customer+Case+-+Xsens+Link+3.jpg" style="width:100%px" class="fr-fic fr-dib" />Ace Ruele uses Xsens Link with creature stilts to capture non-human movement for fantasy character performance.<h3 id="isPasted">Meet Creature Bionics</h3>Creature Bionics focuses on creature and fantasy character performance. The company supports productions from early character development through performance direction, casting, training, mocap, and practical creature movement work.Ace explains the idea simply: how do you take a creature that can be performed by an actor and help that actor create the strongest possible performance?That includes understanding the physical demands of a character, advising on what can be handled through VFX, stunts, wires, mocap, or practical movement, and then helping cast or train the right performer. In some cases, Creature Bionics also builds quick previs using real-time tools, giving directors and teams an early look at how a creature could move before the final asset is ready.“We’re actor focused, we’re performance focused,” Ace says. “How do we get a creature that can be played by an actor to create the best performance?”For Lords of the Fallen, that meant Creature Bionics was not only providing mocap data. It helped connect performance, casting, direction, and capture into one flexible production workflow.

With Xsens Motion Capture

Lords of the Fallen: capturing creature combat

<h2 id="isPasted">Meet HanaX, a one-person virtual studio</h2>HanaX is a virtual artist, performing live through a digital body in a fully immersive world where experience is no longer bound by reality. She performs as her characters, singing, moving, and expressing in ways that blur the line between physical and virtual presence.Her work spans multiple platforms. On Twitch, she delivers interactive virtual live concert experiences. On YouTube, she releases cinematic content and music-driven storytelling, powered by tools like Unreal Engine, Blender, and motion capture.What looks like a full production team is built and performed by one person. Behind the scenes, she operates as a one-person virtual studio, creating stories, building characters and worlds, producing music, and directing cinematic experiences within her own digital environment. <h3>Why VTubing became the perfect medium</h3>HanaX has always been both a performer and a storyteller. Her early on-camera music content performed well, but it felt limiting in bringing her full vision to life. She wanted more than singing on camera. She wanted the freedom to tell stories beyond herself.VTubing solved that.It enabled her to step into different characters, tell their stories, and build entire worlds around them. At the same time, it removed traditional production limits. No need for physical locations, large crews, or expensive setups. Instead, she could create on her own terms. <h3>Starting from zero, building a pipeline from scratch</h3>She started from zero, with no 3D or motion capture background. It was challenging, but it also gave her a blank canvas. Drawing from public tutorials and documentation, she built her own approach and designed an efficient, performance-first pipeline.Motion capture quickly became central to that process.At first, she experimented with more accessible solutions, including VR and hand-tracking systems. As she became more serious, she moved to a strap-based inertial motion capture setup. It worked well enough to get started, but over time, limitations became clear.During live streams, small technical issues became very visible. Characters would slowly drift, bodies would twist, and maintaining a stable performance required constant attention.For recorded content, the problem shifted into post-production. Animations often needed significant cleanup, especially with fingers and body alignment. What started as creative work turned into technical correction.At the time, she assumed this was simply how motion capture worked.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1780995514245-HanaX+BTS+-+Ocean+3.png" style="width:100%px" class="fr-fic fr-dib" />Behind the scenes with HanaX using Xsens Mocap and Manus gloves for OceanX production <h3 id="isPasted">The moment everything changed</h3>That changed when she started using <a href="https://www.xsens.com/entertainment/motion-capture-for-indies" target="_blank" rel="noopener noreferrer">Xsens</a>. The difference was immediate. Everything simply worked.One moment stood out. She could stand in the same position for hours, without drift, without recalibration, without interruption. She did not have to adjust her movement to fit the system. The system matched her. She could just perform.“It was such a small thing, but it felt incredibly liberating.” — HanaXIt sounds simple, but in a live performance context, it changes everything. The system stopped being something she managed and became something she performed through.<a href="https://www.youtube.com/watch?v=JRS9gjtulOY" target="_blank" rel="noopener noreferrer">Watch her Xsens unboxing and first impressions.</a> <h3>From fixing problems to creating content</h3>The biggest impact of switching to Xsens was not just better data, it was how it changed her workflow. Before, a significant part of her time went into fixing issues. Animations needed correction, recordings needed cleanup, and technical work often came before creative work.After switching, that balance flipped. The time previously spent repairing animations could now be used to improve them. Instead of bringing poor data up to an acceptable level, she could focus on making good data even better.As she describes it, the improvements were incremental, but they added up quickly, and over time, reliability simply became the default. <h3>Supporting creative flow</h3>Another key change was continuity. Creative work depends on momentum, and interruptions, whether from tracking issues or battery limitations, break that flow. Previously, this was a recurring issue. Sensors would run out of power mid-session, forcing retakes or pauses.With Xsens, that concern disappeared. When you are in a creative flow, you do not want to stop because something technical fails.That reliability allowed her to stay focused on performance, especially during longer recording sessions or live streams. <h3 id="isPasted">A setup that scales with creativity</h3>Beyond performance, the physical setup also played a role.Moving from a strap-based system to a full suit changed how she interacted with motion capture. What she initially expected to be less convenient turned out to be the opposite. With sensors integrated into the suit and a unified charging workflow, setup became faster and more consistent.Support also stood out as part of the experience. During onboarding, she worked directly with Xsens specialists who understood both the technology and the creative challenges behind it.That combination made it easier to move from setup to production. <h3>Inside HanaX’s performance pipeline</h3>Today, HanaX runs a cohesive, performance-first pipeline, built to capture, render, and deliver in real time.<ul><li>Motion capture with <a href="https://www.xsens.com/entertainment/motion-capture-for-indies" target="_blank" rel="noopener noreferrer">Xsens</a></li><li>Hand capture with <a href="https://www.xsens.com/motion-capture/xsens-metagloves-by-manus" target="_blank" rel="noopener noreferrer">Manus gloves</a></li><li>Real-time creation and rendering in Unreal Engine</li><li>Character creation in Blender</li><li>Editing in Premiere Pro and After Effects</li><li>Live, interactive experiences on Twitch</li><li>Additional tools like Leap Motion and VTubing software, such as Warudo</li></ul>What makes this setup unique is not just the tools, but how they are used together.During her live streams, viewers can become part of the performance. They can appear as avatars on stage, dance alongside her, trigger stage effects, or throw virtual elements in real time. This level of interactivity depends on stable, real-time motion capture as a foundation.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1780995663194-HanaX+Customer+Case+Xsens.png" style="width:100%px" class="fr-fic fr-dib" />HanaX performing live during a charity event, raising $9,706.96 for children in hospitals, with her virtual character powered by Xsens mocap <h3 id="isPasted">Looking ahead</h3>With the foundation in place, HanaX is channeling years of experimentation into more ambitious, performance-driven work, expanding beyond her own universe.Recent work includes collaborating with OceanX to create their mascot and develop a lore-driven short film, as well as working with other artists on full-band performances. Motion capture remains central, enabling character-driven storytelling and multi-character performance.Looking ahead, she is developing original music, new collaborations, and larger-scale virtual productions, continuing to push real-time performance forward.And she is only just getting started. <h3>A workflow built for creativity</h3>For HanaX, switching to Xsens was not just about improving motion capture quality.It changed how she creates.By removing technical friction, it allowed her to focus on performance, storytelling, and continuous improvement. What started as a workaround-driven process became a reliable, scalable workflow.And for a one-person studio, that difference is everything.“It just works. You don’t notice it anymore, because everything works.” — HanaX <h3 id="isPasted">Want to build your own VTuber or virtual production pipeline?</h3>Discover how Xsens helps professionals capture high-quality motion anywhere, with less setup and more control.<a href="https://www.xsens.com/entertainment/motion-capture-for-indies" target="_blank" rel="noopener noreferrer">Explore the Xsens Indie Program</a>

With Xsens

How VTuber HanaX built a high-quality virtual production workflow

Building a cinematic experience with a small indie teamA small team. A bold creative vision. A game designed to feel like cinema.When Sandfall Interactive began development on Expedition 33, the studio wanted to create an experience where storytelling, atmosphere, and performance would stand at the center of the game. The French indie studio, consisting of around 30 people at the peak of production, aimed to blend cinematic presentation with turn-based gameplay in a way that felt immersive and emotionally grounded.Rather than treating cinematics as separate moments between gameplay sections, the team wanted the entire experience to feel cohesive. Character movement, subtle performances, camera work, and pacing all needed to support the emotional tone of the story. The ambition was not simply to create cutscenes, but to build scenes that felt closer to film production than traditional in-game cinematics.As Tristan Fleury, Cinematic Animator at Sandfall Interactive, explains: “We wanted something very similar to cinema. Not a typical video game cinematic, but something that feels like a movie.”That cinematic ambition became one of the defining creative pillars of the project. At the same time, the reality behind development looked very different from a large AAA production. Sandfall was still a relatively small independent studio, working with limited resources, limited space, and a compact production team.Many members of the team were also entering motion capture production for the first time. They needed a workflow that would allow them to move quickly, stay flexible, and maintain high production quality without slowing down creativity. <h3>The challenge of producing cinematic-quality animation efficiently</h3>Creating a cinematic game at this scale introduced major production challenges from the start.The team needed to produce more than four and a half hours of cinematic content while maintaining consistency across character performances and animation quality. For larger studios, this type of production often depends on dedicated optical motion capture stages, extensive capture crews, and highly structured production schedules.For Sandfall, that approach would have created too much complexity.The studio needed a motion capture workflow that could fit naturally into an agile indie development environment. Speed and flexibility were critical. The team needed to be able to capture performances quickly, refine animations efficiently, and iterate without constantly blocking production.William Tomasi, Cinematic Artist at Sandfall Interactive, explains how important speed became throughout development: “We didn’t have a lot of time because we had four and a half hours of cinematics, so we had to be smart and be quick.”Another challenge was physical space. Traditional motion capture setups often require permanent studio environments and large capture areas. Sandfall did not have the luxury of a dedicated mocap stage. Instead, the team needed something portable and adaptable that could move with production requirements.On top of that, the cinematic team constantly refined scenes during development. Animations changed, sequences evolved, and additional performances were often needed late in production. A slow or rigid workflow would have made iteration difficult and time-consuming.The team needed a solution that could support creativity instead of slowing it down.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1780994046115-Clair+Obscur+Expedition+33+Case+4.png" style="width:100%px" class="fr-fic fr-dib" />Real performances, transformed into the cinematic characters of Expedition 33 with Xsens motion capture. <h3 id="isPasted">How Xsens fit naturally into Sandfall’s workflow</h3>Through the <a href="https://www.xsens.com/entertainment/motion-capture-for-indies" target="_blank" rel="noopener noreferrer">Xsens Indie Program</a>, Sandfall Interactive acquired an Xsens motion capture setup that allowed the studio to start building its cinematic pipeline quickly and efficiently.For many on the team, working with motion capture was entirely new. Instead of facing a complicated onboarding process or technical barriers, the team was able to begin capturing performances almost immediately.William recalls how approachable the process felt from the beginning: “He just gave me an <a href="https://www.xsens.com/motion-capture/xsens-link-specifications" target="_blank" rel="noopener noreferrer">Xsens suit</a> and said, ‘Do the cinematics with it.’ It was really easy to get started.”That accessibility quickly became one of the biggest strengths of the workflow.Because the <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens setup</a> was portable, Sandfall could capture motion in multiple environments depending on production needs. The team recorded performances in the office, at home, and in temporary rented spaces, allowing motion capture to remain flexible throughout development.Instead of building production around the technology, the technology adapted to the production.Xsens also integrated smoothly into the team’s Unreal Engine pipeline. By using the Xsens presets and a consistent skeleton structure across characters, the team simplified retargeting and reduced technical overhead during production.As Tristan explains: “It was pretty easy to retarget into our character in Unreal… because we used the same skeleton for all characters.”The workflow itself was designed around speed and efficiency. After capturing performances, the team processed the data through Xsens software before refining animations directly inside Unreal Engine. This reduced unnecessary switching between tools and allowed the cinematic team to continue working inside the environment where scenes were already being built.That production speed became especially valuable whenever changes were needed. If the team realized an animation was missing or wanted to improve a sequence, they could quickly capture a new performance themselves instead of waiting for additional shoot days or external resources.“We just put the suit on ourselves and in maybe one hour we had the animation done,” says William.For a small team working on a cinematic-heavy game, that ability to iterate rapidly became a major production advantage.<iframe width="640" height="360" src="https://www.youtube.com/embed/_RnWiaLz4ss??si=kLSrd8x-zG7-j_3K&amp;wmode=opaque" frameborder="0" class="fr-draggable"></iframe>Behind the scenes of Expedition 33, real performances captured with Xsens and transformed into cinematic in-game animation. <h3>From indie ambition to worldwide recognition</h3>By combining a strong artistic vision with a fast and flexible motion capture workflow, Sandfall Interactive was able to create a cinematic experience that resonated with players far beyond the studio’s original expectations.Expedition 33 became widely recognized for its atmosphere, storytelling, character performances, and cinematic presentation. Despite being developed by a relatively small indie team, the game stood alongside much larger productions in terms of visual quality and emotional impact.The efficiency of the Xsens workflow allowed the team to focus more time on creative refinement and storytelling instead of technical limitations. Rapid iteration, flexible capture sessions, and smooth Unreal Engine integration helped the team maintain momentum throughout production.For Sandfall, the response to the game came as a surprise.As William reflects: “We were proud of what we were doing… but the success was a big surprise for us.”Looking back, the team believes the combination of passion, creative focus, and accessible technology played an important role in making the project successful.“If the devs do something that they love, the player will love it,” the Sandfall Interactive team explains.Sandfall Interactive’s journey demonstrates how smaller studios can achieve cinematic-quality storytelling without relying on massive production infrastructure. With the right tools and workflow, indie teams can move quickly, stay creative, and deliver experiences that compete on a global stage.

With Xsens Indie Program

From indie vision to Game of the Year: Sandfall Interactive on building Expedition 33

At New York University’s Tandon School of Engineering, Mario Mercado, founder and CEO of sports technology company <a href="https://batstoi.com/" target="_blank" rel="noopener noreferrer">BATS-TOI</a> and Deputy Commissioner of the New York State Athletic Commission, is collaborating with faculty and students to advance a groundbreaking project that’s redefining the boundaries between digital performance and athletic motion.<h3>The Challenge</h3>Capturing authentic motion for wrestling game, <a href="https://www.tekfallsupreme.com/" target="_blank" rel="noopener noreferrer">Tekfall Supreme</a>, without the occlusion and drift issues that limit traditional motion capture systems.<h3>The Solution</h3>By using Xsens IMU sensors with optical cameras, Mario and the NYU team built a hybrid system capable of recording full-contact wrestling without drift or occlusion. Students operated the setup end-to-end, gaining hands-on experience with the same technology used in professional game studios.<h3>Key benefits</h3><ul><li>Hybrid precision: IMU and optical tracking combine to deliver drift-free, occlusion-proof data – ideal for complex movement.</li><li>Learning through practice: Students gain professional-level skills on industry-standard tools.</li><li>Groundbreaking realism: In an industry first, the game’s unique “struggle mechanic” replicates the tension and dynamic feedback of real wrestling.</li><li>Dual-purpose dataset: The same capture sessions power both game animation and real-world performance analysis, maximising the value of every movement.</li></ul><h3>Preparing students for the industry</h3>Tekfall Supreme began as a creative goal to portray wrestling with the speed, weight, and unpredictability the sport deserves. But the process of building it has also become a live training ground for NYU students. They aren’t just observing mocap; they’re solving real production constraints in real time. Handling performer safety, troubleshooting capture issues during contact, and shaping raw data into usable assets for gameplay.“This project gives students a chance to solve real problems using the same tools as professionals,” says Mario. “They’re learning motion, teamwork, and innovation through experience and helping preserve the authenticity of wrestling culture in the process.”That practical immersion is already influencing curriculum conversations. Rather than focusing on any single vendor, the aim is to formalize the underlying skills, hybrid capture design, IMU fundamentals, optical integration, and data-to-animation workflows, so graduates leave with knowledge that travels across tools and studios.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1778072111047-Tekfall+Supreme+2026+21.jpg" style="width:100%px" class="fr-fic fr-dib" />Tekfall Supreme BTS: Motion capture session with professional wrestlers using <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens mocap technology</a>. <h3>Innovation and insight</h3>Tekfall Supreme also shows how game-grade mocap can create value beyond entertainment. The captured data isn’t only animating digital wrestlers, it’s being repurposed as a motion analysis resource for real ones. Wrestlers and coaches can study technique, precision, and form with a level of detail typically reserved for elite performance labs. By translating the same datasets used to drive digital athletes into actionable feedback for physical training, the project builds a rare two-way bridge between gameplay and athletic development.“Seeing the same movement serve both the game and the athlete is the exciting part,” says Mario. “We’re not just recreating wrestling for players, we’re finding new ways to understand it for the people who live it.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1778072178290-Tekfall+Supreme+2026+3.png" style="width:100%px" class="fr-fic fr-dib" />Tekfall Supreme BTS: Motion capture session with professional wrestlers using <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens mocap technology</a>. <h3>What’s next for NYU and Tekfall Supreme</h3>With continued collaboration from Mario, NYU aims to deepen the connection between technology, athletics, and creative production. Exploring new applications of hybrid motion capture for both digital entertainment and real-world performance analysis.“We’ve only started to explore what hybrid capture makes possible when you treat motion as both a creative language and a source of measurable insight,” says an NYU project lead, Todd Bryant. “The next phase is about scaling that thinking across sport, games, and performance science.”By uniting innovation, education, and athletic insight, the university is nurturing a new generation of storytellers, technologists, and athletes ready to push the limits of human movement and digital expression.

With MVN Link

NYU and Xsens pioneer hybrid motion capture for games

The Department of Human Movement Sciences (UMCG Groningen) is using Xsens to push anterior cruciate ligament (ACL) prevention research into more realistic football settings. From validating sport-specific movement data to testing interventions for implicit learning, the research shows how wearable motion capture can bring injury prevention research closer to the game itself.<h3>Challenge</h3>Researchers in the Department of Human Movement Sciences wanted to study how female football players can better learn movements to reduce the risk of ACL injuries in real-world settings, without compromising biomechanical data quality.<h3>Solution</h3>The team used Xsens to capture full-body motion during sport-specific football tasks, creating a strong foundation for field-based biomechanics and motor learning research.<h3>Key takeaways</h3><ul><li>Movement patterns improved over time: The intervention helped female football players adapt high-risk football movements linked to ACL injury.</li><li>The richest feedback approach worked best: Players improved most when video instruction, self-video, and verbal feedback were combined.</li><li>Xsens enabled on-pitch biomechanics: The team could capture full-body movement outside the lab while maintaining lab-grade precision.</li></ul>ACL injuries can sideline young football players for months. For female players, the risk is even higher. At the Department of Human Movement Sciences (UMCG), researchers aim to understand how these injuries occur during real football actions and how athletes can learn safer ways to move before injury occurs. The researcher Eline Nijmeijer, together with primary investigator Anne Benjaminse, took on investigating high-risk actions, including landing, deceleration, and changing direction, for her PhD thesis <a href="https://research.rug.nl/en/publications/learning-to-move-moving-to-improve-applying-motor-learning-princi/" target="_blank" rel="noopener noreferrer">"Learning to move, moving to improve: Applying motor learning principles to reduce ACL injury risk"</a>. To capture those movements in a way that reflects real training conditions, the team combined several tools for biomechanical analysis and motor learning, including Xsens motion capture.<iframe width="640" height="360" src="https://www.youtube.com/embed/sfFrQH-z0kc??si=s0UBVacGomrBl5CL&amp;wmode=opaque" frameborder="0" class="fr-draggable"> </iframe><h3 id="isPasted">Bringing ACL research closer to the pitch </h3>ACL injuries happen during fast, reactive, sport-specific moments. That is why the research focused on football movements such as sidestep cutting and jump landings, which are closely linked to ACL injury mechanisms. The goal was not only to measure how young athletes move, but also to test how movement patterns can be improved over time. Female football players followed a 4-week training program, and researchers compared baseline and retention measurements to track lasting change. <h3>Why Xsens</h3>For this project, the team needed motion capture that could move with the research. Xsens helped capture full-body movement not only in controlled testing but also on the football field, with lab-grade precision. That portability was essential. “We wanted to measure the players on the field, and we knew that optical motion capture was impossible, but with Xsens it was,” said Eline Nijmeijer. The suit-based setup also played an important role. For dynamic football movements, the researchers preferred the full-body suit because it stayed in place better and supported reliable full-body measurement across repeated sessions. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1778052477073-Eline+Nijmeijer+suit+setup.jpg" style="width:100%px" class="fr-fic fr-dib" /> <h3 id="isPasted">Validated for dynamic sport-specific movement </h3>Before collecting the field data, the team first validated Xsens with an optical motion capture reference in the lab-based part of the research. That gave them confidence that the data collected outside the lab could be interpreted with credibility. The validation study showed excellent agreement for sagittal plane lower body kinematics across all joints and tasks, with cross-correlation values above 0.92. Hip, knee, and ankle flexion and extension waveforms aligned especially well during sport-specific actions such as jump landings, decelerations, and sidestep cuts. Hip measurements in the frontal plane also showed strong agreement. At the same time, the study found more variability in frontal and transverse plane measurements at the knee and ankle, meaning those angles required more caution in interpretation. <h3>A smarter way to coach movement </h3>The key idea behind the research was simple. Athletes do not always learn best from a long list of verbal instructions. Instead of overloading players with detailed cues about knees, ankles, and hips, the researchers used video-based learning. To test the hypothesis, the players were split into four groups: <ul><li>A control group that did not receive any guidance. </li><li>A group that watched a video of the movement they needed to replicate. </li><li>A group that watched the instruction video and, on request, a replay of their own movement. </li><li>A group that received verbal feedback from the test leader, in addition to the instruction and playback videos. </li></ul>That combination mattered. The group that received the richest mix of instruction and feedback showed the greatest improvements over time, especially in hip- and knee-abduction-related variables. The broader takeaway is that implicit motor learning principles acquired through observation can help athletes improve movement patterns during sport-specific tasks. In practice, that opens the door to more effective injury prevention strategies that fit real coaching environments. With Xsens, the Department of Human Movement Sciences is helping push ACL research into a more practical future. By combining biomechanics, motor learning, and wearable motion capture, the team is building a clearer picture of how female football players move, how those patterns can be improved, and how injury-prevention research can get closer to the game itself. Read the full thesis: <a href="https://research.rug.nl/en/publications/learning-to-move-moving-to-improve-applying-motor-learning-princi/" target="_blank" rel="noopener noreferrer">https://research.rug.nl/en/publications/learning-to-move-moving-to-improve-applying-motor-learning-princi/</a>

Studying safer football movement and motor learning

TeleOpBench from Shanghai AI Laboratory introduces a simulator-centric benchmark for dual-arm dexterous teleoperation, comparing four teleop pipelines side by side. In their evaluation, the motion capture pipeline using Xsens Link and Xsens Metagloves by Manus delivered the highest task precision in the shortest time. <h3>Challenge</h3>Teleoperation tools are hard to compare fairly. Different hardware, operators, and task setups make it difficult to know which interface delivers the best combination of speed and precision for dual-arm dexterous work.<h3>Solution</h3>The team at <a href="https://www.shlab.org.cn/" target="_blank" rel="noopener noreferrer">Shanghai AI Laboratory</a> built <a href="https://gorgeous2002.github.io/TeleOpBench/" target="_blank" rel="noopener noreferrer">TeleOpBench</a> in NVIDIA Isaac Sim, running 30 manipulation tasks across three commercial robots (Unitree Robotics H1-2, Fourier GR1-T2, Unitree G1) under one protocol and metric suite, then mirrored a representative subset in a user study and on a physical dual-arm robot.<h3>Key outcomes</h3><ul><li>One benchmark, four pipelines compared: Motion capture (Xsens Link and Manus Gloves), VR, exoskeleton, monocular vision</li><li>Motion capture delivered the highest task precision with the shortest completion time in the reported evaluation</li><li>A repeatable benchmark setup across tasks, operators, and robot platforms, designed for more reliable teleop decisions</li></ul>When building bimanual manipulation for embodied robot learning, teleoperation often provides the fastest path to high-quality demonstrations. The hard part is not only collecting data, but it is also choosing a teleoperation interface you can trust and comparing alternatives fairly.TeleOpBench tackles exactly that gap by introducing a simulator-centric benchmark for dual-arm dexterous teleoperation, built to enable rigorous and reproducible comparisons across competing teleoperation pipelines.<h3 id="isPasted">What TeleOpBench measures and why it matters</h3>Comparing teleoperation systems in the real world is messy. Hardware differences, environment setup, and task variability can easily dominate the result. TeleOpBench uses NVIDIA Isaac Sim to fix the environment and the robot embodiment, then evaluates teleoperation interfaces using consistent success criteria, with task success and completion time as the primary metrics.To test whether the simulator results actually translate, the authors mirror experiments on a physical dual arm platform and report a strong alignment between simulation and real-world outcomes.<h3>Benchmark setup in brief</h3>Robots: three commercially available humanoids spanning different scales and hand designs: Unitree H1-2, Fourier GR1-T2, and Unitree G1Tasks: 30 bimanual manipulation environments, spanning pick and place, tool use, and collaborative manipulation, organized by complexity so that low-fidelity and high-fidelity interfaces can be compared meaningfully.Interfaces: four representative pipelines implemented under one protocol:<ul><li>Motion capture (Xsens Link and Manus Gloves)</li><li>VR device</li><li>Arm and hand exoskeleton</li><li>Monocular vision tracking</li></ul>Evaluation protocol: from the full suite, TeleOpBench selects 10 representative tasks for a user study with four participants, recording success rates and completion times.<h3>The four teleoperation pipelines, conceptually</h3>TeleOpBench is useful because it makes the trade space tangible.<ul><li>Vision tracking reduces hardware requirements but can be sensitive to occlusion and frame rate limits.</li><li>VR improves wrist and hand tracking fidelity compared to monocular vision, and tends to land between vision and higher fidelity systems on performance.</li><li>Exoskeleton offers kinematic alignment and direct mapping advantages, but has its own mobility limits depending on the design.</li><li>Inertial motion capture focuses on capturing body segment motion precisely and mapping it robustly to the robot.</li></ul><h3>Why Xsens Link and Manus Gloves stood out</h3>TeleOpBench’s motion capture pipeline is built around Xsens Links and Manis Gloves.<ul><li>Xsens Link uses 17 IMUs attached to human body segments for limb movement tracking.</li><li>Xsens Metagloves by Manus provide 20 degrees of freedom per hand, capturing detailed finger joint motion.</li></ul><h3>What the results show</h3>Across the reported evaluation, the paper highlights that the Xsens-based method excels in smoothness and motion precision, completing tasks accurately and typically with the least time cost.TeleOpBench also reports that, when plotting completion-time curves, the inertial MoCap pipeline is the fastest, and that simulation and real-world performance show a strong positive correlation.<h3>What this means for engineering and robotics teams</h3>If you are choosing a teleoperation setup to scale demonstration collection, TeleOpBench offers a concrete way to reason about tradeoffs.<ul><li>Throughput: faster completion times can translate to more demonstrations per operator hour.</li><li>Reliability: higher success rates reduce wasted runs and cleanup time in dataset building.</li></ul>

With Xsens MVN Link

TeleOpBench: A Benchmark for Dual-Arm Teleoperation

Reliable biomechanical research outcomes start with reliable data.  If you are diving deep into athletic performance, injury prevention, clinical gait, or ergonomic risk, you need motion data you can trust, and a workflow you can repeat to build your data sets on. That is why the best biomechanical analysis starts with motion capture, combining a wearable data collection system with robust movement analysis software. Modern biomechanics motion analysis is no longer limited to a fixed lab and cameras in a calibrated volume. With wearable inertial motion capture technology, you can capture kinematics data in 3D in the lab, clinic, or real-world environments, while keeping your methods consistent across participants and sessions. Motion data in biomechanical research In most motion research workflows, the goal is to quantify how the body moves during a task and translate those signals into metrics that can be compared across trials, conditions, and populations. Common outputs include: <ul><li>Kinematics: joint angles, segment orientation, range of motion, velocity, acceleration </li><li>Spatiotemporal metrics: step length, cadence, step width, timing </li><li>Symmetry and coordination: left right differences, inter joint coordination </li><li>Task specific outcomes: reach strategy, trunk contribution, movement variability </li></ul>This is where 3D motion analysis becomes essential. You need reliable 3D movement data to compute consistent metrics and support meaningful comparisons in biomechanical research.  How is motion capture used in biomechanics? A typical motion capture system workflow has three stages: 1. Capture movement in 3D Motion capture records segment motion over time and reconstructs a 3D representation of the movement. Many biomechanics teams use IMUs (inertial measurement units) to record linear acceleration and angular velocity. Inertial systems are especially useful when you need portability, fast setup, and capture outside a lab environment. 2. Convert signals into biomechanical variables Raw sensor data becomes meaningful when it is combined with a biomechanical model. This is the role of human movement simulation software. It estimates segment orientations, joint angles, and other kinematic outputs using anatomical modeling and sensor fusion algorithms. 3. Visualize, quantify, and report Finally, researchers use movement analysis software and tools to: <ul><li>visualize movement in 3D </li><li>compute metrics and summary statistics </li><li>compare trials, conditions, or cohorts </li><li>export outputs for further analysis in MATLAB, Python, or other biomechanics toolchains </li></ul> Why motion capture is essential for research in biomechanics and motion analysis Biomechanical engineering research and applied biomechanics have expanded beyond controlled lab tasks. Inertial motion capture adds value because it supports: <ul><li>Repeatability: standardized protocols across sessions and operators </li><li>Real-world measurement: capture in clinics, training spaces, work environments, or outside </li><li>Time efficiency: faster turnaround from capture to results </li><li>Richer interpretation: full body context instead of single point measurements </li></ul>If your work spans multiple environments, wearable motion capture for biomechanics helps maintain a consistent methodology while expanding where research can be conducted.  Choosing a motion capture system for biomechanics research When <a href="https://www.xsens.com/resources/cases/different-types-of-motion-capture" target="_blank" rel="noopener noreferrer">comparing motion capture systems</a>, focus on criteria that protect both data quality and research efficiency.  1. Accuracy and consistency Look for performance evidence in metrics that matter to your studies, such as joint angle repeatability, segment length estimation, and gait measures, including step width. 2. Movement analysis software quality Your biomechanical analysis software should support: <ul><li>clear visualization and review </li><li>detailed outputs for kinematics and spatiotemporal metrics </li><li>export options that fit your analysis stack </li><li>models that align with your population and tasks </li></ul>3. Workflow fit Consider setup time, calibration requirements, portability, and how easily the system fits your protocol. Wearable systems are often chosen for their ability to capture outside the lab and get users running quickly. 4. Validation and support Documentation and validation resources matter when you scale studies or run multi-site projects. Prioritize systems with independent validation studies and a track record of use in peer-reviewed research.  Why Xsens is a strong choice for motion capture for biomechanics Once you understand how motion capture is used in biomechanics, the next step is selecting a system that matches your research goals. Many teams use Xsens because it maps well to common requirements for measuring devices in biomechanical research across lab, clinic, and field work. <ul><li>Capture outside camera volumes: Xsens wearable motion capture supports data collection in environments where optical setups are not feasible. </li><li>Full-body kinematics for biomechanical motion analysis: Xsens Analyze is designed for human motion analysis and supports exporting and integrating data with third-party tools, including MATLAB, in common biomechanics formats. </li><li>A biomechanical model and algorithm that keep evolving: Xsens constantly develops the system, including work on gender-specific models. </li><li>Research and validation resources: <a href="https://www.xsens.com/support/research-validation" target="_blank" rel="noopener noreferrer">Xsens maintains a research and validation hub</a> that helps teams find publications and reference validation work in their methods and discussion sections. </li></ul> Summary Biomechanical analysis relies on accurate 3D human motion measurements. With modern motion capture for biomechanics and strong movement analysis software, teams can run repeatable biomechanics 3D motion analysis in more places, with clearer insights and faster iteration.  FAQ How is motion capture used in biomechanics? Motion capture is used to capture full-body 3D movement, convert that data into kinematic and spatiotemporal variables using a biomechanical model, and report metrics that support research questions in performance, rehabilitation, ergonomics, and human movement science.  What metrics can I get from 3D motion capture biomechanics workflows? Common outputs include joint angles, segment orientations, range of motion, gait timing, step length, step width, symmetry metrics, and task-specific movement strategies.  What is movement analysis software? Movement analysis software processes raw sensor data, applies sensor fusion engine algorithm and a biomechanical model, and outputs interpretable variables that you can visualize, compare, and export for statistical analysis and reporting.

with Xsens motion capture

Precise biomechanical analysis and research

Starting with a remote setup, the Barbie Doll Adventures team produced full seasons of animation from multiple locations. With Xsens inertial motion capture, every performance – from dance numbers to introducing new characters – was captured with precision.ChallengeWith a lean team, fast turnarounds, and lengthy approval cycles, <a href="https://www.youtube.com/playlist?list=PL5BsRl9zFaeQv9fBqIUcj3CTyI0bh8Pkk" target="_blank" rel="noopener noreferrer">Barbie Doll Adventures</a> needed a motion capture solution that could deliver accurate, character-driven performances efficiently.SolutionXsens inertial motion capture technology gave performers the freedom to suit up quickly, capture data in minutes, and see results live on character rigs. Directors and clients could review shots instantly and make adjustments without impacting the production schedule.Key takeaways<ul><li>Real-time previs: Instant on-screen feedback turned decisions around in hours.</li><li>Performance fidelity: Subtle nuances, from character eyelines to beveled feet, translated cleanly to each character.</li><li>Dance-ready workflow: Durable suits and quick setup enabled complex, syncopated choreography across music video segments.</li></ul>Streamlined productionThe Barbie Doll Adventures team worked to a unique production workflow: asset approvals took time, but once cleared, the motion capture crew could complete an entire episode in under a week. <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens</a> made that pace possible, offering the flexibility to move from calibration to capture in minutes. With no need for cameras or stages, performers could get straight into recording while directors and clients refined performances together in real-time.This workflow proved especially powerful during the pandemic, when everything had to be completed remotely. Over Zoom, producers and animators could watch live feeds of characters performing in the team’s proprietary software, suggesting tweaks on the spot. “We could implement any feedback given from clients like, ‘Let’s have Barbie react in this sequence and break away from the choreography for a beat,' and process the change instantly,” recalls Briana Marin, former professional ballerina (Dance Theatre of Harlem), turned Motion Capture Director and Performer. “What would normally require weeks of storyboarding, revisions, and resources from clients became an agile process completed in a single session. It was an efficiency that kept the show on schedule despite our small team.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1773036218647-Barbie+Puppy+Party+Hero+1.png" style="width:100%px" class="fr-fic fr-dib" /><a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Motion capture</a> performances shaping Barbie’s expressive characters.Defining characters through movementCharacter authenticity was central to Barbie Doll Adventures. The show’s two leads, Malibu and Brooklyn, had to feel distinct not only in appearance but in body language and personality. Xsens’ fidelity enabled performers to craft those nuances through posture, energy, and subtle gestures. Malibu’s optimistic, California-rooted warmth came through in an expressive upper body and energetic movements, while Brooklyn’s grounded confidence was reflected in more deliberate, centered performances.“The accuracy of the eyeline via the head sensor was incredible,” says Briana. “We spent hours refining looks and gestures because those tiny details are what make a character feel alive. Even small adjustments, such as testing new hairstyles or costumes, could be tested live with clients watching. This ability to preview and refine instantly gave our animators reliable data and my performers the confidence that their artistic choices carried through to the final render.”Once a character’s attributes were approved by a client and imported into the proprietary software, performers could see their movements translated into a 3D avatar. This proved empowering for those new to motion capture, enabling them to assess the results of their choreography in real time. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1773036250670-Barbie+Doll+Adventures+BTS.png" style="width:100%px" class="fr-fic fr-dib" />Briana Marin &amp; Eileen Harman (Choreographers) wearing the <a href="https://www.xsens.com/motion-capture/xsens-link-specifications" target="_blank" rel="noopener noreferrer">Xsens Link</a> motion capture for Barbie Doll Adventures.Inclusive storytellingBarbie Doll Adventures placed inclusivity at the heart of its storytelling, introducing new characters including a blind Barbie, a neurodivergent Barbie, and others that reflected its diverse audience. Bringing these characters to life required motion that was lifelike as well as respectful – details like the correct angle of a mobility cane had to be captured with care.“Xsens always delivered,” Briana reflects. “It was durable, responsive, and accurate enough to carry the weight of inclusivity and choreography at the same time. The detail in each movement was truly unbelievable throughout the entire process, too. People recognised the character I was playing just by the way my arm moved.”By combining inclusivity with technical precision, Barbie Doll Adventures showed how motion capture can go beyond efficiency to elevate storytelling itself. With Xsens at the core of production, the team captured performances that were not only accurate but also full of personality, ensuring every viewer could see themselves reflected on screen. Check out Malibu and Brooklyn in action dancing to “Puppy Party,” directed by Briana Marin with choreography and performance by Eileen Harman. Captured with Xsens motion capture technology. <iframe width="640" height="360" src="https://www.youtube.com/embed/RFxR6EaZ6hk?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable"></iframe>Briana’s next project continues into the Mattel doll franchise directing Monster High's  animated version of the iconic ‘Fright Song.’ This new adaptation is centered around global girl group KATSEYE, with choreography and motion capture performance by Eileen Harman. You can watch the official animated music video of the 'Fright Song' <a href="https://youtu.be/HLih_hMPoCI?si=uN7Bxtwm5Oj6WWLf" target="_blank" rel="noopener noreferrer">here</a>.

Dance and movement for Barbie Doll Adventures

Motio Studio is a Malaysia-based, storytelling-driven creative studio working across film, television, documentaries, and brand content. Known for emotionally resonant narratives and visually compelling work, the studio continuously looks for ways to increase realism while keeping production workflows efficient.As projects grew in scale and delivery timelines tightened, Motio Studio needed a more flexible approach to capturing natural human movement. Traditional animation workflows and complex optical motion capture setups added time and technical overhead, limiting creative iteration.A local partnership enabling better performanceTo address these challenges, <a href="https://www.motio.studio/" target="_blank" rel="noopener noreferrer">Motio Studio</a> worked together with <a href="https://www.3particle.com/" target="_blank" rel="noopener noreferrer">3Particle</a>, Xsens’ partner in South East Asia. Through this partnership, Motio Studio integrated Xsens inertial motion capture into their production pipeline, allowing motion capture to become a practical, repeatable part of everyday production.3Particle supported the setup and integration process, ensuring Motio Studio could move quickly from initial testing to live production. The result was a workflow that prioritised performance, speed, and creative freedom without the constraints of camera-based systems.Capturing authentic human motionWith <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens</a>, Motio Studio captures smooth body language, natural timing, and realistic weight shifts directly from performers. The markerless and portable nature of the system allows motion to be recorded in different environments, with minimal setup and fast iteration.Instead of animating characters from scratch or relying heavily on reference footage, the team now starts with authentic human motion. This approach significantly improves realism while reducing the amount of cleanup and post-production required, saving weeks of animation work across projects.Improving collaboration across teamsMotion capture has also changed how Motio Studio collaborates internally. Directors, animators, performers, and technical artists are involved earlier in the process, working together around captured performance rather than interpreting it later in animation.This shared creative process leads to faster decision-making and stronger performances from the start, aligning creative intent across departments and reducing rework later in production.A scalable solution for growing productionsBy working with 3Particle and adopting Xsens motion capture, Motio Studio has transformed motion capture from a specialised technical step into a core creative tool. The studio now benefits from shorter production timelines, higher-quality character motion, and a workflow that scales as project demands grow.The partnership between 3Particle and Motio Studio demonstrates how local expertise combined with reliable motion capture technology enables studios in Southeast Asia to deliver high-quality results while maintaining creative flexibility.About 3Particle3Particle is Xsens’ partner in South East Asia, supporting studios, production teams, educational institutions, and the humanoid robotics market with motion capture solutions across the region. With a strong focus on local expertise, 3Particle helps customers integrate Xsens technology into real-world production environments, supporting practical adoption within active workflows.By combining hands-on technical support with a deep understanding of regional production needs, 3Particle enables studios like Motio Studio to adopt motion capture efficiently and scale their workflows with confidence.

How 3Particle supports motion capture workflows for Motio Studio in South East Asia

How a lean indie studio uses inertial motion capture to move faster, iterate more, and deliver cinematic realism.For many indie studios, character animation becomes a compromise between quality, time, and budget. <a href="https://www.emptyvessel.io/" target="_blank" rel="noopener noreferrer">Empty Vessel</a> set out to avoid that compromise.Founded by experienced AAA developers and operating as a small, agile team, Empty Vessel is building DEFECT, a cyberpunk squad-based immersive objective shooter where tension, realism, and cinematic presentation play a central role. From the earliest stages of development, the team knew that believable human motion would be essential to making the experience work.To achieve that level of quality without the overhead of traditional motion capture pipelines, Empty Vessel built its animation workflow around <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens inertial motion capture</a>. Empty Vessel &amp; DEFECTEmpty Vessel is a studio formed by developers with backgrounds at studios such as Naughty Dog, id Software, and BioWare. Team members have previously worked on major franchises including Uncharted, The Last of Us, Doom, and Call of Duty.Today, the studio operates with a lean team of around 17 developers. The goal is not to replicate the scale of AAA production, but to deliver experiences that feel just as polished, while remaining flexible and efficient.That philosophy is reflected in DEFECT.Set in a dystopian cyberpunk future, DEFECT is a squad-based immersive objective shooter where four teams compete in the same match, each pursuing different objectives. Players can take on the role of authoritarian enforcement units or powerful gang factions, navigating dense environments filled with both AI-controlled enemies and other players.The gameplay emphasizes tactical tension. Movement is deliberate, communication matters, and every corner carries uncertainty. Even in competitive multiplayer modes, PvP encounters are layered with PvE elements, forcing players to constantly assess risk and adapt.Immersion is a core design pillar. Rather than relying on a traditional HUD, DEFECT keeps interface elements out of the way wherever possible. Menus exist directly in the world, presented as an in-game PDA that the character physically interacts with. Objectives unfold through voice-over and environmental cues, supporting a cinematic experience that emerges naturally from gameplay rather than scripted cutscenes.<iframe width="640" height="360" src="https://www.youtube.com/embed/5xrVTBvS7o0?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable"></iframe>Gameplay reveal from <a href="https://store.steampowered.com/app/2470010/DEFECT/" target="_blank" rel="noopener noreferrer">DEFECT</a> by indie studio Empty Vessel.Animation challenges at indie scaleFor a small studio like Empty Vessel, animation quality quickly becomes a pressure point. Realistic human motion is time-consuming to create, and traditional motion capture pipelines often introduce long delays between capture and usable data.Rico Flores, Animation Director at Empty Vessel, has spent his career working with both high-end optical motion capture and more budget-conscious setups. While optical capture delivers strong results, it often comes with turnaround times that do not fit a lean production model.“From shoot day to actually getting usable data back, it can take weeks or even months,” Flores explains. “That makes iteration slow, especially when you’re still figuring out how something should feel in the game.”For DEFECT, where moment-to-moment gameplay, pacing, and tension are constantly evolving, that lack of speed was a problem. The team needed a way to prototype quickly, test ideas immediately, and refine performances without burning time or budget.Why Empty Vessel chose XsensFlores had already introduced Xsens at a previous studio and saw firsthand how it changed the way animation teams could work. When Empty Vessel was formed, the decision was clear.“Once I got a taste of Xsens and how much I could produce with it, I knew that for my next company we were going to go Xsens right out of the gate,” he says.Xsens allowed Empty Vessel to bring motion capture fully in-house. Instead of scheduling external shoots and waiting for results, the team could capture motion whenever it was needed and see results almost immediately.“I can shoot something today, see it in a few hours, and have it on my character the same day,” Flores says. “If something is a priority, I can literally go to my garage, capture it, and get it into the game.”That speed fundamentally changed expectations around animation production.Building DEFECT’s animation pipelineXsens sits at the core of DEFECT’s animation workflow. The system is used to capture a wide range of character motion, from traversal and combat movement to environmental interactions and everyday actions.Much of this work is done internally by Flores himself, allowing the team to iterate rapidly without relying on external resources.“If we want to test something, I’ll capture it quickly, throw it into the game without heavy cleanup, and see how it feels,” he explains. “If it works, I polish it. If it doesn’t, we move on. That might only be a few hours of work.”This approach allows Empty Vessel to experiment freely. Animations are no longer a bottleneck that slows down design decisions. Instead, they become part of the creative process, supporting rapid prototyping and refinement.For more specialized performances, such as complex stunts or highly trained combat movement, the team occasionally supplements its pipeline with optical motion capture.“A lot more animation than people think is just general motion,” Flores says. “Walking, interacting with objects, pulling a weapon, using a lever. All of that can be done quickly with Xsens, without needing a full studio shoot.”Clean data and faster polishBeyond speed, data quality was a key factor in adopting Xsens. According to Flores, one of the most time-consuming aspects of animation cleanup is removing jitter and noise from motion data.“That was always one of the toughest parts,” he says. “With Xsens, the data is clean. I rarely have to deal with jitter, so I can focus on polishing the performance instead of fixing curves.”The result is a workflow where captured motion is usable almost immediately, with significantly less cleanup required before it can be refined and finalized.Punching above indie weightFor Empty Vessel, investing in motion capture was not just about efficiency. It was a strategic decision to stand out in a crowded indie market.Many smaller studios rely heavily on marketplace animation assets, which can limit originality and visual identity. By building a real motion capture pipeline, Empty Vessel was able to push DEFECT’s animation quality beyond typical indie expectations.“When you look at DEFECT, you can actually compare it to AAA projects,” Flores says. “We’ve been able to punch above our weight by using an AAA-style mocap pipeline at a much lower cost.”Animation plays a major role in that perception. Realistic motion supports immersion, reinforces tension, and helps DEFECT feel grounded and believable, even in its cyberpunk setting.Empowering small teamsXsens has also had a direct impact on team structure. With the right tools in place, a single animator can produce work that would traditionally require a much larger department.“It’s empowered me to do the work that, at other studios, would need more people,” Flores explains. “Whatever the game needs, I can make it.”While motion capture is an investment, Flores sees it as a long-term cost saver.“If you have someone who understands the technology, it pays for itself over time,” he says. “Especially for an indie studio.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1773037618535-Screenshot+2026-01-29+at+4.15.51+PM.png" style="width:100%px" class="fr-fic fr-dib" /><a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens motion capture</a> applied directly to DEFECT characters.Looking aheadAs DEFECT continues development, Xsens remains a central part of Empty Vessel’s production pipeline. The flexibility to capture motion quickly, iterate freely, and maintain high quality allows the team to keep refining the experience without slowing momentum.For indie studios aiming to deliver realistic character motion and cinematic presence without AAA overhead, Empty Vessel’s approach shows what is possible with the right tools and mindset.

With Xsens MVN Animate

How indie studio Empty Vessel built high-quality character animation

How Xsens is shaping the future of animation, visual effects, and storytelling for students.At Georgia State University’s Creative Media Industries Institute, students are learning how to bring digital characters to life through motion. Led by Professor of Practice James Martin, GSU has integrated Xsens inertial motion capture technology into its curriculum to prepare students for the evolving world of real-time animation, VFX, and virtual production.ChallengeGSU needed to replicate the workflows used in high-end productions and make them accessible to students. Solution<a href="https://www.xsens.com/motion-capture/xsens-mvn-link" target="_blank" rel="noopener noreferrer">Xsens Link</a> suits were flexible, comfortable, and able to capture high-quality data without the need for a dedicated studio space. The inertial system enables students to perform anywhere – on campus, outdoors, or in mobile setups – removing the limitations of traditional optical mocap systems.Key takeaways<ul><li>Fast, flexible learning: Xsens suits require minimal setup and calibration, making it easy for students to jump straight into performance capture.</li><li>Inclusive and adaptable: The system accommodates different body types and performance styles, supporting diverse creative projects across disciplines.</li><li>Real-world workflows: Students gain exposure to networking, data processing, and mobile mocap setups, mirroring the workflows used in major production studios.</li><li>Collaborative storytelling: The technology empowers cross-departmental collaboration between animators, filmmakers, and game designers, all within a shared creative pipeline.</li></ul>Building skills for the futureBeyond technical expertise, GSU’s program emphasizes critical thinking and storytelling. Students learn how movement informs character development and how performance data connects to narrative intent.“Once they’re suited up, students see their own performances mirrored in real time,” says James. “That instant feedback changes how they understand motion. It’s both a technical lesson and an artistic revelation.”As GSU integrates AI and advanced rendering workflows into its curriculum, <a href="https://www.xsens.com/motion-capture/xsens-mvn-animate" target="_blank" rel="noopener noreferrer">Xsens technology</a> continues to play a key role. Motion data is being combined with AI tools like ControlNet to explore new frontiers in animation and visual storytelling.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770812123511-GSU+Mocap+Low+Res+2.jpg" style="width:100%px" class="fr-fic fr-dib" />Motion capture set at the studio of GSUA platform for opportunityFor many students, motion capture serves as a gateway to industry careers. Graduates have gone on to roles in animation, technical direction, and performance capture for games and film. James is also the founder of Actor Capture – a specialist mocap studio – and through this relationship, students gain direct exposure to professional projects and the confidence to operate independently.“Our mission is to make motion capture accessible, collaborative, and creatively liberating,” says James. “<a href="https://www.xsens.com/entertainment/education-program-for-animation" target="_blank" rel="noopener noreferrer">With Xsens</a>, our students are learning, and they’re producing work that meets professional standards. That experience gives them an incredible advantage when they step into the industry.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770812236416-GSU+Mocap+Low+Res+1.jpg" style="width:100%px" class="fr-fic fr-dib" />GSU mocap coordinator putting students in the Xsens Link suitGSU’s future plansGeorgia State University plans to expand its Xsens footprint across more courses in fine arts, animation, and media production, ensuring that every student has access to cutting-edge motion capture tools.By uniting technology, artistry, and education, CMII is creating a generation of storytellers ready to push the boundaries of what’s possible in digital performance.

With Xsens Academic License

Empowering the next generation of motion capture artists at Georgia State University

Ti5 Robotics uses Xsens inertial motion capture to speed humanoid robot motion modeling by 30% and boost complex action success by 40%+, enabling industrial-grade precision, including ±2 mm placement in narrow aisles. Challenge: Ti5 needed a faster path to robust humanoid robot motion development, avoiding long cycles of manual modeling and tuning, while maintaining performance that holds up in real industrial environments.Solution: Ti5 integrated Xsens inertial motion capture into a closed-loop R&amp;D workflow, connecting motion data capture to motion mapping, control development, testing, and optimization.Key outcomes:<ul><li>~30% reduction in the modeling cycle for core robotic motions</li><li>40%+ higher success rates for complex actions such as precise grasping and gait switching</li><li>Material placement precision within ±2 mm in narrow workshop aisles</li></ul>Ti5 Robotics is a leading Chinese robotics company developing high-precision humanoid robot hardware. Its flagship “T” series includes industrial collaborative models and commercial service robots. The focus is simple: flexible motion, real-world adaptability, and precise task execution.These robots are built for real environments. Think material handling and assembly in smart manufacturing, customer-facing roles like retail guidance and venue reception, and R&amp;D platforms for universities and research labs.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1772622247751-ABUIABACGAAg5_uVyQYo6OCY1gUwuAg4-AU.jpg" style="width:100%px" class="fr-fic fr-dib" />Why motion captureTi5 chose motion capture to start from real human movement. It provides high-quality, multidimensional motion trajectories, including the small adjustments skilled workers make without thinking.With motion capture in the loop, Ti5 can build complex motions faster, reduce modeling errors, and iterate using data feedback. This helps the robot move naturally while still meeting industrial-grade precision targets.Why XsensTi5 learned about Xsens through peer recommendations and technical research, then selected Xsens as the motion capture foundation for humanoid robot development.Their decision was driven by trust in high-quality, precise, reliable motion data and stability in demanding environments. Ti5 highlights " Xsens' low integration complexity enables rapid embedding into our robotics development workflow without complex adaptation or debugging.”How Ti5 uses Xsens in their humanoid robot workflowXsens helps Ti5 connect motion capture to robot control development in a closed-loop process, so motion data is not only captured, but directly improves robot behavior. Here is how their workflow functions:Data acquisition → Data cleaning and fusion via Xsens algorithms → Import into Ti5's robot motion control platform → Motion mapping and algorithm training → Prototype testing and optimization, forming a closed-loop R&amp;D process. The results Ti5 reports with Xsens Ti5 points to measurable impact in both development speed and robot performance: “We reduced the modeling cycle for core robotic motions by approximately 30%, significantly lowering R&amp;D investment.”  A shorter modeling cycle means the team can run more iterations, stabilize behaviors faster, and expand the motion library across tasks sooner.Ti5 also reports a 40% or greater increase in success rates for complex actions such as precise grasping and gait switching. These motions are sensitive; small timing or coordination errors often turn into failures.Finally, Ti5 highlights faster robot response to environmental changes, supported by low-latency motion data synchronization. This helps the robot adjust more confidently when conditions shift in real facilities.In an industrial material handling trial, Ti5 used Xsens to capture skilled workers performing load-bearing walking and precise placement. After implementation, Ti5 reports obstacle avoidance accuracy and material placement precision within ±2 mm in narrow workshop aisles, supporting precision manufacturing requirements where small errors can result in rework and downtime. What’s nextIn the next 1 to 2 years, Ti5 plans to scale deliveries of industrial-grade humanoids and expand into 10+ commercial service scenarios. They expect richer motion data to help robots learn more complex movements as deployments grow.Over the next 3 to 5 years, Ti5 aims to build a universal humanoid platform for cross-industry use. As multi-sensor fusion and motion capture advance, they expect stronger full-scenario adaptability across indoor and outdoor tasks.ks.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1772622284991-ABUIABACGAAgjr_dtAYo0M3WZDCADzi4CA.jpg" style="width:100%px" class="fr-fic fr-dib" />TakeawayWhen you are building humanoid robots for the real world, motion is not just a feature, it is the foundation. Ti5 Robotics uses Xsens motion capture to turn skilled human movement into robot-ready motion intelligence, helping shorten development cycles, improve success rates on complex actions, and reach industrial-grade precision where it counts.FAQWhy use motion capture for humanoid robot training?Motion capture provides high-quality, multidimensional motion trajectories based on how skilled workers actually move. That data helps robotics teams reproduce complex motion logic faster, reduce trial-and-error in manual modeling, and iterate quickly using real feedback.What results can motion capture improve in industrial humanoids?Motion capture can improve development speed, motion realism, and task success on complex behaviors that require coordinated joint timing, balance, and transitions. In industrial settings, this can translate into more consistent execution, higher success rates on complex actions, and better performance in constrained environments.How does Xsens integrate into robot control workflows?Ti5 integrates Xsens by capturing motion data on reference human models, processing the data through cleaning and fusion, and importing it into their motion control platform for motion mapping and algorithm training. The workflow closes the loop through prototype testing and optimization, with real-time synchronization to the robot control system and millisecond-level latency control.

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