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>

With Xsens MVN Analyze

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

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

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

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

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.

with Xsens

Ti5 Robotics: 30% faster modeling, 40%+ higher motion success

Kickboxing rehab is becoming measurable as Saxion University of Applied Sciences combines Xsens motion capture with pressure sensor data to quantify recovery and support better return-to-training decisions.Challenge:Kickboxing rehab is difficult to track with traditional, manual methods, and common tools do not capture punch and kick performance in a sport-specific way.Solution:Using the Xsens Link suit and pressure sensors on pads, Saxion records full-body movement and strike output during structured sessions to generate objective recovery metrics like left-right symmetry.Key takeaways:<ul><li>Built for real training environments: Inertial motion capture requires no studio, making consistent weekly measurements practical.</li><li>Movement plus output: Xsens provides full-body context while pressure sensors quantify strike impact, connecting technique to results.</li><li>Clear progress signals: Metrics like symmetry and repeatable best-effort punch analysis help physiotherapists track improvement over time and guide return-to-sport decisions.</li></ul>Kickboxing is an unsurprisingly dangerous sport. While exciting to watch, throwing uppercuts, jabs, and roundhouse kicks can easily lead to injuries for athletes. To better understand and improve rehabilitation in this demanding field, researchers at <a href="https://www.saxion.nl/" target="_blank" rel="noopener noreferrer">Saxion University of Applied Sciences</a> are exploring new methods of monitoring recovery.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770814514683-Saxion+UFC+Figther+2.jpg" style="width:100%px" class="fr-fic fr-dib" />Closing the gap in kickboxing rehab research“There isn’t much research around kickboxing rehab, especially concerning the use of technology for monitoring rehabilitation,” says Katrien Fischer, researcher and human movement scientist. “Traditional analysis methods are quite manual, making them difficult to quantify and analyze, as these challenges aren’t sport-specific.”Athletes are typically assessed with ground reaction force plates, which are highly effective in sports like running, football, or long jump. However, these tools fall short when applied to combat sports, where punches and kicks are crucial. This gap highlights the need for more specialized approaches tailored to the unique demands of kickboxing.“It’s also important to consider the culture of rehab in boxing and kickboxing,” adds researcher and physiotherapist Remco Kuipers. “Often, not much is done. Fighters tend to push through pain and focus on getting ready for their next match.” This combination of minimal rehabilitation and limited technology has historically made it difficult to measure recovery in combat sports – something the Saxion team aims to change.Full-body kinematics for punches and kicks with inertial motion captureTo tackle this challenge, the researchers turned to Xsens motion capture technology. “We knew Xsens was the right choice because we’ve worked with the system in the past,” explains Katrien. “We opted for the Link suit because of its low latency and ability to pick up on every nuance. Now, we’re using it every week.”The Xsens Link suit is a full-body system with inbuilt sensors that track joint rotation, angles, and velocity. Unlike camera-based setups, it requires no dedicated studio space, making it easy to use anywhere. For athletes with busy training schedules, this convenience makes rehab sessions more accessible and less time-consuming.Inertial motion capture also allows rehabilitation to take place in flexible locations, without the need for specialized labs. Researchers and physiotherapists can bring the technology directly to the athlete, enabling efficient and high-quality analysis on the spot.“We’ve developed a detailed, structured motion capture process to keep data collection consistent,” says Remco. “It involves a warm-up of shadowboxing and pads with a professional trainer. Then we measured eight sessions of kickboxing with a one-minute break between each one. We asked the subject to hit with maximum voluntary contraction, then take the five strongest jabs, crosses, hooks, and uppercuts for analysis.”From subjective feedback to objective rehab decision-makingBy combining motion capture data with pressure sensor measurements, researchers can generate quantifiable insights into performance. One approach they are exploring is the limb symmetry index (LSI), which compares the performance of one arm or punch against the other. Using pressure sensors embedded on pads, this method provides a precise way to measure strength and coordination in combat-specific movements.This kind of objective data has the potential to transform rehabilitation in combat sports. Instead of relying primarily on subjective feelings, physiotherapists could base recovery programs on measurable progress, leading to better outcomes for athletes.“Using Xsens for this project will bring new findings to both us at Saxion and the physiotherapy sector as a whole,” concludes Remco. “We look forward to gathering data that shows improvements in speed, force output, grip strength, and endurance – all essential elements in combat sports performance.”

From pain to progress: Bringing data to kickboxing rehabilitation

TenCate Grass is pushing the boundaries of what an artificial pitch can be, using Xsens motion capture to turn every step, cut, and sprint into actionable insight. By grounding their turf innovation in real athlete data, TenCate is creating sustainable next-generation surfaces that feel like natural grass.Challenge:TenCate needs to create a new, sustainable way to manufacture artificial turf – and it needs to perform just as well as the real thing.Solution:Using Xsens, the TenCate research team can test athletes on different surfaces, validating the new turf material.Key takeaways:<ul><li>From lab to pitch: Tencate tested artificial turf in various locations and conditions.</li><li>Combining camera and mocap: Recording athletes with cameras allows for analysis of one part of the body. Xsens supports this with the full context, demonstrating how each surface affects performance.</li><li>Visual indicator of performance: Showing motion capture data from two surfaces, side by side, helps researchers determine which material to prioritize.</li></ul><a href="https://www.tencategrass.com/" target="_blank" rel="noopener noreferrer">TenCate Grass </a>is the world’s leading producer of artificial turf, supplying surfaces for professional sport, community clubs, and municipalities worldwide. Beyond manufacturing, the company invests heavily in R&amp;D at its Center for Turf Innovation in the Netherlands, where its mission is to create turf that feels and performs as close to natural grass as possible.With over 3000 square meters indoor lab – plus access to full-size natural grass and artificial pitches – TenCate works closely with professional athletes and clubs such as PSV Eindhoven to define what makes the perfect grass for each sport, team, and environment. But simply observing players wasn’t enough. To truly understand how surfaces influence performance, TenCate turned to Movella’s Xsens motion capture technology.“We wanted a system that could tell us exactly how athletes move on different surfaces,” says Tom Wills, Manager of the Center for Turf Innovation at TenCate Grass. “Xsens gives us biomechanical data we can’t capture with cameras alone – things like stride length, joint angles, and acceleration patterns.”Sustainable alternativesTraditionally, artificial turf relies on recycled rubber tyre crumb as infill. However, with the EU’s upcoming 2031 ban on microplastics, that material is being phased out. Which, for TenCate, is something of an opportunity.The R&amp;D team is now testing alternatives – including wood chips, cork, and olive stones – as well as developing non-infill turf systems. And to validate these new designs, biomechanics is essential. By capturing data directly from athletes on the pitch, TenCate can compare movements on new prototypes versus natural grass.“People adapt their movement patterns depending on the surface,” explains Tom. “With Xsens, we’ve seen that our non-infill systems are beginning to replicate natural grass performance, which is exactly where we want to be.”Testing in real environmentsUnlike camera-based systems that are limited to the lab or small test zones, Xsens’ portable IMU-based system allows TenCate to run studies on real fields, under real playing conditions.At their innovation center and at partner sites such as PSV Eindhoven’s training ground, TenCate researchers observe athletes performing drills, from sprint starts to sharp 180° turns. The Xsens system records movement seamlessly across multiple pitches, with only quick recalibration needed between surfaces. Sessions typically last up to two hours, limited not by the equipment but by player fatigue. Data is then cross-referenced with high-speed video for detailed surface interaction insights.“The combination of cameras and Xsens gives us the full picture,” says Tom. “We can zoom in on foot-to-surface contact with cameras, and then use Xsens to understand whole-body motion leading to that movement. It’s a level of insight we simply couldn’t get otherwise.”Beyond the raw data, Xsens also provides powerful visualization tools. Coaches, physiotherapists, and decision-makers can view 3D avatars that compare movement patterns across different surfaces – making complex biomechanics easy to understand.“Not everyone can interpret a graph of hip flexion angles,” Tom laughs. “But when you show them two avatars side by side – one running on natural grass, one on an alternative turf – it clicks. People understand. That visual impact is hugely valuable.”Long-term innovationTenCate has been using Xsens since 2021, and the technology has become central to its product development cycle. From early-stage lab tests to large-scale field trials, motion capture data ensures every innovation is backed by hard evidence.For athletes, the system is comfortable and, crucially, not an obstruction once play begins. For researchers, it delivers reliable, repeatable data. And for the wider sports industry, it means safer, higher-performing, and more sustainable pitches.“Xsens has given us the ability to move beyond opinion and perception, and into measurable, repeatable performance data,” concludes Tom. “That’s critical as we redefine what artificial turf can be.”

Designing the next generation of playing surfaces

ChallengeAs a solo creator, Edward (<a href="https://www.youtube.com/@GTshortStories/featured" target="_blank" rel="noopener noreferrer">GTshortStories</a>) oversaw every stage of production, balancing creative ambition with the restricted time, budget, and resources.SolutionEdward chose to produce all animation using inertial motion capture, enablingf him to play every character without multiple cameras or a rental stage. Key takeaways<ul><li>Fuelling filmmaking: Indie filmmakers can achieve high-quality results by embracing accessible production methods to overcome budget and manpower constraints.</li><li>Efficiency and creative freedom: Streamlined production workflows reduce manual tasks, enabling independent creators to focus more on storytelling and world-building rather than technical bottlenecks.</li><li>Democratizing production value: <a href="https://www.xsens.com/entertainment/motion-capture-for-indies" target="_blank" rel="noopener noreferrer">The Xsens Indie Program</a> means independent filmmakers have more affordable access to <a href="https://www.xsens.com/en/entertainment/motion-capture" target="_blank" rel="noopener noreferrer">Xsens motion capture tools</a>. They can produce work that rivals studio-level projects, narrowing the gap between passion-driven independents and large-scale productions.</li></ul>Believing is Edward Green’s work-in-progress film. It follows an engineering mastermind father and a bullied son, whose biggest dream is to become a superhero. To create a rich world around the protagonists, Edward needed to stretch his filmmaking skills to their fullest potential. Being a solo filmmaker “There’s no team. It’s just me,” says Edward. “My wife helps behind the scenes sometimes, but ultimately, you have one person operating the entire thing. I wrote the script, and it’s financed by me. So I need to use realistic and self-sufficient production methods from concept to completion.”From the beginning, one clear challenge stood in the way: animation. Keyframing and rotoscoping are highly time-consuming processes, especially when going it alone. Each character would be painstakingly animated, taking Edward a significant amount of time and effort to complete. So he turned to a method that enabled him to record data while acting out the parts: motion capture.“As an indie creator, there are a lot of hats you have to wear,” he continues. “Motion capture is one of those hats. It would enable me to become every character, including extras, and record it entirely by myself. I needed to ensure it was as efficient as possible, which is why I opted for Xsens.”Ease of useInertial motion capture relies only on sensors within the suits and post-processing software. This empowers independent filmmakers like Edward to capture performance data virtually anywhere, without the constraints of a dedicated mocap stage or multi-camera setup.“I needed a plug-and-play solution,” says Edward. “It was the only way I could create something of such scale. Using the Awinda suit and the Xsens Animate software meant that I could get to work straight away. I could also rely on the system to deliver high-quality data, making my job in post much simpler.”Working solo and having restricted timelines, the motion capture data had to translate into production-ready animations in as few steps as possible. Xsens’ inertial sensors track joint rotation, acceleration, and velocity with pinpoint precision, ensuring minimal cleanup when in the editing stage. Competing on a Hollywood levelThe resulting animation is smooth and natural, giving Believing a cinematic finish that stands alongside studio-level productions. This same technology is now available to indies pursuing similar results. “Using Xsens for animation has enabled me to turn my dreams into reality,” Edward concludes. “Believing will be able to compete with some big names. That’s in part thanks to the writing, talented voice actors, and post-production, but it’s also down to the sheer quality of animation.”The Xsens Indie Program offers inertial motion capture technology to those creating on a smaller budget. By sharing project work, creators are eligible for significant discounts on the suit and software, enabling them to create at a higher level than before.

Writer-director Edward Green set out to create his animated feature, Believing, entirely independently. With the right tools, the project is progressing from concept to screen at incredible speed.

Xsens in indie film: Edward Greens Believing

When Auburn University’s Iván Nail-Ulloa set out to measure the strain of lifting 400-pound manhole covers, motion capture data revealed the hidden risks behind the task. His findings led to the development of an assistive device that makes this demanding job safer and more ergonomic.ChallengeAuburn University’s Biomechanical Engineering (AUBE) Lab postdoctoral fellow, Iván Nail-Ulloa, needed to accurately measure employees’ physical wellbeing. It was important for the motion capture solution to work in any environment, including locations with magnetic interference.SolutionIvan used Xsens to identify potential risk areas and develop an assistive machine that automatically lifts manhole covers, with minimal human assistance required.Key takeaways<ul><li>Identifying the problem areas: Ivan and the team analysed lumbar spine loading, one of the most common injury areas during physical work</li><li>High compressive force during manhole cover lifting: Ergonomic analysis revealed that workers’ backs are subjected to potentially harmful/injury-inducing forces with each manhole lifted</li><li>Risk applies to multiple workers: Whether one or two people are lifting a cover, the force applied is still similar</li></ul>Ergonomic analysis is increasingly data-driven. Physical wellness at work takes technological evidence and extensive research to quantify. Postdoctoral fellow Iván Nail-Ulloa from Auburn University shares his project on ergonomics, reflects on the product he made to improve employee wellbeing, and shows how inertial motion capture provided the most accurate results.Preparing for ergonomic analysis Funded by EPRI Occupational Safety and Health Program 62, Ivan began his project, “<a href="https://www.sciencedirect.com/science/article/abs/pii/S0169814124000921" target="_blank" rel="noopener noreferrer">Assessing the accuracy of a wireless sensor system for estimating lumbar moments during manual lifting tasks considering the effects of load weight, asymmetry, and height</a>”. It was designed to assess manual labor employees within their work environment and the adverse effects their tasks could have on their bodies, particularly for the lumbar spine. Lower-back pain is a well-known issue in the ergonomics industry, and Ivan wanted a technological method to study the cumulative exposure to physical risk factors. Traditionally, ergonomic solutions were created based on self-reported pain or company injury documents. “Things changed in the ergonomics industry when we could scientifically track data that provided tangible proof to employers of their employees experiencing pain,” explains Iván. “Having this information helps us find the exact issue with their workflow and provide a solution to stop injuries from happening.”The dissertation project began in 2018 when Iván had to choose which technology was best suited for his research. “We decided to compare optical and inertial motion capture using biomechanical modeling,” he says. “Our study found that inertial motion capture data and optical motion capture data varied by 12-14%, showing that the small difference, coupled with flexibility gains, made the inertial method the ideal choice.”  After making this decision, Iván began to research different systems.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770812802229-Ivan+Nail+Ulloa+Auburn+Uni+3.jpg" style="width:100%px" class="fr-fic fr-dib" />Creating a safe working environment for high-risk jobs A particular focus of Iván’s project was to enhance the occupational health and safety of power utility workers in New York. “Employees lift manhole covers that reach 400 pounds,” he mentions. “This is an extremely heavy load, and can be incredibly unsafe for those who have to lift it.” The workers use J-hooks that attach to the manhole covers and then haul them out of the way.To effectively quantify the pressure experienced on the workers’ bodies, the Xsens system was the perfect solution. “Working on ergonomics in a real-world scenario is very fast-paced, and we had to stop traffic in New York to record the worker’s movements,” explains Iván. “Luckily with the ease of setup, we could quickly get the recordings without holding anyone up for too long.”Given the particular setting and circumstances of this application, the research team knew they needed inertial motion capture to capture an accurate ergonomic analysis. Before Xsens, Iván found that machinery and nearby electronics would disrupt the technology’s electromagnetic field, so he had to search for a new option. The Awinda motion capture suit used in this study has magnetic immunity, making it the perfect use case in this context.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770812824750-Ivan+Nail+Ulloa+Auburn+Uni.jpg" style="width:100%px" class="fr-fic fr-dib" />Measuring the impact of manhole cover liftingThe research found that a significant amount of stress was placed on the workers’ bodies during the initial movement of the manhole cover (peaking at 276-739 lbs of compressive force). This applied whether there were one or two people moving the cover at once. While the compressive forces remain below the recommended compression limit, given the number of times the employees could do this task in a day, the cumulative damage was proven to be a very serious topic to address. This is on top of another point of high force revealed to occur during the initial exertion of the mahnhole cover, resulting in significant torso flexion.Gaining this valuable ergonomic research led to Iván and his team designing and building a power hook that automatically lifts manhole covers, eliminating the risk of injury. This technology enabled a reduction in peak compression force of 7-15%, and the improvement in the ergonomics was also noted anecdotally by the workers testing the new device, reporting that it “helps to keep a neutral back".“This solution simply could not be found without objective movement data,” Ivan says. “We needed quantifiable figures to show the contractors that moving these manhole covers posed a significant risk to their workers.” <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770812848481-Ivan+Nail+Ulloa+Auburn+Uni+2.jpg" style="width:100%px" class="fr-fic fr-dib" />Rapid results for occupational health and safetyCreating a safe working environment takes extensive planning and research to effectively quantify the workers’ needs. Ergonomic analysts do just this, but they need to have high-quality, accurate equipment to help them get the required information. Iván’s use of Xsens technology helped him make countless workers’ jobs safer through objective movement data. He needed pinpoint accuracy, and found that through biomechanical analysis and a reliable motion capture system, he could achieve just this.Looking to the future, Iván plans to continue ergonomic research using inertial motion capture. “Xsens is perfectly suited to my needs, and shows just how important accuracy is in ergonomics,” he says. “The next thing we’ll focus on from this project is improving the automatic manhole lifter in terms of speed, which was an idea created as a result of our collected data and workers’ feedback.”

With Motion Capture

How Auburn Researchers Made Manhole Lifting Safer

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

Quantum Movement combines motion capture, camera footage, and software to create an all-in-one tool for physical therapy, performance analysis, and training.Challenge:Biomechanics tools tend to be costly, complex, and limited to elite athletes, leaving most practitioners and athletes reliant on less accurate observational analysis.Solution:Quantum Movement combined Xsens motion capture with camera footage and software to deliver research-grade accuracy, real-time biofeedback, and a portable setup, making advanced biomechanics accessible to all.Key takeaways:<ul><li>Real-time biofeedback: Athletes and patients can instantly correct movements, especially valuable for ACL rehabilitation and injury prevention.</li><li>Simple, portable setup: Only a camera and a small set of sensors are needed: no lab required.</li><li>Democratizing biomechanics: Quantum Movement bridges the gap between elite sports technology and the broader athletic and fitness community.</li></ul>Sport – whether that's football, swimming, mixed martial arts, or anything in between – is one of the most physically demanding occupations. Athletes are injured regularly. Training regimes become more detailed. But preparing plans for each individual is costly and complex. When starting <a href="https://www.quantmove.com/" target="_blank" rel="noopener noreferrer">Quantum Movement</a>, CEO and founder Andy Barr recognized that sports biomechanics and its technology weren’t accessible enough, and only top-class athletes could access them. Everyone else, including sportspeople and those looking to improve their fitness, would rely on outdated methods of physical assessment, such as observational analysis, which lack data-driven insights.The team solved this by combining video with inertial motion capture. This allowed them to capture the smaller details, such as subtle joint rotations, acceleration, and balance, that are impossible to see with the naked eye. The goal was to bring elite insight into a format that could be used by everyday practitioners and athletes alike. Research-grade accuracyIn his work as a physical therapist, Andy had witnessed just how many practitioners used traditional forms of biomechanical analysis. Observational measurements such as range of motion, control, and strength, are now being replaced by technology and quantifiable metrics.“I had my eye on Xsens from the beginning because of its strong reputation in the research sector,” says Andy. “We often see it used in the elite sports industry because of its granular detail. I wanted to bring this research-grade accuracy to Quantum Movement and have its quality become available to more people.”The Quantum Movement system also integrates with witness camera footage, making it ideal for including visual components along with numerical information. A single camera – for example, a GoPro or the new mobile app – can be used alongside five Xsens DOT sensors to analyze almost any testing or training scenario. The Quantum Movement application captures the video footage while Xsens sensors simultaneously record highly detailed motion data, with both streams being synced together for immediate analysis.Generating real-time feedback“Our biofeedback mode allows athletes and sports enthusiasts to track their progress as they are working out,” explains Bart Piwowar, VP of Product at Quantum Movement. “Users select key metrics such as joint angle, body movement, or center of mass, and watch as the graph updates in real time.”Making this possible is Xsens’ wireless inertial sensors. The motion capture system links to a laptop or mobile device and displays its data within the Quantum Movement platform in an easy-to-read graph. Traditionally, biomechanical analysis takes place after data collection. Now, however, real-time feedback allows athletes to adjust their form and movement as they perform. “A key focus for the Quantum Movement team is anterior cruciate ligament (ACL) rehabilitation,” continues Bart. “It’s one of the most common and debilitating injuries in sport.” Effective recovery requires patients to progress based on clear, evidence-based criteria that indicate which activities they’re ready for and vice versa. “Without this structure, patients often either attempt movements too soon (increasing the risk of re-injury) or fail to advance when appropriate,” Bart adds. “Unfortunately, both scenarios occur far too frequently.”Quantum Movement addresses this gap by combining its software and methodology with Xsens DOT technology. Using real-time biofeedback, patients and practitioners can monitor joint angles, assess movement quality, and receive corrective feedback during rehabilitation exercises. This not only provides objective guidance throughout the recovery process but also boosts confidence, improves outcomes, and significantly reduces the likelihood of ACL re-injury.For athletes and researchersThanks to its unique toolset, the team’s technology is designed for quick and easy setup - making it accessible to technical specialists, athletes, and non-experts alike.“This is different from your usual lab-based approach,” continues Andy. “You only need a camera, a set of Xsens sensors, and somewhere to send the data to. That means you can use it in the gym, on the field, or at home, with minimal preparation required.”A new method of biomechanical analysisQuantum Movement is redefining how practitioners, athletes, and rehab professionals approach human movement analysis. By integrating Xsens inertial motion capture technology with intuitive software and camera footage, the team delivers a powerful, portable alternative to outdated, subjective systems. The result is a comprehensive, real-time solution that offers research-grade accuracy, without the complexity or exclusivity of elite-level setups.Whether it’s supporting ACL rehab, refining movement technique, or preventing injury, Quantum Movement empowers users with the data they need, when they need it. Thanks to the reliability and precision of Xsens, Quantum is helping democratize advanced biomechanics, making high-quality motion analysis accessible far beyond the world of professional sport.

By Xsens MVN Analyze

Democratizing rehab and performance technology with Quantum Movement

VFX Supervisor Victor Perez built landscapes and filled them with people for the feature film, Naples to New York. On a short timescale, he found a way to do this efficiently and with high-quality results, winning two accolades at the David di Donatello Awards.ChallengeThe film was set in an imagined version of New York City. Victor worked with this unique brief to create hyperrealistic yet fantastical scenes. SolutionUsing a combination of Xsens and volumetric capture, shots were filled with natural and dynamic crowds in post-production.Key takeaways<ul><li>Realistic human movement: Xsens picks up on small details and body language nuances, ensuring lifelike on-screen animations.</li><li>High-volume motion capture data: Victor worked with a single artist to capture over 300 movement cycles within a day. </li><li>Efficient post-production: Volumetric capture underpinned by Xsens enabled Victor to build dynamic crowds on an independent film budget.</li></ul><a href="https://m.imdb.com/title/tt22490428/" target="_blank" rel="noopener noreferrer">Naples To New York</a> follows two children in post-war Italy as they escape poverty and travel to the USA. Written by Federico Fellini in 1948 and uncovered 60 years later, the story has a specific neorealistic style, which was handled with care when production began. Director Gabriele Salvatores used this style in line with Fellini’s vision, requiring an archival feel and finetuned post-production. For this, Victor Perez stepped in – a VFX Supervisor on major projects such as Pirates of the Caribbean, Batman, and Harry Potter.Building New YorkTo help visualize a fantastical vision of New York, Victor and his team undertook extensive crowd-building, architectural work, and prop integration using a small team of just 167 artists over the course of six months. The post-production team was responsible for 536 shots across the film, providing visuals for traffic, buildings, and people. A significant focus was on the creation of New York itself. “Fellini had never been to New York,” Victor explains. “So it had to look fantastical and somewhat dreamlike. It also helped that I’ve never visited the city.”New York scenes were shot in Trieste, Italy, reflecting Fellini’s not-quite-accurate idea of how the American city looked. “I created a merged landscape by using the architecture of Trieste and overlaying 1940s New York iconography,” says Victor. “But the real challenge was filling the streets with people.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770811045580-Naples+To+New+York+-+People+2.png" style="width:100%px" class="fr-fic fr-dib" />Creating crowdsNew York is a famously busy city, so the team used a mixture of native filming and VFX to bring scenes to life. CG character creation was a strong start, but with just six months to complete the project, Victor searched for something more efficient, eventually opting for volumetric capture.“We used a 36-camera cage to scan over 900 extras,” he says. “Then we animated them using <a href="https://www.xsens.com/motion-capture/xsens-mvn-animate" target="_blank" rel="noopener noreferrer">Xsens inertial motion capture technology</a>.” This dramatically reduced time for the Naples To New York post-production team, capturing scans in one day while being able to animate them at a later date.  <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1770811104992-Naples+To+New+York+-+People.png" style="width:100%px" class="fr-fic fr-dib" />Fast-paced motion capture With the help of associate VFX supervisor Larisa Zhuraleva, Victor used the <a href="https://www.xsens.com/motion-capture/xsens-mvn-link" target="_blank" rel="noopener noreferrer">Xsens motion capture suit</a> to create 300 animation sequences in a single day. These could then be applied directly to the scanned extras, making the crowd appear dynamic and bustling. “Using Xsens is like using a camera,” says Victor. “Once you’ve set it up, you can get as much content as you need.” Inertial motion capture enabled the pair to create different postures, gaits, and gestures with a high level of precision. “We wanted our characters to move fluidly like in real life, so motion capture was the perfect solution,” Victor continues. “We could also evaluate our progress in real-time to see if we were getting the right movements and amend where needed.”After a day of recording themselves, Victor and the team quickly transferred the motion capture data to post-processing software the next morning. From there, they fine-tuned movements where needed and prepared the scans for animation, resulting in a lively and highly realistic reconstruction of New York’s crowds.<iframe width="640" height="360" src="https://www.youtube.com/embed/AR5_imz9i2s?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable"> </iframe>Efficiency and longevity A quarter of Naples To New York’s VFX shots involved Xsens motion capture. And within such a short period of time, the team needed to get crowd-building done efficiently. “Using the Xsens suit was invaluable to the production,” concludes Victor. “It brought a depth of movement that really elevated the film. And now, I have a high-quality library of animations fit to use on projects to come.”

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