This article originally appeared in <a href="https://engineering.wustl.edu/news/2023/Brain-machine-interfaces-for-insects-to-study-principles-of-odor-guided-navigation.html" target="_blank" rel="noopener noreferrer">McKelvey School of Engineering</a> and has been republished with permission.<hr><iframe width="640" height="360" src="https://www.youtube.com/embed/dBNOGbF-e7E?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe>The locust follows a pleasant scent on a treadmill. (Credit: Raman lab)The inviting smell of a freshly baked cookie immediately triggers a motor response to search for the source of that smell. Often the cookie can be easily found.This everyday event that we perform without a thought is an amazing feat that combines our superior ability to smell the cookie and computational prowess to determine the directions to move toward the cookie. Robots that possess similar capabilities are yet to be developed as the basic biological principles that are needed to perform this task are yet to be fully understood. &nbsp;The ability to study neural responses in behaving insects is essential to understanding the robust solutions biological systems have developed for several engineering problems. For example, locusts have survived for at least 8 million years — longer than humans have been on this planet — in nearly all parts of the earth. Their many remarkable capabilities include seeing, hearing and smelling things that humans cannot sense, jumping multiple times their body length, the uncanny ability to fly up to 100 kilometers a day, and switching between solitary and menacing swarms phases as needed for survival. They use these capabilities to find food, avoid predators, propagate their species, and do all things necessary to keep them alive. Researchers in the McKelvey School of Engineering at Washington University in St. Louis have long sought to understand the power of the locusts’ sensing, computing and locomotory capabilities.Barani Raman, professor of biomedical engineering in the McKelvey School of Engineering, is leading a multidisciplinary team to study how the locust brain transforms sensory input into behavior with a four-year, $4.3 million grant from the National Science Foundation’s Integrative Strategies for Understanding Neural and Cognitive Systems (NCS) program. The grant converges years of research in Raman’s lab with that of his longtime WashU collaborators, including Shantanu Chakrabartty, professor of electrical &amp; systems engineering, and Srikanth Singamaneni, professor of mechanical engineering &amp; materials science, as well as Alexandra Rutz, assistant professor of biomedical engineering, and Yehuda Ben-Shahar, professor of biology, also at WashU.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1697685410077-ezgif-5-9129b96817.jpg" style="width: 766px;" class="fr-fic fr-dib">Researchers in the McKelvey School of Engineering have long sought to understand the power of the locusts’ sensing, computing and locomotory capabilities. With a $4.3 million grant from the National Science Foundation, they will converge that research to develop a “cyborg,” or mobile robot or drone, that can mimic the locusts’ behaviors. (Credit: Raman lab)“Insects are an engineering marvel,” Raman said. “They possess diverse sensing modalities and locomotory responses yet contained in such a small package. We want to engineer tools to study the amazing capabilities of these relatively simpler organisms.”The research brings together Washington University’s strengths in neural engineering, integrated circuits, biomaterials, synthetic biology and genetic engineering to understand how the insects use olfactory cues to navigate toward an odor source, which could potentially be used for various applications, such as detecting gas left on in the kitchen or as the proverbial canary in the coal mine to test spaces for hazardous chemicals. In 2024, the team plans to launch the first-of-its-kind Center for Cyborg and Biorobotics Research (CyBoR) to formally conduct the research.&nbsp;The team plans to study the neural response in the locusts’ brains by having the locusts follow a specific odor on a specially built treadmill while walking on a foam ball and while flying in a wind tunnel. By studying their movements and neural activity in the brain in response to these odors, the team can process the information using a custom microchip to develop a “cyborg,” or mobile robot or drone, that can mimic the locusts’ behaviors. They also aim to augment the locusts’ ability to detect certain odors over others.“Nature already has endowed this organism with various capabilities, so why not understand and augment those capabilities using synthetic mechanisms?” asked Chakrabartty, whose expertise is in sensors and integrated circuits. “Ultimately, our goal is to design a completely synthetic system that has similar remarkable capabilities.”While the team has already joined forces to create recording instruments and nanomaterials to manipulate neural and behavioral responses, they will continue to improve on those as they develop the bio-hybrid and mobile robotic systems.&nbsp;“One of the important challenges in these studies is the limited stability of the neural recording and stimulation electrodes and interfaces over a long period,” said Singamaneni, whose expertise is in novel bio- and nanomaterials. “We aim to design and realize novel anti-inflammatory electrodes and biointerfaces that will enable stable long-term neural recording and stimulation.”Previously, <a href="https://engineering.wustl.edu/news/2016/Engineers-to-use-cyborg-insects-as-biorobotic-sensing-machines.html" target="_blank">the research team developed a miniature “backpack”</a> containing sensors that recorded the locusts’ brain activity when exposed to the odors. However, the existing backpack is too heavy for the locusts to wear while flying, so the team will work to reduce its weight.At Washington University, the research is underway in a state-of-the-art CyBoR facility that includes the habitat for the locusts, the treadmill, the wind tunnel, specialized microscopes, and space for visiting researchers as well as for visitors interested in learning about the insects. WashU students also will be included in the research as well as students from the community through various outreach programs.&nbsp;Other co-investigators include Alper Bozkurt, distinguished professor of electrical &amp; computer engineering at North Carolina State University, who will lead efforts on instrumentation for navigation control; Sawyer Fuller, assistant professor of mechanical engineering at the University of Washington, who will lead efforts to build miniaturized robots that incorporate both biological and engineering elements; and Nabil Imam, assistant professor of computational science and engineering at Georgia Tech, who will lead the development of neuromorphic algorithms and hardware in the bio-hybrid and robotic systems.

Barani Raman, professor of biomedical engineering in the McKelvey School of Engineering, is leading a multidisciplinary team to study how the locust brain transforms sensory input into behavior with a four-year, $4.3 million grant from the National Science Foundation’s Integrative Strategies for Understanding Neural and Cognitive Systems (NCS) program. 

Brain-machine interfaces for insects to study principles of odor-guided navigation

As a result of the development of various machines and robots, we have become able to effortlessly handle jobs that humans could not perform with muscle strength and motor skills. Moreover, owing to advances in sensors, AI, and other information processing technologies, we have also become able to use perceptual abilities that exceed the five human senses. In order for humans to freely use the extended abilities realized through such machinery, other technologies that create a closer relationship between machinery and humans are required.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjc5Mjc1MDU1MDkxLW11cmF0YV9ibWk3LTAxLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib">Figure 1: Detecting brain activity to freely manipulate a machine&nbsp;<h2 id="isPasted">Scanning brain activity to create the ultimate HMI</h2>When a human is operating a machine, the Human&ndash;Machine Interface (HMI) becomes the point of contact between both sides. Devices such as the steering wheel and pedals of an automobile, the keyboard and mouse of a PC, and the touch panel of a smartphone are able to operate a machine as an HMI. Recently, voice recognition technologies have progressed to the point where it has become possible to operate a machine such as an AI speaker using natural language as an HMI. Moreover, if you utilize the Virtual Reality (VR) technologies applied in games, etc., you can experience events within the virtual world created by the computer with a sense of immersion and feeling that you are actually there. The relationship between human and machine is steadily becoming closer due to the progress of technology.However, with existing HMIs, a considerable degree of skill is required to communicate motions and operations you are thinking about to the machine. Freely operating a car as if it were part of your body like a racer or bus driver requires training that takes a lot of time. Moreover, when operating a machine through a tool such as a steering wheel, a slight delay inevitably occurs in the operation. To realize the kind of operation that feels as if human and machine have merged, technologies that further reduce the distance between both are needed.So how much will the distance between human and machine be reduced in the future? The development of a technology to unconsciously move machinery like the limbs of your own body, which can be described as the ultimate form of HMI, is being advanced. That technology (Figure 1) is called &quot;BMI&quot; (Brain&ndash;Machine Interface). BMI has already reached the stage of practical implementation in some applications. This article introduces the trends in BMI evolution and the impact of this technology.<h2>Visualizing what someone is thinking through advances in sensing and information processing</h2>The development of sensing technologies to detect brain activity and information processing technologies to interpret (decode) the status of brain activity is becoming increasingly active. Thus, we are becoming able to realize an advanced BMI.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjc5Mjc1MDg0Mjc4LW11cmF0YV9ibWk3LTAyZW4ucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">Figure 2: Realization of BMI through the progress of sensing and information processing technologies&nbsp;Until now, investigating brain activity required the use of large-scale medical equipment to measure brainwave changes and distribution within the head. Brainwaves are minute electrical signals that record from the top of the head, etc. the electrical potential occurring in the neuronal projections that make up the brain. To accurately measure brainwaves, you need to use 12 or more EEG recording devices to precisely measure electrical potential fluctuations of several microvolts.Sensing technologies that accurately read brainwaves in a non-invasive manner without implementing any surgical interventions such as embedding electrodes in the head have advanced rapidly in recent years. Because brainwaves are observed as small voltage fluctuations called &quot;microvolts,&quot; it was difficult to accurately measure them due to the impact of electrical noise generated by the muscles and electromagnetic waves in the surrounding environment. Owing to the development of technologies that remove noise, it has become possible to take highly precise brainwave measurements with miniature sensors.In addition to the method of reading minute electric potential fluctuations, sensor miniaturization and increasing precision is advancing in methods that measure the magnetic fields generated due to brain activity and technologies that shine near-infrared light on the head to detect the states of light scattering and reflection to estimate changes in the volume of blood flow within the brain. Moreover, the use of a technology called fMRI (functional magnetic resonance imaging) equipment*1 to identify active areas of the brain with pinpoint high precision and measure the state of brain activity with greater detail is also advancing. By making effective use of these technologies according to different purposes, we have become able to know the state of brain activity from many angles.*1 fMRI (functional magnetic resonance imaging) is a technology that measures the electromagnetic waves generated by the deoxygenated hemoglobin within the blood flowing in the brain to detect the activity of any location in the brain.Moreover, technologies that interpret (decode) the biometric information that reflects brainwaves and other brain activity have also advanced, and we have become able to visualize cognitive information such as what a person is looking at or listening to. The technologies have developed to the point where today if you collect accurate brain activity information and effectively analyze it, you can even reproduce a fuzzy image on a monitor of the content of a dream that someone is having during sleep or images that a person is seeing with their eyes from brain activity information. Moreover, it is also possible to determine emotions and other mental states or the comprehension of studied material.In recent years, it has become clear how the activity of brain cells and the various parts of the human brain relate to each other while operating by accurately modeling brain function based on deep-learning theory, which has become utilized in various fields as a core technology of artificial intelligence (AI), and the analysis precision has rapidly increased.<h2>Wide range of BMI application fields, from entertainment to welfare and education</h2>Because it has become comparatively easy to measure brain activity, attempts are being made to apply the information obtained through measurement to various applications.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjc5Mjc1MTEyNzI5LW11cmF0YV9ibWk3LTAzLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib">Applying BMI to extend human capabilities&nbsp;For example, headphones that utilize brainwave sensors and are equipped with functions that can determine the degree to which a person is concentrating and in a relaxed state have been practically implemented. Games and other applications in which the character movement and story development change according to a person&#39;s mental state can be realized. When it comes to entertainment content, it is meaningless if the viewer or player becomes bored. However, no matter how interesting the content is, some people may find it boring. If you can provide content that triggers emotions by various means according to the mental state of each individual, then it will become something that will satisfy everyone.In addition, there are also initiatives to utilize BMIs to support the lifestyles of those with disabilities through machines. Equipment that can distinguish between several hundred different types of messages from brainwaves have already been practically implemented, and it is hoped that it can be utilized as a means of communication for those with severe motor impairments that make speech and writing difficult. The arrival of an era in which prosthetic hands and legs can be manipulated like real limbs through the utilization of BMIs may not be far off.Moreover, there are also initiatives underway to detect a person&#39;s brain response to received stimulation and apply that to impactful education and training to increase learning effectiveness. Systems that improve English listening capabilities in a short period of time by analyzing how English conversation audio is being heard and understood within the student&#39;s head and providing feedback are being developed.BMI is an essential technology for minimizing the distance between human and machine as much as possible to merge both together. As the technology develops, it will become possible to freely manipulate massive and micro machines, machines placed in remote or dangerous locations, as well as computers with advanced computing power as if they were your own limbs. BMI will likely become a technology that extends human potential and supports the future.<hr id="isPasted"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjg1MDg2NjcyNTM4LTE2ODUwODY2NzI1MzgucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii">If you have any questions based on this article that you would like to discuss with an expert at Murata, don&#39;t hesitate to reach out. There&#39;s an entire team ready to support you with your question.<a class="button-main-action" href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" rel="noopener noreferrer" target="_blank">GET IN TOUCH</a><hr>

As a result of the development of various machines and robots, we have become able to effortlessly handle jobs that humans could not perform with muscle strength and motor skills. Moreover, owing to advances in sensors, AI, and other information processing technologies, we have also become able to use perceptual abilities that exceed the five human senses.

Using BMI to operate machinery like your own limbs without any manipulation

In this episode, we talk about NeuralTree: a neural interface capable of detecting neural impulses associated with brain disorders and countering them.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/af523f9f-6e33-407d-8aec-98ea14b8fd45?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe><hr><h3 id="isPasted">EPISODE NOTES</h3>(0:46) - <a href="https://www.wevolver.com/article/a-neuro-chip-to-manage-brain-disorders" target="_blank">A Neuro-chip To Manage Brain Disorders</a><hr>As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.To learn more about this show, please visit our <a href="https://www.wevolver.com/profile/the.next.byte" target="_blank">shows page</a>. By following the page, you will get automatic updates by email when a new show is published. Be sure to give us a follow and review on <a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" rel="nofollow" target="_blank">Apple</a>, <a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" rel="nofollow" target="_blank">Spotify</a>, and most of your favorite podcast platforms!

In this episode, we talk about NeuralTree: a neural interface capable of detecting neural impulses associated with brain disorders and countering them.

Podcast: The Future of Neurology: Neural Interfaces Countering Neural Diseases

This article was discussed in our <a data-saferedirecturl="https://www.google.com/url?q=https://www.wevolver.com/profile/the.next.byte&source=gmail&ust=1672821999265000&usg=AOvVaw3lLKdHdEN0YvCEsaHI7hx9" href="https://www.wevolver.com/profile/the.next.byte" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/af523f9f-6e33-407d-8aec-98ea14b8fd45?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> The full article will continue below.<hr>Mahsa Shoaran of the <a href="https://www.epfl.ch/labs/inl/" target="_blank">Integrated Neurotechnologies Laboratory</a> in the School of Engineering collaborated with St&eacute;phanie Lacour in the <a href="https://www.epfl.ch/labs/lsbi/" target="_blank">Laboratory for Soft Bioelectronic Interfaces</a> to develop NeuralTree: a closed-loop neuromodulation system-on-chip that can detect and alleviate disease symptoms. Thanks to a 256-channel high-resolution sensing array and an energy-efficient machine learning processor, the system can extract and classify a broad set of biomarkers from real patient data and animal models of disease in-vivo, leading to a high degree of accuracy in symptom prediction.&ldquo;NeuralTree benefits from the accuracy of a neural network and the hardware efficiency of a decision tree algorithm,&rdquo; Shoaran says. &ldquo;It&rsquo;s the first time we&rsquo;ve been able to integrate such a complex, yet energy-efficient neural interface for binary classification tasks, such as seizure or tremor detection, as well as multi-class tasks such as finger movement classification for neuroprosthetic applications.&rdquo;Their results were presented at the 2022 IEEE International Solid-State Circuits Conference and&nbsp;<a href="https://ieeexplore.ieee.org/document/9905664" rel="noopener" target="_blank">published</a> in the IEEE Journal of Solid-State Circuits, the flagship journal of the integrated circuits community.<h2>Efficiency, scalability, and versatility</h2>NeuralTree functions by extracting neural biomarkers &ndash; patterns of electrical signals known to be associated with certain neurological disorders &ndash; from brain waves. It then classifies the signals and indicates whether they herald an impending epileptic seizure or Parkinsonian tremor, for example. If a symptom is detected, a neurostimulator &ndash; also located on the chip &ndash; is activated, sending an electrical pulse to block it.Shoaran explains that NeuralTree&rsquo;s unique design gives the system an unprecedented degree of efficiency and versatility compared to the state-of-the-art. The chip boasts 256 input channels, compared to 32 for previous machine-learning-embedded devices, allowing more high-resolution data to be processed on the implant. The chip&rsquo;s area-efficient design means that it is also extremely small (3.48mm2), giving it great potential for scalability to more channels. The integration of an &lsquo;energy-aware&rsquo; learning algorithm &ndash; which penalizes features that consume a lot of power &ndash; also makes NeuralTree highly energy efficient.In addition to these advantages, the system can detect a broader range of symptoms than other devices, which until now have focused primarily on epileptic seizure detection. The chip&rsquo;s machine learning algorithm was trained on datasets from both epilepsy and Parkinson&rsquo;s disease patients, and accurately classified pre-recorded neural signals from both categories.&ldquo;To the best of our knowledge, this is the first demonstration of Parkinsonian tremor detection with an on-chip classifier,&rdquo; Shoaran says.<h2>Self-updating algorithms</h2>Shoaran is passionate about making neural interfaces more intelligent to enable more effective disease control, and she is already looking ahead to further innovations.&ldquo;Eventually, we can use neural interfaces for many different disorders, and we need algorithmic ideas and advances in chip design to make this happen. This work is very interdisciplinary, and so it also requires collaborating with labs like the Laboratory for Soft Bioelectronic Interfaces, which can develop state-of-the-art neural electrodes, or labs with access to high-quality patient data.&rdquo;As a next step, she is interested in enabling on-chip algorithmic updates to keep up with the evolution of neural signals.&ldquo;Neural signals change, and so over time the performance of a neural interface will decline. We are always trying to make algorithms more accurate and reliable, and one way to do that would be to enable on-chip updates, or algorithms that can update themselves.&rdquo;<hr>ReferencesU. Shin, C. Ding, B. Zhu, Y. Vyza, A. Trouillet, E. C. M. Revol, S. P. Lacour, M. Shoaran, &quot;NeuralTree: A 256-Channel 0.227-&mu;J/Class Versatile Neural Activity Classification and Closed-Loop Neuromodulation SoC,&quot; in IEEE Journal of Solid-State Circuits (JSSC), vol. 57, no. 11, pp. 3243-3257, Nov. 2022, doi:&nbsp;<a href="https://ieeexplore.ieee.org/document/9905664" rel="noopener" target="_blank">10.1109/JSSC.2022.3204508</a>.U. Shin, L. Somappa, C. Ding, B. Zhu, Y. Vyza, A. Trouillet, S. P. Lacour, M. Shoaran, &ldquo;A 256- Channel 0.227&mu;J/class Versatile Brain Activity Classification and Closed-Loop Neuromodulation SoC with 0.004mm2-1.51&mu;W/channel Fast-Settling Highly Multiplexed Mixed-Signal Front-End&quot; in IEEE International Solid-State Circuits Conference (ISSCC), 2022, doi:&nbsp;<a href="http://ieeexplore.ieee.org/document/9731776" rel="noopener" target="_blank">10.1109/ISSCC42614.2022.9731776</a>.

EPFL researchers have combined low-power chip design, machine learning algorithms, and soft implantable electrodes to produce a neural interface that can identify and suppress symptoms of various neurological disorders.

A neuro-chip to manage brain disorders

Image credit: Wyss Institute at Harvard University

Article #8 of Improving Lives with Digital Healthcare Series: Advancements in electronics have transformed the healthcare sector. The focus is on improving the experiences of users by utilizing cutting-edge technologies like advanced drug delivery systems, wearables, surgical robots, and more.

The Next-Generation of Medical Technologies: Digitized, Miniaturized, and Connected

This is the fourth article in an&nbsp;<a href="https://www.wevolver.com/article/design-challenges-in-consumer-and-medical-wearables" rel="noopener noreferrer" target="_blank">8-part series</a>&nbsp;featuring articles on Improving Lives with Digital Healthcare. The series focuses on electronic systems that enable innovation in the healthcare industry. This series is sponsored by Mouser Electronics. Through the sponsorship, Mouser Electronics shares its passion for technologies that enable smarter and connected applications.Brain-Computer Interface (BCI) is a means to establish direct communication between a human brain and a computer to allow the machine to sense and be controlled by thoughts converted to electrical signals. The technology has its potential applications in education, gaming, entertainment, and above all, in medical science. BCI devices can help people with paralysis or severe motor disabilities control prosthetic devices.Artificial Intelligence (AI) and Machine Learning (ML) combined with Digital Signal Processing (DSP) enable greater accuracy and reliability in evaluating and developing BCI applications. In this article, we examine this field, and some of the critical electronic components within the signal chain required to measure brain waves, bodily functions, and how everything is put together.<h2 dir="ltr">Brain-Computer Interface and Electroencephalograms</h2>The human brain produces oscillating electronic voltages. The typical value of these voltages is minimal, measured in units on the order of millionths of volt (microVolts). The most common way to collect and analyze these brain-wave voltages is through an electroencephalogram (EEG). An EEG is an electrophysiological monitoring method to record electrical activity on the scalp. It captures signals directly related to the brain waves happening directly under the skull.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU4NDAxMzUyODUwLTE2NTg0MDEzNTI4NTAucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="720" height="405" class="fr-fic fr-dii">Fig. 1: By understanding the brain&#39;s activity in different situations, it is possible to make robotic equipment that can be controlled by thoughts. Source: National Science FoundationBCI via an EEG can be unidirectional (one-way) or bidirectional (two-way). Bidirectional BCI allows information to flow both ways, thus opening the brain to feedback and future adjustments. EEGs can be invasive, semi-invasive, or non-invasive. Invasive EEGs involve directly locating and connecting devices to the human brain. Semi-invasive EEGs can be placed between the brain and the skull. Non-invasive BCI, on the other hand, is generally done by a cap placed on the skull with various electrodes.&nbsp;EEGs provide temporal resolution of 0.05 seconds and spatial resolutions on the order of 10 mm. Other techniques, besides the electrical technique employed by EEGs, can be used to gather data. These techniques can employ magnetic, metabolic, or other forms.Brain waves are classified into one of five general categories based on their frequency as shown in Table 1. Medical researchers break these frequencies into bands because each band represents a distinct way a brain operates in performing its functions. For example, critical activities such as memory and recollection happen especially, but not exclusively, in the theta band. Researchers use these bands to analyze what might be going on if appearing signals are too little, too great, or in an optimal amount.<div align="left" dir="ltr"><table><tbody><tr><td>Band</td><td>Frequency (Hz)</td></tr><tr><td>Delta</td><td>0.5-3</td></tr><tr><td>Theta</td><td>3-8</td></tr><tr><td>Alpha</td><td>8-12</td></tr><tr><td>Beta</td><td>12-38</td></tr><tr><td>Gamma</td><td>38-42</td></tr></tbody></table></div>Table 1: The five general categories of brain wave bands. Each frequency range is a nominal value and not necessarily absolute.An EEG acquires the brainwave signals and digitizes them. They are then signal-processed, where features can be extracted and translation algorithms perform classifications. They also can be printed out or recorded for future analysis.&nbsp;Signal outputs can be utilized to form device commands to provide instructions related to motor control, locomotion/movement, and environmental conditions or stimuli. BCI helps allow disabled people to have more control of their external environments.<h2 dir="ltr">Brain-Computer Interface and the Human Condition</h2>Because of human biology, our senses and our intelligence have fundamental limitations. It is conceivable that BCI and implants could enhance or provide new sensory information and augment biological capabilities.&nbsp;A primary consideration in merging man and machine is understanding how the machine and the human interact and exchange information between themselves on a real-time basis since they operate in two different domains. More work remains to be done to understand how the mutual coordination of individually-addressable neurons directing the brain can function in its environment while maintaining coordination with the digitally-addressable domain of the interface.&nbsp;<h2 dir="ltr">Brain-Computer Interface Research</h2>BCI is also being investigated to look at areas to help humanity, including restoring or enhancing human vision, motor recovery for disabled limbs, and brain mapping to assist in restoring and correcting various neurological damage and disorders. Brain mapping can lead to a greater understanding of seeing how human thought is realized to human action. It can lead to augmented human learning, new or enhanced human sensing, and new embedded autonomous neural systems. Let&rsquo;s look at two examples of where BCI can continue to evolve and lead.<h3 dir="ltr">Superhuman Cognition</h3>Billionaire Elon Musk is actively investigating BCI issues. He is one of the founders of Neuralink Corp., a neurotechnology company developing implantable brain-machine interfaces. Neuralink is working on building better tools for communicating with the brain. These founders believe that, with the right team, the applications for this technology are limitless. Neuralink is exploring the possibility of embedding into the brain ultrafine electronic threads that permit neural activity. One of Musk&rsquo;s stated goals is to achieve &ldquo;superhuman cognition.&rdquo;&nbsp;Inventor and futurist Ray Kurzweil believes that human intelligence is characterized by its remarkable ability to recognize patterns. He views human intelligence as an evolutionary, self-organizing hierarchical system operating in the context of a biological pattern-recognition machine. Musk is motivated to achieve superhuman cognition based upon his desire for humanity to negotiate more proficiently in understanding the emergence and spread of more powerful AI, which is becoming ever more adept in its excellence at pattern recognition.&nbsp;<h3 dir="ltr">New Senses</h3>When looking at how BCI can enhance human senses, one can consider the case of Neil Harbisson, cofounder of the Cyber Foundation. He has been recognized as the world&rsquo;s first cyborg. Born color-blind, Harbisson has permanently installed an antenna into his skull so that he can now literally hear color, substituting his auditory sense in place of his visual limitation. Harbisson is actively advocating a future in which humans incorporate technology into their bodies.<h3 dir="ltr">Sensor Hubs</h3>Supporting these efforts, sensor hubs are being employed in various ways to collect additional biometric information beyond BCI. Sensor hubs use multiple sensors and a microcontroller to collect and analyze numerous human parameters not directly accessed by brain waves. These can include collecting information about the human pulse heart rate, pulse blood oxygen saturation (SpO2), and estimated blood pressure.<h2 dir="ltr">Ensuring High-Quality Data</h2>Because brain signals are so small, the entire electronic signal chain is prioritized in its design to minimize noisy, spurious, or artifact signals. The patient might induce these sources through their physical movements, sweating, eye movements, heart rhythms, and the like. Electrical errors can result from 50Hz/60Hz noise, electrode-skin contact issues, and cable movements.Successful electronic component selection will focus on utilizing high-precision, low-noise, high-resolution signal chain products. Low-noise amplifiers (LNA), unity-gain buffers, and precision Analog-to-Digital Converters (ADCs) are chosen to prevent the introduction of unwanted signals into the chain while providing the ability to resolve data accurately and reliably. Differential amplifiers and bandpass filters are also employed to ensure only high-quality data is transmitted. Appropriate connectors and jumpers are needed to get accurate signals into and out of the brain.&nbsp;<h2 dir="ltr">Artificial Intelligence with Brain-Computer Interface</h2>AI and its subsets, including ML and deep learning (DL), are enabling approaches in EEG-based BCIs. DL can offer automatic classifications of EEG signals. This effort allows for the data to be utilized in various applications and other Convolutional Neural Networks (CNN) training. At present, human expertise supports AI approaches. The desire is to eliminate artifacts, increase the data quality, and continue to realize gains in AI technology so that measured brain wave signals can continue to exhibit exponential increases in their ability to be classified by AI through DL techniques.<h2 dir="ltr">Electronic Components by Molex Enabling Brain-Computer Interface Applications</h2><a href="https://www.mouser.com/new/molex/molex-025-premo-flex-jumpers/" target="_blank">Molex 0.25mm-Pitch Premo-Flex Jumpers</a> offer reliable connectivity in a compact design for tight packaging applications. The jumpers deliver durable, ultra-flexible, cost-effective solutions for printed circuit board (PCB) connections in virtually any industry. These FFC/FPC jumpers are available in standard lengths, pitches, and circuit sizes to accommodate a wide range of flexible interconnect requirements between two PCBs. Molex 0.25mm-Pitch Premo-Flex Jumpers are ideal for medical applications, including patient monitoring for signals, including the body&rsquo;s condition, surgical equipment, and telehealth. <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU4NDAxMzUxNDY5LTE2NTg0MDEzNTE0NjkucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii">Fig. 2:&nbsp;<a href="https://www.mouser.com/new/molex/molex-025-premo-flex-jumpers/" rel="noopener noreferrer" target="_blank">Molex 0.25mm-Pitch Premo-Flex Jumpers</a><a href="https://www.mouser.com/new/molex/molexeasyon/" target="_blank">Molex 0.25mm Pitch Easy-On FPC Connectors</a> offer a 50 V voltage rating, 50 M&Omega; insulation resistance, and 150 V AC dielectric withstanding voltage. These connectors provide designers with a range of sizes and styles to accommodate other PCB components. Molex 0.25 mm Pitch Easy-On FPC Connectors are ideal for next-generation medical devices. <img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU4NDAxMzUxMzcwLTE2NTg0MDEzNTEzNzAucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" width="720" height="144" class="fr-fic fr-dii">Fig. 3:&nbsp;<a href="https://www.mouser.com/new/molex/molexeasyon/" rel="noopener noreferrer" target="_blank">Molex 0.25mm Pitch Easy-On FPC Connectors</a><h2 dir="ltr">Conclusion</h2>EEG-based BCI relies on high-performance electronic signal chains. Careful consideration of all critical electronic components, including reliable connectivity in compact designs, are needed to accurately measure EEG and other bodily functions. AI and DL techniques enable dynamic EEG data to receive better interpretations and allow humanity to realize more benefits from BCI.This article was initially published by Mouser and Molex in an <a href="https://www.mouser.com/news/molex-improving-lives-with-digital-healthcare/molex-improving-lives-with-digital-healthcare.html" target="_blank">e-magazine</a>. It has been substantially edited by the Wevolver team and Electrical Engineer <a href="https://www.wevolver.com/profile/ravi.rao" target="_blank">Ravi Y Rao</a>. It&#39;s the fourth article from the Improving Lives with Digital Healthcare Series. Future articles will introduce readers to some more interesting applications of electronics in healthcare.<hr>Introductory article covered the f<a href="https://www.wevolver.com/article/biomedical-instruments-and-the-future-of-digital-healthcare/draft" rel="noopener noreferrer" target="_blank">undamentals of biomedical instruments and the ways in which digitizing them is transforming healthcare.&nbsp;</a>Article 1 explored the&nbsp;<a href="https://www.wevolver.com/article/design-challenges-in-consumer-and-medical-wearables" rel="noopener noreferrer" target="_blank">design challenges in Consumer and Medical wearables.</a>&nbsp;It showcased how technologies once limited to hospitals are now made available to everyone for monitoring personal health.Article 2&nbsp;was focused on the present state of robotic surgery. <a href="https://www.wevolver.com/article/connectivity-solutions-for-the-next-generation-of-surgical-robots" rel="noopener noreferrer" target="_blank">It explained how advancements in robotics and communication, combined with the expertise of surgeons, enable customized treatments for patients.&nbsp;</a>Article 3 presents an&nbsp;<a href="https://www.wevolver.com/article/sensing-and-energy-systems-for-minimally-invasive-cardiovascular-surgeries" rel="noopener noreferrer" target="_blank">overview of how new sensing, communication, and energy systems, engineered for the healthcare sector can be used to transform cardiovascular disease treatment procedures.</a>Article 4 examined&nbsp;<a href="https://www.wevolver.com/article/next-generation-medical-devices-for-brain-computer-interfaces" rel="noopener noreferrer" target="_blank">Brain-Computer Interfaces and how they help in enhancing human vision, motor recovery for disabled limbs, and more.</a>Article 5 featured an <a href="https://www.wevolver.com/article/designing-medical-devices-for-real-life-an-interview-with-molex-printed-circuit-solutions" rel="noopener noreferrer" target="_blank">informative webchat between Mike Depp, and Glen Capek from Molex, as they discussed trends in flexible electronics driving new solutions for medical wearables applications.&nbsp;</a>Article 6 discussed&nbsp;<a href="https://www.wevolver.com/article/immersive-technologies-in-medical-education" rel="noopener noreferrer" target="_blank">how immersive digital technologies like Augmented Reality (AR) and Virtual Reality (VR) make medical learning more engaging through lifelike experiences.</a>Article 7 <a href="https://www.wevolver.com/article/enabling-early-diagnosis-and-better-postoperative-care-with-remote-health-monitoring-devices" rel="noopener noreferrer" target="_blank">explained the role of wearable devices and their enabling technologies in revolutionizing continuous health monitoring.&nbsp;</a>Final article was&nbsp;<a href="https://www.wevolver.com/article/the-next-generation-of-medical-technologies-digitized-miniaturized-and-connected" rel="noopener noreferrer" target="_blank">a roundup of the entire series that tried to give readers a snapshot of the potential of medical technologies in the present times.</a><hr><h2 dir="ltr">About the sponsor: Mouser Electronics</h2>Mouser Electronics is a worldwide leading authorized distributor of semiconductors and electronic components for over 1,100 manufacturer brands. They specialize in the rapid introduction of new products and technologies for design engineers and buyers. Their extensive product offering includes semiconductors, interconnects, passives, and electromechanical components.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU4NDAxMzUxMTY4LTE2NTg0MDEzNTExNjgucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii"><h2 dir="ltr">References</h2>[1] Next-gen devices for Brain-Computer Interfaces, Mouser, [Online], Available from: <a href="https://www.mouser.com/blog/next-generation-medical-devices-bci" target="_blank">https://www.mouser.com/blog/next-generation-medical-devices-bci</a>

Article #4 of Improving Lives with Digital Healthcare Series: Transferring information directly between the human brain and a computer can unlock the possibilities of using machines as extended parts of the human body.

Next-Generation Medical Devices for Brain-Computer Interfaces

<a href="https://brooksrehab.org/" target="_blank">Brooks Rehabilitation</a> recently announced that the MagTrack study, a collaborative research endeavor with the&nbsp;<a href="https://www.ece.gatech.edu/" target="_blank">Georgia Tech School of Electrical and Computer Engineering</a>, has been successfully completed. Feedback from the Brooks clinical team and its patients has allowed Georgia Tech engineers to transform their early research prototype into a user-ready version that was tested by more than 17 power wheelchair users living with tetraplegia — a form of paralysis caused by spinal cord injury that affects the arms, hands, trunk, legs, and pelvic organs.The collaboration between the Brooks and Georgia Tech teams has created a path to a first-of-its-kind, innovative application for individuals living with disabilities. The teams — comprised of physicians, clinical therapists, and engineers — brought together multidisciplinary expertise in advanced science, technology, and clinical rehabilitation.“We met with the Georgia Tech team years ago, when we first heard of the research breakthroughs they were achieving for wheelchair users. Brooks is constantly looking for technology that is useful for our patient population living with spinal cord injuries and mobility impairments. To see where the MagTrack project has advanced even just since the early stages of this study is incredible,” said Geneva Tonuzi, medical director of the spinal cord injury program, the spinal cord injury and related disorders day treatment program, and Cyberdyne HAL Therapy at Brooks Rehabilitation.As a result of this engineering-clinical collaboration,&nbsp;<a href="https://magtrack.ece.gatech.edu/" target="_blank">MagTrack</a> was created as a cutting-edge assistive technology that enables power wheelchair users to control their connected devices (e.g., smartphone, computer) and drive their power wheelchairs using an alternative, multimodal controller. In addition, the assistive device is designed to be wearable, wireless, and adaptable to the user’s specific condition.The MagTrack study is earning the praise of patients and scientists alike and has been&nbsp;<a href="https://ieeexplore.ieee.org/document/9540352" target="_blank">published</a> in&nbsp;<a href="https://www.embs.org/tbme/" target="_blank">IEEE Transactions on Biomedical Engineering</a>. From the beginning, the MagTrack studies have tested the performance of the Head-Tongue Controller (HTC), an earlier version of the MagTrack technology, on its ability to perform complex human-machine interactions that will enhance users’ quality of life. The MagTrack’s HTC allows the user to perform a variety of complex tasks in a single controller through the use of tongue and head movements, which are detected by eyewear and a tiny tracer that is temporarily glued onto the tongue using Glustitch’s&nbsp;<a href="https://periacryl.com/" target="_blank">PeryAcryl</a> bio-compatible adhesive. Target-specific commands are generated from these motions using advanced data processing and machine learning models. This combination of input modalities allows the user to perform a variety of daily functions with customizable control, from performing complex computer tasks (e.g., mouse navigation, scrolling, drag-and-drop) to completing advanced driving maneuvers when connected to a power wheelchair.In the latest study, researchers connected the MagTrack technology to a single power wheelchair donated by Quantum Rehab, and recruited 17 patient volunteers from Brooks Rehabilitation to test the functionality and usability of the device by completing a set of both simple and advanced driving tasks. Results showed that new users of MagTrack can complete these tasks as fast, and sometimes even faster, with the MagTrack’s HTC rather than their personal, alternative controller. Since the study session lasted less than 3 hours — and in a power wheelchair that wasn’t their own — it is anticipated that participants would be more proficient, and thus perform better with MagTrack, if they were given more time to familiarize themselves with its multimodal capabilities and using their own power wheelchair."Working with all of the participants has been very rewarding,” said Jesse Milliken, speech-language pathologist in the spinal cord injury program at&nbsp;<a href="https://brooksrehab.org/" target="_blank">Brooks Rehabilitation Hospital</a>. “Each patient who came in was someone who has been directly affected by a spinal cord injury and who can truly benefit from this technology. It was amazing to see how their faces lit up when they saw they were able to control their wheelchair with such ease and comfort. They all said they can see this improving their day-to-day lives if it were available to them. It's been such an honor to be a part of this process and see the work and thought process behind such advanced technology." Patients from the&nbsp;<a href="https://brooksrehab.org/" target="_blank">Brooks</a> spinal cord injury program who have participated in phase three of the study call the advancement “exciting” and a “great system that can be used for so many things.” After experiencing the technology themselves, they believe it will “touch the lives of those who are able to use it.”To date, the head array and sip-and-puff are the most common alternative controllers recommended by physical therapists to individuals living with tetraplegia, while specialized switches and joystick technology are available for those with mobility in their upper extremities. These technologies were developed many decades ago for the basic need of controlling a power wheelchair. Since then, a lack of innovation in this field has hindered these assistive technologies from adapting to today’s technology. Furthermore, they are affixed to the wheelchair, which becomes inaccessible once the user is transferred to a bed, a couch, or any location away from the wheelchair. Therefore, there is a growing need for this population to have access to new, alternative controllers that will enable them to be active members of an interconnected digital world.“The trajectory of the MagTrack study shows an unprecedented possibility for the advancement of independent function as well as mobility for electric wheelchair users. Our team and partners are energized and motivated by the recent patient trials to continue to push this technology and its capabilities as far as possible. This technology can significantly improve people’s lives. We will continue to work to see these advances in assistive technology come to life,” said Georgia Tech’s Omer T. Inan, director of the Inan Research Lab, Linda J. and Mark C. Smith Chair in Bioscience and Bioengineering, associate professor in the School of Electrical and Computer Engineering, and adjunct associate professor in the Wallace H. Coulter Department of Biomedical Engineering.“MagTrack is an innovative assistive technology aimed for those living with physical paralysis to have access to more complex human-machine interactions, which will facilitate the control of more devices in their everyday life that they cannot easily use otherwise,” said Nordine Sebkhi, postdoctoral researcher at the Inan Research Lab in the School of Electrical and Computer Engineering. “The development of our wearable alternative controller eliminates the need for having multiple assistive technologies, replacing them with a single multimodal and integrated system.” Sebkhi is the co-creator of MagTrack and the technical lead in the development of this assistive technology.As a result of these studies,&nbsp;<a href="https://magtrack.ece.gatech.edu/" target="_blank">MagTrack</a> has been refined to offer a fully integrated, all-in-one experience so that a user can seamlessly switch between driving their wheelchair and controlling connected devices in their surroundings (e.g., smartphone, computer, automated door opener, smart TV). The system can be used anywhere since it is wearable, and its built-in wireless connectivity facilitates portability.The team at Georgia Tech is already working on a new version of&nbsp;<a href="https://magtrack.ece.gatech.edu/" target="_blank">MagTrack</a> that is not only more inconspicuous, but also includes detection of facial gestures that significantly augments its control capabilities. Thanks to a grant from the&nbsp;<a href="https://gra.org/" target="_blank">Georgia Research Alliance</a>, this new version of MagTrack will be tested in a focus group at the&nbsp;<a href="https://www.shepherd.org/" target="_blank">Shepherd Center</a> and in simulated testing in a home-like environment. In the coming year, the team plans to make MagTrack available to early adopters for at-home validation testing to further improve the technology before pursuing commercialization.This successful study is only a start since, at its core, MagTrack is a new type of body motion tracking. The Georgia Tech team is working on various designs of MagTrack to be used as a wearable articulograph for motor speech disorders, as a hand and joint tracking system for physical rehabilitation, and even as a finger tracking for VR/AR applications. The MagTrack team will be partnering with the&nbsp;<a href="https://gcmiatl.com/" target="_blank">Global Center for Medical Innovation</a> to assist in regulatory strategy and project planning to transition the technology from the lab to the market.

A squint is an example of a facial gesture that MagTrack can detect and issue a discrete command to control a connected device.

Clinical work begins with MagTrack, a cutting-edge assistive technology that enables power wheelchair users to control their connected devices and drive their power wheelchairs using an alternative, multimodal controller.

MagTrack Technology Opens Doors for Independent Operation of Smartphones, Computers, and Other Devices for Wheelchair Users

In this episode, we talk about an initiative from EPFL to allow those with spinal cord injuries to control robots for help with day-to-day tasks and MIT’s bug robots that are taking big strides for small scaled bio-robotics. As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/32c37b88-b3ef-47fb-9e84-e99e608e1ed2?dark=false" class="fr-draggable"></iframe> <hr>This podcast is sponsored by <a href="https://www2.mouser.com/" id="isPasted" rel="nofollow" target="_blank">Mouser Electronics</a>.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1642495419840-Mouser-sponsor-1-a.jpg" style="width: 766px;" class="fr-fic fr-dib"><hr><h3 id="isPasted">EPISODE NOTES</h3>(2:25) -&nbsp;<a href="https://www.wevolver.com/article/mind-controlled-robots-now-one-step-closer/" target="_blank">Mind-controlled Robots 🧠🦾</a>(12:25) -&nbsp;<a href="https://www.wevolver.com/article/giving-bug-like-bots-a-boost/" target="_blank">Bug Robots 🐞🤖</a>Episode 53 was brought to you by Mouser Electronics, Farbod &amp; Daniel’s favorite electronics distributor. Click <a href="https://resources.mouser.com/medical/drawing-a-blank-on-brain-computer-interfaces" target="_blank">here&nbsp;</a>to read the article giving an overview of brain-computer interface technologies.<hr>About the podcast:Every day, some of the most innovative universities, companies, and individual technology developers share their knowledge on Wevolver. To ensure we can also provide this knowledge for the growing group of podcast listeners, we started a collaboration with two young engineers, Daniel Scott Mitchell &amp; Farbod Moghaddam who discuss the most interesting content in this podcast series.&nbsp;To learn more about this show, please visit the <a href="https://www.wevolver.com/profile/the.next.byte" target="_blank">shows page</a>. By following the page, you will get automatic updates by email when a new show is published.Be sure to give us a follow and review on <a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" rel="nofollow" target="_blank">Apple</a> podcasts, <a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" rel="nofollow" target="_blank">Spotify</a>, and most of your favorite podcast platforms!Take a few seconds to leave us a review. It really helps!&nbsp;<a href="https://apple.co/2RIsbZ2" rel="nofollow" target="_blank">https://apple.co/2RIsbZ2</a>If you do it and send us proof, we’ll give you a shoutout on the show.

In this episode, we talk about an initiative from EPFL to allow those with spinal cord injuries to control robots for help with day-to-day tasks and MIT’s bug robots that are taking big strides for small scaled bio-robotics.

Podcast: Mind-Control and Bug-Like Robots

In this episode, we talk about how Neuralink wants to put chips in people’s heads, how Alauda wants to bring about the age of flying electric vehicles with their Airspeeder, and a joint effort to consider the carbon footprint of high performance processors. As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/816a5019-8dcc-44f6-87cf-e4a0b1f91ce6?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> <h3>EPISODE NOTES</h3>(0:46) -&nbsp;<a href="https://www.wevolver.com/article/neuralink-the-company-that-wants-to-put-a-chip-in-your-head" target="_blank">Neuralink</a>Neuralink wants to plant chips in people using a robotic and reversible operation with the goal of eliminating neural related illnesses.&nbsp;(9:25) -&nbsp;<a href="https://www.wevolver.com/article/how-evtol-flying-cars-are-made---airspeeder-factory-tour-at-goodwood-speedweek" target="_blank">Airspeeder: The Flying Car</a>Alauda is developing an electric flying race vehicle to display technical achievements and the viability of this form of transportation.&nbsp;(15:20) &nbsp;- Carbon Footprint &amp; Computer ChipsA joint effort between Harvard, Arizona State University, and Facebook revealed that manufacturing computer chips makes up a large portion of the total carbon footprint of electronic devices. With this in mind, the researchers hope to convince big technology companies to take this factor into account when designing devices that don’t even utilize the full performance that these chips offer.--About the podcast:Every day, some of the most innovative universities, companies, and individual technology developers share their knowledge on Wevolver. To ensure we can also provide this knowledge for the growing group of podcast listeners, we started a collaboration with two young engineers, Daniel Scott Mitchell &amp; Farbod Moghaddam who discuss the most interesting content in this podcast series.&nbsp;To learn more about this show, please visit the&nbsp;<a href="https://www.wevolver.com/profile/the.next.byte" target="_blank">shows page</a>. By following the page, you will get automatic updates by email when a new show is published.Be sure to give us a follow and review on <a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" rel="nofollow" target="_blank">Apple</a> podcasts, <a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" rel="nofollow" target="_blank">Spotify</a>, and most of your favorite podcast platforms!

In this episode, we talk about how Neuralink wants to put chips in people’s heads, how Alauda wants to bring about the age of flying electric vehicles with their Airspeeder, and a joint effort to consider the carbon footprint of high performance processors.

Podcast: Neuralink, Airspeeder: The Flying Car, Carbon Footprint & Computer Chips

This article was discussed in our <a data-saferedirecturl="https://www.google.com/url?q=https://www.wevolver.com/profile/the.next.byte&source=gmail&ust=1640817319915000&usg=AOvVaw2nPRdRwJrXSYYeM9RCFu5x" href="https://www.wevolver.com/profile/the.next.byte" id="isPasted" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/816a5019-8dcc-44f6-87cf-e4a0b1f91ce6?dark=false" class="fr-draggable"></iframe>The full article will continue below.<hr><h2>The Elevator Pitch</h2>Neuralink wants to solve brain and spine related illnesses via the seamless integration of a coin-sized device with your brain. In summer 2020, the company held a live product demo hosted by CEO Elon Musk to display what they have been working on.<iframe src="https://www.youtube.com/embed/CLUWDLKAF1M?&amp;t=581s&amp;wmode=opaque&amp;rel=0" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 788px; height: 438px;"></iframe><h2>The Device</h2>Neural interfacing technology capable of reading and stimulating neuron activity is not necessarily new, but Neuralink's device known as the Link boasts certain features that make it stand out, such as 1024 channels (reportedly 100x more than current competitors), wireless inductive charging, a small form factor (allowing seamless integration with the skull), and utilization of readily available, mass-produced parts making the device as affordable as a new smartphone.&nbsp;<h2><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjE2ODEyNDgyNDE2LXRoZS1saW5rLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 788px;" class="fr-fic fr-dib" alt="">Image 1. The Link Device (CNET) The Procedure</h2>A robot will remove a portion of your skull the same size as the device and thread the electrodes to a segment of your brain where small electric charges will stimulate the neurons. &nbsp;Safety and accessibility are some of the primary objectives with this implant.&nbsp;Here is how the team plans on hitting those marks:- Anesthesia is not required- The entire surgery can be done under an hour- Patients can be released from hospital the same day as the procedure- A robot can do the entire procedure to guarantee accuracy- It will automatically inspect and insert electrodes where there are no veins or arteries- It is completely reversible; if you decide you don't want it, take it out without any damages<h2 class="fr-img-space-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjE2ODEyNjM5NDcwLW5ldXJhbGluay1pbnN0YWxsYXRpb24uanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 788px;" class="fr-fic fr-dib">Image 2. Link procedure process (CNET) The Motivation</h2>A key driving force behind this project is providing an inexpensive, safe, convenient, and reversible neural interfacing solution that could potentially eliminate neural illnesses while offering those suffering from spinal injuries the chance to regain their mobility. Still, that's not the most ambitious part of this project.Musk has repeatedly expressed his concern about the rapid rise of artificial intelligence (AI) and what it could mean for the future of humanity; therefore, he sees the Link as a viable life raft where the human mind could integrate with AI. In fact, the Neuralink team already demonstrated an elementary version of this long-term goal by having a monkey control a computer using their device to play video games.<h2>The Functionality</h2>Usually at this point everyone has the same big question: does it work? Well, the proof is in the pigs.The stars of the 2020 product demo were three little pigs that helped demonstrate the safety of the Link. The first pig had never had an implant, the second had an implant at some point but it had been removed, and the third was the one currently with an implant; the major takeaway was that you will not experience any noticeable negative changes to your behavior with or without the implant (even if you've removed it).Gertrude, the third pig, was proudly showing off her implant to the audience by having the neuron impulses connected to her snout visualized while being fed. Every time her snout touched food, the audience saw a spike.More impressively, the demo contained a video of a pig on a treadmill whose joint movements were being almost perfectly predicted using the information from the implant. This could theoretically help those with spinal injuries by relaying the movement information that they are thinking to a secondary implant located at the base of the spinal cord thereby enabling movement.&nbsp;<div class="fr-img-space-wrap"><div class="fr-img-space-wrap"><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjE2ODEyODIwMzg5LVBpZyB3YWxrLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 788px;" class="fr-fic fr-dib">Image 3. Predicted vs. actual joint movements (CNET)&nbsp;During the Q&amp;A, Elon mentioned that it is possible to have a feature for the Link where the user will be able to upload their memories to the cloud and replay them at will.&nbsp;</div></div><h2>The When</h2>Neuralink received a breakthrough designation from the FDA in July 2020 and it looks like they are on track to start human trials by the end of 2021.&nbsp;

Neuralink is an ambitious startup backed by Elon Musk that hopes to rid the world of brain-related illnesses using a coin-sized chip

Neuralink: The Company That Wants To Put A Chip In Your Head

In a&nbsp;<a href="https://www.nature.com/articles/s41467-019-10994-4" rel="noopener nofollow" target="_blank">paper</a> published in July 2019, researchers described a way in which neuroprosthetic devices — capable of monitoring and making sense of electrical signals in the human brain — will soon be able to help patients incapable of physical speech to be able to fully take part in interactive verbal exchanges.We are well on our way as Homo sapiens to becoming a species that fully merges technology with our organic bodies. In some ways, we’ve been getting at this for centuries already, beginning with the first use of eyeglasses, at the end of the thirteenth century in Italy, to improve vision by making it easy for someone to wear two magnifying lenses on the bridge of their nose.But ever since the invention of the computer and the first human-machine interfaces were born (HMIs), a dream of many technologists has been to create direct connections between computers and the human brain. These brain-computer interfaces (BCIs) — also known as Brain-Machine Interfaces (BMIs) — would eliminate the lag inherent in the translation between thought → physical action → computer response. BCIs also allow people who cannot perform physical actions required for HMIs to bypass that real-world step and directly control powerful computer tools with the electrical impulses in their brains.One of the dreams is that BCIs will eventually place the entire canon of human knowledge within the realm of immediate recall: No more searching the internet via typing or voice commands needed. In the near future, we will be able to think about what we need and pull whatever relevant information is available directly from a cloud and into the forefront of our minds.BCIs work because we are able to detect the signals sent between neurons in our brains between the dendrites and axons connecting them. These tiny bits are the differences in electrical potential expressed by ions on every neuron. Scientists can find and measure these signals using implantable electrodes.The signals become digital information which is then translated by algorithms that have been developed over many years of painstaking research and experimentation. Thus, our brain’s signals become a director for machine intelligence that can then be used to control specially-enabled prosthetic limbs and wheelchairs and move cursors and click buttons on monitors. The software can also be trained to recognize the signals that account for very specific “thoughts” that represent numbers and letters, which enables writing (of a sort) for people otherwise unable to physically write.Just like any software application, though, BCIs are susceptible to hacking, as already shown in some intentional attempts at&nbsp;<a href="http://brl.ee.washington.edu/wp-content/uploads/2014/05/07128844.pdf" rel="noopener nofollow" target="_blank">malicious brain-spyware creation</a>. If a BCI can move numbers and letters across a digital gulf, it isn’t going to be difficult for someone to hijack that data and be able to translate whether it represents a banking PIN or a social security number.While the holy grail for the medical community is to use BCIs in neuroprosthetics to change the lives of disabled people for the better (even to the point of the&nbsp;<a href="https://www.theguardian.com/technology/2014/apr/01/mind-controlled-robotic-suit-exoskeleton-world-cup-2014" rel="noopener nofollow" target="_blank">mind-controlled exoskeleton</a> a soccer player used to kick-off the 2014 World Cup), an entire ecosystem of business opportunities is growing around this cutting edge technology:—&nbsp;<a href="https://kernel.co/" rel="noopener nofollow" target="_blank">Kernel</a> is capturing memories from the hippocampus, reading them with AI and “recording” them with up to 80% accuracy.— Elon Musk’s&nbsp;<a href="https://www.neuralink.com/" rel="noopener nofollow" target="_blank">Neuralink</a> initiatives aim to create implantable interfaces between the brain and computers. The early goals will be to offer treatments for brain and nervous system disorders, with the eventual path leading to enhancing normally-functioning brains — i.e. increasing memory and processing speed, adding built-in cloud and internet access, and expanding our senses. This has been tested successfully in monkeys so far, with plans on track for human testing in 2020.— A company called&nbsp;<a href="https://www.foc.us/" rel="noopener nofollow" target="_blank">Foc.us&nbsp;</a>is marketing “brain stimulators” to improve reaction speeds for gamers.— <a href="https://www.neuropace.com/" rel="noopener nofollow" target="_blank">Neuropace</a> is working on ways to predict, detect and stop the signals sent among neurons that cause seizures.<iframe src="https://www.youtube.com/embed/TcAvtglo9Jg?&amp;wmode=opaque" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 788px; height: 583px;"></iframe>—&nbsp;<a href="https://www.mindmaze.com/" rel="noopener nofollow" target="_blank">Mindmaze</a> is creating a&nbsp;<a href="https://www.nanalyze.com/2016/05/augmedix-and-mindmaze-virtual-reality-in-healthcare/" rel="noopener nofollow" target="_blank">motion-capture VR/AR game system</a> to give paralyzed people a more full experience, while&nbsp;<a href="http://neurable.com/" rel="noopener nofollow" target="_blank">Neurable</a> is using similar tech to give people the ability to control toys and games with their thoughts.— The Pittsburgh-based startup Cerêve has already secured commercial clearance from the FDA to sell their&nbsp;<a href="https://ebbsleep.com/" rel="noopener nofollow" target="_blank">“Sleep System”</a> that can ameliorate insomnia.—&nbsp;<a href="https://www.brainco.tech/" rel="noopener nofollow" target="_blank">Brainco</a> is making wearable devices that will help teachers monitor the level of focus their students have in the classroom and better find and help those students with learning difficulties.—&nbsp;<a href="https://thenextweb.com/neural/2020/02/25/this-startup-is-building-a-brain-reading-device-to-take-on-elon-musks-neuralink/" rel="noopener nofollow" target="_blank">Neurosity</a> is also working on wearable devices with a keen eye for design and allowing app developers to use it as a playground for innovation.— The United State government, through the&nbsp;<a href="https://m.youtube.com/watch?v=vsbDQm2yISc&t=1s" rel="noopener nofollow" target="_blank">Defense Advanced Research Projects Agency</a> (DARPA), is researching BCIs for a large number of potential applications.All of these uses are possibilities, and there are hundreds of other potential applications for BCIs. Most come with a number of limitations are exactly how practical they would be in the real world. For instance, monitoring students’ focus in a classroom is all well and good until one realizes that actually helping those students would require more staff. Even greater problems need to be resolved before such technology will actually be all that useful.And then there is the fact that most EEG-based BCI systems are very obfuscated: Users and designers don’t actually know all of the possible commands that are available and how to use them in a given BCI. Nataliya Kosmyna of MIT Media Lab has&nbsp;<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210145" rel="noopener nofollow" target="_blank">proposed a new conceptual</a> and design space that will allow researchers to properly track, taxonomize, and compare all of their various work, which in turn should help in generating new uses for it.There are a number of ethical considerations that come along for the ride with the implementation of BCIs. One big one, which is evident across almost all technological breakthroughs, is the further stratification of society. There will be those people who can afford BCIs that can improve their lives drastically — whether for strictly medical reasons or to enhance human performance and quality of life in other ways.Next, there is the issue of just exactly how aware and mentally capable certain BCI patients will be, especially concerning those who exist in “locked-in”, comatose states. A BMI may allow these patients to communicate to a degree with the outside world, but there is no way (yet) for us to know exactly their degree of consciousness.<blockquote>All relevant parties need to be cautious and not infer that a BCI indicating certain levels of brain activity and semantic processing in a subject is evidence of an understanding of the ethical magnitude of life-and-death decisions and the ability to make them.</blockquote><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115612/" rel="noopener nofollow" target="_blank">-Walter Glannon</a>, Bioethics Professor at University of CalgaryYet another, and somewhat more immediately worrying for most of us, is that this technology essentially creates a bridge between the human mind and the outside world that might be manipulated by those with dark purposes. Plowing ahead at full-speed without devoting tremendous effort, concern, and diligence toward keeping the information in our brains safe — as well as the physical structure itself — will lead to some truly terrible outcomes. If software can be hijacked, and now the brain is a part of that software, might we see people themselves being hijacked by hackers and terrorists? Could a new kind of computer virus be engineered to create deleterious effects in the biology of a human mind and body?Every new and extremely powerful technological advance comes with the potential for amazingly good as well as nightmarishly bad results. Atomic power, satellites, genetic engineering, artificial intelligence: Brain-computer interfaces are no different. It only takes supremely smart people to make these great things, but it takes good and ethical smart people to monitor them and make sure the human race is not threatened by such inventions.

The merging of humanity with the technology we have created has begun…

Brain-Computer Interfaces: The Next Step in Human Evolution

During the Olympics, skiers think through the twists and spins they will make in an aerial competition, a speed skater visualizes how he will sneak past a competitor on the inside line, and a curler imagines the perfect sweep.&nbsp;It&rsquo;s called mental rehearsal, and psychologists and athletes alike know that it works: picturing ourselves going through routines, whether it&rsquo;s figure skating or something more mundane, improves our chances of success. Now, neuroscientists report Feb. 15 in&nbsp;Neuron, they&rsquo;ve learned how the brain learns physical tasks, even in the absence of real-world movement, and found that it could hinge on getting the mind to the right starting place, ready to perfectly execute everything that follows.A new study suggests that mental rehearsal&mdash;picturing oneself going through a routine, such as a skiing competition&mdash;improves performance by preparing the mind for action.&ldquo;Mental rehearsal is tantalizing, but difficult to study,&rdquo; said <a href="https://profiles.stanford.edu/intranet/saurabh-vyas" target="_blank">Saurabh Vyas</a>, a graduate student in bioengineering and the paper&rsquo;s lead author. That&rsquo;s because there&rsquo;s no easy way to peer into a person&rsquo;s brain as he imagines himself racing to a win or practicing a performance. &ldquo;This is where we thought brain-machine interfaces could be that lens, because they give you the ability to see what the brain is doing even when they&rsquo;re not actually moving,&rdquo; he said.Although there are some important caveats, the results could point the way toward a deeper understanding of what mental rehearsal is and, the researchers believe, to a future where brain-machine interfaces, usually thought of as prosthetics for people with paralysis, are also tools for understanding the brain, said <a href="https://profiles.stanford.edu/krishna-shenoy" target="_blank">Krishna Shenoy</a>, the Hong Seh and Vivian W. M. Lim Professor in the School of Engineering, a member of <a href="http://biox.stanford.edu/" target="_blank">Stanford Bio-X</a> and the <a href="https://neuroscience.stanford.edu/" target="_blank">Stanford Neurosciences Institute</a> and the study&rsquo;s senior author.<h2>What are you thinking?</h2>The idea for the study came while thinking about how people learn to use brain-machine interfaces to perform a task, Vyas said. In a typical setup, a person&mdash;or, very often, a monkey&mdash;has to learn to move a cursor around a computer screen using only patterns of activity in the brain, not hand or other movements. That got Vyas wondering whether what people (or monkeys) learned using brain-machine interfaces might somehow transfer, in a way similar to mental rehearsal, to physical movements.&ldquo;He&rsquo;s just sitting there thinking, and as he&rsquo;s thinking he&rsquo;s getting better and better&rdquo; at moving the cursor, Vyas said, referring to one of the monkeys he studied.&ldquo;The natural question becomes: What happens if you switch to another context, where now he actually has to generate muscle activity? Do you see the effects of that learning in that new context?&rdquo;The short answer is yes, mental learning does transfer to physical performance. Vyas initially taught two monkeys outfitted with brain-machine interfaces to move a cursor from one place to another on a computer screen using only their minds, then introduced a complication, called a visuomotor rotation: what mental signals they previously used to move a cursor up would now move it at an angle, say 45 degrees clockwise. The monkeys easily adapted, and that adaptation carried over when they repeated the same task using their hands, rather than the brain-machine interface, to control the cursor directly. Now, if the monkeys wanted to move the cursor up, they moved their hands 45 degrees clockwise.This suggested that the monkeys were doing something like mental rehearsal, Vyas said&mdash;what they had learned to do in their minds, they could then do with their hands. Some additional experiments and an analysis of recorded neural activity suggest the reason why: rehearsing the task with a brain-machine interface got patterns of activity in the monkeys&rsquo; brains into just the right spot, so they could carry out the same rotation task with their hands, even though they had never done so before.<h2>A new way to probe the mind</h2>&ldquo;There are key differences between our paradigm and true mental rehearsal,&rdquo; Vyas said, and there are reasons to be cautious about interpreting the results too broadly. For one thing, one can&rsquo;t just ask a monkey to imagine skiing down a mountain slope, as one could with a person. For another, mentally rehearsing a task is not the same as using a brain-machine interface to do it. In the latter case, people get feedback on how they&rsquo;re doing, something they can only imagine in mental rehearsal.&ldquo;We can&rsquo;t prove the connection beyond a shadow of a doubt,&rdquo; Shenoy said, but &ldquo;this is a major step in understanding what mental rehearsal may well be in all of us.&rdquo; The next steps, he and Vyas said, are to figure out how mental rehearsal relates to practice with a brain-machine interface&mdash;and how mental preparation, the key ingredient in transferring that practice to physical movements, relates to movement.Meanwhile, Shenoy said, the results demonstrate the potential of an entirely new tool for studying the mind. &ldquo;It&rsquo;s like building a new tool and using it for something,&rdquo; Shenoy said. &ldquo;We used a brain-machine interface to probe and advance basic science, and that&rsquo;s just super exciting.&rdquo;

Mentally preparing for physical activities primes the mind to perfectly execute tasks like skiing. | Getty Images​/Marcin Wiklik

A new tool explores how mental learning processes translate into physical performance.

Brain-machine interfaces visualize how the mind prepares for real-world action

Is there a way to preserve the fleeting, fragile stuff that makes us who we are?

Memory, Neuralink, and Immortality of Consciousness

Future cars will be both self-driving and manual. &quot;We wanted to harness technology to enhance drivers&rsquo; skills without interfering with the enjoyment of being behind the wheel,&quot; explains Jos&eacute; del R. Mill&aacute;n, who holds the <a href="https://cnbi.epfl.ch/" target="_blank">Defitech Foundation Chair in Brain-Machine Interface</a> (CNBI). As part of a joint project with Nissan researchers based at the CNBI, the team managed to read the brain signals that indicate a driver is about to do something &ndash; such as accelerate, brake or change lanes &ndash; in order to send that information to the vehicle. With this advance notice of a few hundreds of milliseconds, the smart vehicle can anticipate the driver&#39;s movements and make the ensuing maneuver easier. The car is also equipped with sensors to monitor its environment, which means it can help the driver when traffic conditions are difficult.An easier and more personalized driving experienceThe signals produced in the driver&#39;s frontal motor cortex are detected using a sensor-equipped EEG (electroencephalography) headset. They are then sent to the smart vehicle for processing. By combining that data with the information detected by its own sensors, the car can react to the situation at hand. &quot;If you&#39;re coming to a red light and getting ready to brake, the car will assist you by starting to brake 200&ndash;500 milliseconds before you do. But if you approach a red light and your brain shows no intention of slowing the car down, the car will warn you that the light is red to make sure you&#39;ve seen it,&quot; says Mill&aacute;n.We all generate different patterns of brain signals, so the vehicle learns from each driver and customizes its software. It stores each driver&#39;s regular routes, as well as their driving habits and style, using this information to more accurately anticipates what each driver might do at any time. The brain-machine interface not only makes driving easier, it also creates a more personalized experience, as the car will always be in sync with the driver. Even the car&rsquo;s setting can be transparently adapted to the driver&rsquo;s preferences. For instance, if the driver has adopted a more relaxed driving style, the interface will detect that the selected sports mode is not appropriate and switch the car to a more comfortable setting.Tech transferIn 2014, after four years of research, scientists from the CNBI delivered the brain-machine interface to their industry partner Nissan. The carmaker then continued the research through a senior innovation research program with support from the CNBI. The resulting technology was integrated into a prototype, creating the interface that enables the vehicle to communicate with the driver. This prototype was unveiled at the Consumer Electronics Show in Las Vegas in January.Since 2015, Nissan and the CNBI researchers have been working on further developing this brain-vehicle technology, mainly by adding an eye tracker function. &quot;Our eyes are always moving and observing what&#39;s going on around us,&quot; says Mill&aacute;n. &quot;But not everything we see is relevant or important. So we are studying ways to detect brain signals that indicate that a certain object or situation has caught our attention and needs to be factored in by the vehicle.&quot;For several years now, Mill&aacute;n&#39;s team has been developing scientific knowledge in detecting and using brain signals to control objects and our environment. They have been focusing on driver-assist technology with Nissan since 2011. In parallel, they have been exploring other applications for their expertise as well, such as helping people with motor disabilities.

EPFL and Nissan researchers are able to read a driver’s brain signals and send them to a smart vehicle so that it can anticipate the driver’s moves and facilitate the driving process. Nissan recently unveiled this brain-to-vehicle (B2V) technology. 

Future cars will be both self-driving and manual. "We wanted to harness technology to enhance drivers’ skills without interfering with the enjoyment of being behind the wheel," explains José del R. Millán, who holds the Defitech Foundation Chair in Brain-Machine Interface (CNBI).

A smart car that can read brain signals

<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1570181911758-inputtest2.jpeg" style="width: 461px;" class="fr-fic fr-dib">Study participants tapped Morse Code into Google Glass after four hours&nbsp;It&rsquo;s not exactly beating something into someone&rsquo;s head. More like tapping it into the side.Researchers at the Georgia Institute of Technology have developed a system that teaches people Morse code within four hours using a series of vibrations felt near the ear. Participants wearing Google Glass learned it without paying attention to the signals &mdash;they played games while feeling the taps and hearing the corresponding letters. After those few hours, they were 94 percent accurate keying a sentence that included every letter of the alphabet and 98 percent accurate writing codes for every letter.This is the latest chapter of passive haptic learning (PHL) studies at Georgia Tech. The same method &mdash; using vibrations while participants aren&rsquo;t paying attention &mdash;&nbsp;<a href="https://www.news.gatech.edu/2014/06/23/wearable-computing-gloves-can-teach-braille-even-if-you%E2%80%99re-not-paying-attention" target="_blank">has taught people braille</a>,&nbsp;<a href="https://www.news.gatech.edu/2008/11/07/reinventing-way-people-learn-play-piano" target="_blank">how to play the piano</a> and&nbsp;<a href="https://www.news.gatech.edu/hg/item/140221" target="_blank">improved hand sensation for those with partial spinal cord injury.</a>The PHL projects are all led by Georgia Tech Professor Thad Starner and his Ph.D. student Caitlyn Seim. The team decided to use Glass for this study because it has both a built-in speaker and tapper (Glass&rsquo;s bone-conduction transducer).In the study, participants played a game while feeling vibration taps between their temple and ear. The taps represented the dots and dashes of Morse code and passively &ldquo;taught&rdquo; users through their tactile senses &mdash; even while they were distracted by the game.&nbsp;The taps were created when researchers sent a very low-frequency signal to Glass&rsquo;s speaker system. At less than 15 Hz, the signal was below hearing range but, because it was played very slowly, the sound was felt as a vibration.&nbsp;Half of the participants in the study felt the vibration taps and heads a voice prompt for each corresponding letter. The other half &mdash; the control group &mdash; felt no taps to help them learn.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1570181952817-tap2.jpeg" style="width: 630px;" class="fr-fic fr-dib">The findings demonstrate silent, eyes-free text entry on a mobile device without a keyboard (participants touched on Glass&#39;s touchpad to enter Morse code during quizzes). &nbsp;Many mobile or wearable devices cannot accommodate a full keyboard, so it is a challenge to enable text entry on these devices. This research demonstrates a successful system and a rapid, low-effort way to learn it. Participants were tested throughout the study on their knowledge of Morse code and their ability to type it. &nbsp;After less than four hours of feeling every letter, everyone was challenged to type the alphabet in Morse code in a final test.The control group was accurate only half the time. &nbsp;Those who felt the passive cues were nearly perfect.The research was recently presented in Germany at the 20th International Symposium on Wearable Computers.&ldquo;Does this new study mean that people will rush out to learn Morse code? Probably not,&rdquo; said Starner. &ldquo;It shows that PHL lowers the barrier to learn text-entry methods &mdash; something we need for smartwatches and any text-entry that doesn&rsquo;t require you to look at your device or keyboard.&rdquo;Previous research on PHL used custom hardware to provide the tactile stimuli, but here researchers use an existing wearable device.&nbsp;&ldquo;This research also shows that other common devices with an actuator could be used for passive haptic learning,&rdquo; he says. &ldquo;Your smartwatch, Bluetooth headset, fitness tracker or phone.&rdquo;&ldquo;In our Braille and piano PHL studies, people felt vibrations on their fingers, then used their fingers for the task,&rdquo; said Seim. &ldquo;This study was different and surprising. People were tapped on their heads, but the skill they learned was using their finger.&rdquo;Seim&rsquo;s next study will go a step further, investigating whether PHL can teach people how to type on the trusted QWERTY keyboard. That would mean several letters assigned to the same finger, rather than using only one finger like Morse code.

brain–machine interface (BMIs)

Profiles