Supported by a gift from Meta, the two-year project uses electromyographic (EMG)-based human-machine interface technology as a platform for investigating motor learning through gamified training systems. While EMG systems are often studied in the context of prosthetic limb control, the broader goal of the project is to understand how adaptive interfaces can become more intuitive and embodied over time.

鈥淭his Meta support will enable my lab to work on real-world problems that can have an immediate impact on neurotechnologies.鈥� 鈥� Mohsen Rakhshan, assistant professor

麻豆映画传媒 was selected through Meta鈥檚 competitive funding initiative, in part because of its interdisciplinary approach pairing engineering with philosophy and ethics.

Mohsen Rakhshan, an assistant professor in 麻豆映画传媒鈥檚 Department of Electrical and Computer Engineering and the Disability, Aging and Technology (DAT) faculty cluster initiative, and Jonathan Beever, a professor of philosophy and director of the 麻豆映画传媒 Center for Ethics, will lead the project.

鈥淭his Meta support will enable my lab to work on real-world problems that can have an immediate impact on neurotechnologies,鈥� Rakhshan says. 鈥淭he impact ranges from individuals using augmented and virtual reality for entertainment to individuals with amputation or paralysis seeking to improve their quality of life. It also gives my engineering students the opportunity to integrate ethics research into their technical work.鈥�

Advancing Motor Learning Through EMG

EMG-based interfaces translate electrical signals generated by muscle activity into digital commands, allowing users to control devices through subtle physical gestures. In immersive environments, these systems can enable more natural interaction with virtual objects. In rehabilitation settings, they can assist in training neural prostheses.

The 麻豆映画传媒 team is using this technology to examine how people learn new motor skills in digital environments, particularly through gamified interaction tasks designed to strengthen human-computer coordination. By training both the participant and the signal-processing algorithm (often called a 鈥渄ecoder鈥�) simultaneously, through a process known as co-adaptation, researchers aim to create systems that improve alongside the user.

鈥淎 significant challenge for most of these systems is that they require constant retraining or calibration of the decoder,鈥� Rakhshan says. 鈥淩etraining after each use can discourage individuals from using these devices long term. The human nervous system is plastic 鈥� it can adapt and improve performance over time. But if the decoder is constantly reset or kept static, it may prevent the nervous system from leveraging that plasticity. We aim to develop a co-adaptive loop between the human and the device.鈥�

Rather than focusing solely on stable decoding, the project investigates how adaptive systems can enhance motor learning, improve user confidence and promote a stronger sense of embodiment in human-machine interaction.

If successful, the research could inform next-generation EMG systems used in immersive computing, rehabilitation technologies and assistive devices.

Embedding Ethics Into Engineering

A defining feature of the project is the integration of ethics alongside engineering from the outset.

鈥淚nterdisciplinary collaboration between ethics and technical experts is the best path forward for responsible innovation.鈥� 鈥� Jonathan Beever, professor

Longitudinal EMG studies can reveal subtle motor signatures that uniquely identify individuals, raising questions about privacy and data protection. Adaptive systems may also influence a user鈥檚 sense of agency, whether individuals feel genuinely in control of the interface. For example, if an EMG system begins adjusting its interpretation of muscle signals automatically, users may feel the device is responding to them intuitively or, in some cases, acting unpredictably. Researchers want to better understand how these dynamics affect trust, confidence, and long-term use.

To address these questions, Beever will be embedded within the 麻豆映画传媒 Laboratory for Interaction of Machine and Brain (LIMB), contributing directly to experimental design and evaluation. The team will conduct structured assessments of agency and embodiment while examining potential privacy leakage from EMG signal data.

鈥淚nterdisciplinary collaboration between ethics and technical experts is the best path forward for responsible innovation,鈥� Beever says. 鈥淭echnological advancement must be guided toward good ends. Our work emphasizes not only ethical research practices but also deeper questions about autonomy and agency in human-machine interfaces.鈥�

A Three-Phase Study

The longitudinal study will involve 30 participants completing 10 sessions over two months, allowing researchers to measure both short-term and long-term motor learning outcomes.

The project will occur in three phases:

Phase 1: Standardizing muscle signal data so artificial intelligence systems can more accurately interpret user intent.

Phase 2: Training both participants and machine learning models simultaneously 鈥� a co-adaptive process designed to improve human-computer interaction through gamified tasks.

Phase 3: Conducting structured evaluation of agency, embodiment and privacy risks while developing a publishable ethics framework for adaptive EMG-based systems.

鈥淭here has been a significant increase in industry interest in using biological signals such as EMG, from muscles, and EEG, from the brain, to interact with virtual and augmented reality, consumer electronics, prostheses for individuals with amputation and robotic systems for individuals with paralysis,鈥� Rakhshan says.

This research is supported by a gift from Meta. The project is conducted by faculty, staff and students in 麻豆映画传媒鈥檚 Department of Electrical and Computer Engineering, the Disability, Aging and Technology research cluster and the 麻豆映画传媒 Center for Ethics.

The winning team includes Mubarak Shah, the director of the 麻豆映画传媒 Institute of Artificial Intelligence (IAI); Helen Huang and Qiushi Fu, associate professors of biomedical engineering; Yue Wen, an assistant professor of biomedical engineering; Abhilash Durgam, a doctoral student who works in the Center for Research in Computer Vision; and Jerry Fu, a postdoctoral scholar mentored by Huang and Wen.

As top 10 winners, Team Marque鈥檚 code will be added to the competition鈥檚 open-source repository, contributing to the future advancement of EEG research. They also receive a certificate in recognition of their achievement. Shah says that placing in the top 10 at the world鈥檚 premier venue for AI and machine learning is a tremendous accomplishment for 麻豆映画传媒 and its newly established IAI.

鈥淚t speaks to the strength of 麻豆映画传媒鈥檚 interdisciplinary culture,鈥� Shah says.

鈥淥ur students and faculty, with their combined expertise in machine learning, neuroscience, signal processing and computer vision can compete with some of the world鈥檚 best teams.鈥� 鈥� Mubarak Shah, Trustee Chair Professor

The competitors had to prevail in two individual challenges that utilized data from the Healthy Brain Network, which includes EEGs of more than 3,000 children who were multitasking. Challenge 1 asked the teams to improve the predicted reaction time of a subject seeing change in contrast of an image while Challenge 2 called for an improved prediction of mental health traits in a subject.

Durgam says the secret to Team Marque鈥檚 success was to look for the patterns that hold true for all people.

鈥淩ather than treat this as a regression problem to predict a number, we used a classification approach where we taught our model to recognize the unique ‘profile’ of the person,鈥� Durgam says. 鈥淭his encouraged the model to understand the individual’s distinct characteristics rather than just treating the task as a simple math problem.鈥�

The team鈥檚 efforts are more than just an accomplishment for themselves and for the university 鈥� their code can now be used by scientists to advance EEG research.

鈥淥ur open-source repository supports open-science efforts, which I believe is necessary to make substantial breakthroughs in EEG research at a faster rate than any one group could accomplish alone,鈥� Huang says. 鈥淏eing able to predict mental health traits in developing children is a challenging problem that has great societal impact and could be solved faster collectively as a field by working in parallel and sharing data and code so groups don鈥檛 have to repeat something that has already been tried.鈥�

Team Marque came together after Durgam reached out to Huang to learn more about EEG. Each of them had already formed teams for the competition, but decided to combine efforts for better results. For Huang, the competition also had a personal connection as one of the organizers, Seyed Yahya Shirazi 鈥�21PhD, is her former student.

鈥淚 don鈥檛 think we have been in the top 10 if we didn鈥檛 combine efforts,鈥� Huang says. 鈥淭ogether, we could work in parallel to explore fundamentally different approaches first to identify the most promising one and then focus on optimizing specific parameters.鈥�

In an effort to expand the use of AI in agriculture, several 麻豆映画传媒 researchers will work together to develop several AI-driven technologies that aim to improve the industry鈥檚 field operations. The team is supported by a $2.74 million grant from the U.S. Department of Agriculture (USDA) – National Institute of Food and Agriculture (NIFA). The funded project will specifically enhance the agricultural applications produced by the AI Institute for Transforming Workforce and Decision Support (AgAID), an institute funded by NIFA. Professor Manoj Karkee from Washington State University is the team鈥檚 leading collaborator of AgAID.

Leading the charge for 麻豆映画传媒 is Professor Yunjun Xu of the Department of Mechanical and Aerospace Engineering. He will use his expertise to develop AI methods for motion control and scheduling in agricultural robots. These autonomous ground robots are used to conduct several operations in open fields such as detecting diseases and harvesting crops.

Collaborating with Xu are Professor Ladislau B枚l枚ni of the Department of Computer Science and Assistant Professor Chen Chen from the Center for Research in Computer Vision. B枚l枚ni will strive to integrate AI into the manipulation of agricultural robotic arms to improve the way they interact with their physical environment, while Chen will investigate a new AI method for the sensors used in precision agriculture, a farming practice that uses technology to make more accurate and informed decisions.

Also on the project is chemistry Professor Swadeshmukul Santra, who will work with Chen and Xu to integrate AI into the analysis of pesticide residues.

The 麻豆映画传媒 team hopes that these technologies will be of use to both current and future generations of farmers and AgAID researchers.

鈥淲e anticipate that each AI method will advance its respective state-of-the-art technology and can have performance superior to existing or traditional methods,鈥� Xu says. 鈥淲e also hope to inspire more people, especially younger generations, to join the U.S. agricultural sector workforce.鈥�

To spark an interest in agriculture, the 麻豆映画传媒 researchers plan to coordinate various outreach activities for students including a summer exchange program and workshops. They also plan to develop a new course and training materials around this work, which will be facilitated with the help of graduate students.

The project is funded via the NIFA interagency application program in conjunction with the U.S. National Science Foundation.

About the Researchers

Xu joined 麻豆映画传媒 as an assistant professor in 2008. He earned his doctoral degree in aerospace engineering from the University of Florida. His research interests include agricultural robots, control theory and flying vehicles. He is an Associate Fellow of the American Institute of Aeronautics and Astronautics and a Fellow of the American Society of Mechanical Engineers.

B枚l枚ni is a professor of computer science and the co-director of the AI Things Laboratory at 麻豆映画传媒. He has secondary joint appointments in the Department of Electrical and Computer Engineering and the Center for Research in Computer Vision. He is also a member of the 麻豆映画传媒 Cluster for Disability, Aging and Technology. He received his doctoral and master鈥檚 degrees from Purdue University. He is a senior member of the Institute of Electrical and Electronics Engineers, a senior member of the Association for Computing Machinery and a member of the Upsilon Pi Epsilon honorary society.

Chen is an assistant professor at the Center for Research in Computer Vision and previously served as a postdoctoral scholar for the center. His main research interests are computer vision, image and video processing, and machine learning. He earned his doctoral degree in electrical engineering from the University of Texas at Dallas. He is a senior member of the Institute of Electrical and Electronics Engineers.

Santra holds a doctorate in chemistry from the Indian Institute of Technology Kanpur. After graduating, he worked at the University of Florida (UF) as a postdoctoral researcher and later as a research assistant professor at the UF Department of Neurological Surgery and Particle Engineering Research Center. In 2005, Santra joined 麻豆映画传媒 as an assistant professor at the NanoScience Technology Center, the Department of Chemistry and the Burnett School of Biomedical Sciences. He is the director of the 麻豆映画传媒 Materials Innovation for Sustainable Agriculture center, a USDA-NIFA-recognized Center of Excellence.

Helen Huang, the principal investigator of the lab and associate professor in , understands firsthand how STEM (science, technology, engineering, mathematics) is dominated by men. Nationally, just 25% of those working in computer occupations are women, and just 15% of engineers and architects are women, according to the Pew Research Center. But with women like Huang in STEM leadership roles, those numbers can change 鈥� something International Women in Engineering Day seeks to influence as it celebrates the work of women engineers annually on June 23.

鈥淚 think the most important thing [for women in STEM] is to have a supportive network,鈥� Huang says. 鈥淪urround yourself with people who will encourage you to pursue what you鈥檙e interested in. There are plenty of women in STEM who would love to see more women in STEM.鈥�

In the BRaIN Lab, Huang helps student researchers conduct human subject experiments and analyze large sets of data from the brain, muscles and body during challenging balance and walking tasks. By measuring electrical activity of the brain, computer algorithms can estimate where and when areas of the brain activate during movement 鈥� valuable insight that can design better robotic devices and rehabilitation for those with impaired movement.

For Lindsey Lee, seeing the BRaIN Lab was an 鈥渁ha鈥� moment. While studying a bachelor鈥檚 degree in mechanical engineering 鈥� which she just graduated from this spring 鈥� she discovered the lab and a way to combine her passion for sports, movement and math. Since, she鈥檚 worked in the lab to analyze people鈥檚 patterns of walking in response to perturbations on a treadmill and that young and older adults increase their walking speed when a treadmill shifts rapidly from side-to-side, disrupting the normal walking pattern. Next, she will continue to analyze these findings and others in the BRaIN Lab while pursuing a master鈥檚 degree in biomedical engineering.

鈥淗aving Helen as a mentor has solidified my interest in the field and she鈥檚 encouraged me and helped build my confidence to continue onto graduate school,鈥� Lee says. 鈥淚 think it鈥檚 great to see a successful woman in this field. It can help inspire others who may not have similar examples in their life.鈥�

For Shayla Hoa, a sophomore in mechanical engineering, the BRaIN Lab and Huang鈥檚 success also have influenced her career interests.

鈥淚 often find myself surrounded by male classmates, but witnessing Helen鈥檚 remarkable career achievements and the strides she鈥檚 made has given me a sense of assurance to persevere,鈥� Hoa says. 鈥淭he BRaIN Lab has given me hands-on experience conducting human-subject experiments and collaborating with more experienced peers who I can depend on for guidance.鈥�

Huang hopes interest in the BRaIN Lab and biomedical engineering continues to grow. She feels it will at 麻豆映画传媒, as and are now offered. Limbitless Solutions, a nationally recognized nonprofit at 麻豆映画传媒 that designs and builds personalized prosthetics more affordably thanks to its 3D-printing technology, also has brought more attention to the growing field. 麻豆映画传媒 also offers a , which prepares students for careers in medical research and development.

As understanding of brain activity and human movement grows, ultimately Huang hopes to help preserve mobility.

鈥淭he end game is to make sure everyone can maintain their mobility,鈥� she says. 鈥淢obility is a big part of our quality of life. It can greatly impact what we do, our mood, our ability to be independent. Our ultimate goal is to help our growing population in this way.鈥�

To help address this critical issue and reduce disparities, a team of 麻豆映画传媒 researchers is partnering with the City of Orlando on a $2.3 million project funded by the National Institutes of Health (NIH), National Institute on Minority Health and Health Disparities.

The project seeks to address the public health problem and prevent falls with the optimization of technology that is low-cost and portable.

The work will help ensure older adults can 鈥渁ge in place,鈥� and supports the City Beautiful Action Plan 2022-2025, which, as one of its primary goals, prioritizes the development of affordable housing options and services to help older residents safely stay in their homes.

鈥淎s the population of our city ages and residents are living healthier, more active and longer lives, it鈥檚 important we ensure Orlando is a well-designed, livable community that promotes health and sustains economic growth, creating happier and healthier residents of all ages,鈥� says Orlando Mayor Buddy Dyer. 鈥淲e are excited to work with 麻豆映画传媒 on this grant as it will play a significant part in understanding how we can improve the health and safety of our older adult population and better implement age-friendly initiatives, especially in underserved neighborhoods.鈥�

Innovative Approach

With the new funding, , an associate professor at the College of Nursing and the project鈥檚 principal investigator, will work with an intradisciplinary team of experts to roll out a large-scale pilot in low-income, senior communities in Central Florida of an fall assessment intervention they鈥檝e developed and tested.

鈥淭he primary goal is to prevent falls,鈥� Thiamwong says. 鈥淲ith this real-world testing, we hope to be able to prove it works and is sustainable in order to scale up and prevent falls in more communities.鈥�

The researchers鈥� Physio-Feedback and Exercise, or PEER, intervention program was successfully tested as part of an NIH-funded . Their work has also been published in Research in Gerontological Nursing.

The researchers showed that their intervention, which uses technology to help reduce people鈥檚 fear of falling and improve their balance, was feasible, safe, and improved balance, muscle strength and fall risk.

The technology resembles a small scale and links to a computer. It can be easily transported to rural or low-income communities to provide immediate physio-feedback.

The immediate part is important, Thiamwong says.

鈥淥lder adults trust the results more when it is immediate,鈥� she says. 鈥淚t begins a conversation and empowers them to do something about it, and with the technology able to show improvement over time, it is also encouraging.鈥�

Perception versus Reality

For more than half of older adults, their perception of their fall risk and actual physical fall risk are not aligned, Thiamwong says.

She says a fear of falling is just as risky as poor balance as it may limit their physical activity.

To address this, the researchers鈥� intervention includes a fall risk appraisal matrix that categorizes participants into quadrants looking at both their fear and balance.

The objective is to bring all participants to low fear and normal balance by the end of the eight-week intervention.

The program includes cognitive reframing to reduce fear and both a group- and home-based exercise program led by a trained peer coach to improve balance.

鈥淪ocial support from peers is important to build connections and hopefully continue to keep the physical activity going even after the intervention,鈥� Thiamwong says.

Critical Collaboration

The researchers say collaboration with an interdisciplinary team is critical to address older adults falling and other healthcare challenges.

Thiamwong 聽began her collaborations with the one of the聽 project鈥檚 co-investigators, , after seeing some of his publications on aging research shortly after she joined 麻豆映画传媒.

Stout, who is director of the college鈥檚 , says the collaborations have developed into a research partnership that has been very successful.

鈥淭here is a聽great聽potential for collaboration between programs and faculty expertise in different colleges at 麻豆映画传媒,鈥� Stout says. 鈥淚nterdisciplinary collaboration is important because it allows different fields to share knowledge and ideas, which can lead to new breakthroughs.鈥�

One of the ways 麻豆映画传媒 fosters interdisciplinary collaboration is through research clusters, such as the Disability, Aging and Technology cluster that Thiamwong and project co-investigator Joon-Hyuk Park, an assistant professor in the , are a part of. The team has been successful in conducting NIH- and 麻豆映画传媒-funded studies.

鈥淭he cluster is an excellent facilitator to promote interdisciplinary research,鈥� Park says. 鈥淭he most challenging questions we, as researchers and scientists, seek to address these days can鈥檛 be tackled from one discipline, especially when it comes to human science to understand human behavior and study instrumentations. We need expertise from various fields.鈥�

, an assistant professor of and project co-investigator, says that many factors influence older adults’ fall risk, including physical health, socioeconomic status, as well as psychological motivations and feelings.

鈥淚n addition, if you want to launch a fall-risk intervention that involves technology, you have to consider factors like older adults’ ability to use the technology and cost effectiveness,鈥� she says.

鈥淚t’s easy to see how problems like this require a team of experts that understand each factor and know how to conduct science across traditional disciplinary boundaries,鈥� she says. 鈥淚t’s a truly excellent team and an important problem we are trying to solve.鈥�

Research Team

Thiamwong received her doctoral degree in nursing from Mahidol University in Thailand.

She joined 麻豆映画传媒 in 2016. She鈥檚 an expert in healthy aging, fall prevention and gerontological nursing. She is leading a 麻豆映画传媒 research team in implementing preventive interventions to transform practice, especially for older adults with limited resources.

Stout received his doctorate in exercise physiology from the University of Nebraska 鈥� Lincoln. He joined 麻豆映画传媒 in 2012. He鈥檚 an expert in physical assessments, such as body composition, handgrip strength and physical activity in aging populations, and he has published several studies examining the relationship between psychological and physical variables and the risk of falling.

Park received his doctorate in mechanical engineering from Columbia University. He joined 麻豆映画传媒 in 2019. He鈥檚 an expert in engineering wearable sensors and assistive technologies. His role in the project is to apply his knowledge and experience in wearables-based physical activity monitoring and assessment.

Rui Xie is an assistant professor in the , which is in 麻豆映画传媒鈥檚 . He received his doctorate in statistics from the University of Georgia. He joined 麻豆映画传媒 in 2019.聽 Xie is an expert in designing study designs that are appropriate for collecting data, while minimizing the risk of bias and ensuring the validity of the results, as well as data analysis and result interpretation.

鈥淚 was inspired to join this research team because I was fascinated by the multidimensional and multidomain data the team plans to collect in the project,鈥� Xie says. 鈥淚 felt that my skills and experience in data analysis and modeling could be of great value to the research.鈥�

Lighthall received her doctorate in gerontology from the University of Southern California. She joined 麻豆映画传媒 in 2015. She鈥檚 an expert in cognition and emotion across the adult lifespan, with a specific focus on age-related changes to decision processing and behavior. She is helping to determine the cognitive and motivational factors that impact older adults鈥� fear of falling by guiding the team鈥檚 measurement of these psychological factors.

a Beat M. and Jill L. Kahli Endowed Professor in Oncology and an associate professor in 麻豆映画传媒’s College of Nursing, received her doctorate in nursing from 麻豆映画传媒. She joined 麻豆映画传媒 in 2005. She鈥檚 an expert in qualitative research and randomized clinical trials, aging populations, and health disparities, with experience in technology-based intervention development and testing.

鈥淚nterdisciplinary collaboration is important because one person cannot know it all or do it all,鈥� she says. 鈥淵ou need the different perspectives and experiences from other disciplines to make your own work more complete and more relevant.聽Without the teamwork of experts from different disciplines, your work and ideas will get stale very quickly.鈥�

That鈥檚 why researchers are exploring alternative methods, such as neural stimulation, in which tiny electrical pulses are sent to a specific brain region to alleviate symptoms of neurological and neuropsychiatric disorders.

In a new study appearing in Nature Biomedical Engineering, researchers showed they can predict the effect of these stimulations across multiple brain regions, thus paving the way for personalized treatments.

Electrical neural stimulation, also known as deep brain stimulation, is an established treatment method that uses electrodes implanted in the brain to send therapeutic, electrical impulses that affect brain activity. It is a commonly performed surgical treatment for Parkinson鈥檚 disease and has been researched as a treatment for depression, chronic pain and addiction.

However, the understanding of how multi-regional brain activity responds to electrical stimulation has been limited, says the study鈥檚 lead author, Yuxiao Yang, an assistant professor in 麻豆映画传媒鈥檚 Department of Electrical and Computer Engineering and a member of 麻豆映画传媒鈥檚 Disability, Aging and Technology faculty research cluster.

The researchers worked to overcome this limitation by designing a new electrical stimulation wave that maps brain activity. They also created machine-learning techniques that can track the effects of the stimulations on the pattern of brain activity.

The study is the first to predict multi-regional brain response to ongoing electrical stimulation and will help illuminate ways to improve and understand the effects of neural-stimulation treatments, Yang says.

鈥淥ur data-driven approach was able to resolve two standing challenges: first, predicting brain response to ongoing electrical stimulation, and second, doing so for brain activity collected from multiple brain regions,鈥� the researcher says.

鈥淏ringing the two features together has implication of developing personalized treatments that automatically adjust the electrical stimulation by the right amount through monitoring the real-time multi-regional brain response,鈥� he says.

The next steps for the researchers will be to further validate their findings.

Study co-authors were Maryam M. Shanechi and Omid G. Sani with the University of Southern California, and Bijan Pesaran, Shaoyu Qiao, J. Isaac Sedillo and Breonna Ferrentino with New York University.

Yang received his doctorate in electrical engineering from the University of Southern California and joined 麻豆映画传媒鈥檚 Department of Electrical and Computer Engineering, part of 麻豆映画传媒鈥檚 College of Engineering and Computer Science, in 2020. He also directs the NeuroControl Lab at 麻豆映画传媒.