Title: "Non-invasive Brain Stimulation on Motor and Cognitive Function facilitation: Research from Our Lab"
Abstract: In this seminar, we develop the latest advancements in training facilities for rehabilitation, focusing on soft robotics, motion analysis and balance. Our team is currently developing a novel AR-based Bilateral Treadmill Training System, which we believe will be of great interest to the sports science community. Our system features several innovative components, including a markerless and real-time motion capture system that allows for precise motion analysis without the need for markers. The bilateral belt treadmill supports different speed ratios between belts, enabling varied training scenarios. Additionally, the Femto Mega depth sensor camera requires only one or two cameras for the entire training system, enhancing efficiency. The markerless gait analysis is applicable to any treadmill with embedded force sensors, providing comprehensive gait analysis. Real-time monitoring and visual feedback offer immediate biomechanical feedback to athletes, while comprehensive gait pattern analysis includes both kinematic and kinetic data for detailed assessments. Motor and balance control assessments evaluate athletes’ motor skills and balance.
We see significant potential for applying this system in rehabiliation training. The bilateral belt design allows for a range of speeds and sudden movements, making it suitable for various training intensities. Our preliminary data from stroke rehabilitation training demonstrates immediate training effects and improvements in balance with soft robotic training, as evidenced by changes in the center of pressure (COP) after ten sessions. Bio: Prof. Raymond Kai-Yu TONG, a Professor in the Department of Biomedical Engineering at the Chinese University of Hong Kong (CUHK). His commitment to fostering creativity and engagement among students has resulted in numerous accolades, including the Best Teacher Award in 2021 and University Education Award 2022 (Highest Teaching Honours in CUHK) recognition as one of the Top 10 Global Ageing Influencers (recognized by the industry and Ageing Asia at the World Ageing Festival in Singapore), the Fellow of the American Institute for Medical and Biological Engineering (AIMBE) College in 2022 and Awardee of the 2013 Ten Outstanding Young Persons, Hong Kong. He has successfully established Hong Kong's first Biomedical Engineering Department in 2017. His research interests include Motion Analysis (e.g. AR Rehabilitation, Hope4Care), Rehabilitation Robotics (e.g. Hand of Hope), Soft Robotics (Hopebotics, XoMuscle), Brain-Computer Control Interface (BCI), Stroke Rehabilitation, Wearable Sensors, AI in medical imaging, Functional Electrical Stimulation(FES) and Cognitive Assessment Software.
Title: Exploring Advanced Training Facilities for Stroke Rehabilitation: Soft Robotics, Motion Analysis and Bilateral Treadmill Design
Abstract: In this seminar, we develop the latest advancements in training facilities for rehabilitation, focusing on soft robotics, motion analysis and balance. Our team is currently developing a novel AR-based Bilateral Treadmill Training System, which we believe will be of great interest to the sports science community. Our system features several innovative components, including a markerless and real-time motion capture system that allows for precise motion analysis without the need for markers. The bilateral belt treadmill supports different speed ratios between belts, enabling varied training scenarios. Additionally, the Femto Mega depth sensor camera requires only one or two cameras for the entire training system, enhancing efficiency. The markerless gait analysis is applicable to any treadmill with embedded force sensors, providing comprehensive gait analysis. Real-time monitoring and visual feedback offer immediate biomechanical feedback to athletes, while comprehensive gait pattern analysis includes both kinematic and kinetic data for detailed assessments. Motor and balance control assessments evaluate athletes’ motor skills and balance.
We see significant potential for applying this system in rehabiliation training. The bilateral belt design allows for a range of speeds and sudden movements, making it suitable for various training intensities. Our preliminary data from stroke rehabilitation training demonstrates immediate training effects and improvements in balance with soft robotic training, as evidenced by changes in the center of pressure (COP) after ten sessions. Bio: Prof. Raymond Kai-Yu TONG, a Professor in the Department of Biomedical Engineering at the Chinese University of Hong Kong (CUHK). His commitment to fostering creativity and engagement among students has resulted in numerous accolades, including the Best Teacher Award in 2021 and University Education Award 2022 (Highest Teaching Honours in CUHK) recognition as one of the Top 10 Global Ageing Influencers (recognized by the industry and Ageing Asia at the World Ageing Festival in Singapore), the Fellow of the American Institute for Medical and Biological Engineering (AIMBE) College in 2022 and Awardee of the 2013 Ten Outstanding Young Persons, Hong Kong. He has successfully established Hong Kong's first Biomedical Engineering Department in 2017. His research interests include Motion Analysis (e.g. AR Rehabilitation, Hope4Care), Rehabilitation Robotics (e.g. Hand of Hope), Soft Robotics (Hopebotics, XoMuscle), Brain-Computer Control Interface (BCI), Stroke Rehabilitation, Wearable Sensors, AI in medical imaging, Functional Electrical Stimulation(FES) and Cognitive Assessment Software.
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