About this Research Topic
In the dynamic landscape of human movement science, the convergence of cutting-edge technology with the intricacies of human physiology has ushered in a new era of transformative possibilities. This captivating research theme, encompassing the realms of neurorehabilitation, assistive robotics, human-machine interaction, and balance control, offers the exciting prospect of reshaping the boundaries of movement recovery. Translational research serves as the crucial conduit between scientific breakthroughs and tangible implementation, ensuring that the cutting-edge technologies birthed within laboratories seamlessly transition into real-world clinical applications.
Neurorehabilitation delves into neuroplasticity, unraveling the brain's adaptability for recovery. Advanced imaging and neurophysiology guide interventions, enabling rewiring of neural pathways in individuals with neurological injuries. Assistive robotics fuse human potential with sophisticated devices, aiding recovery through tailored support. These allies enhance muscle activation, joint movement, and gait training, driving functional independence. Human-machine interaction deciphers neural signals, blurring lines between humans and technology. A seamless collaboration empowers individuals to guide and benefit from technological assistance. Investigating balance control strategies is crucial for designing assistive robotics that revolutionize rehabilitation and mobility. By understanding users' perspectives, we uncover the intricate link between human thinking, neuromuscular coordination, and balance maintenance. This insight informs the development of user-centered robotics, enhancing natural movement patterns and enabling effective rehabilitation, ultimately restoring stability and confidence in mobility.
This Research Topic serves as a platform for the exploration of key mechanisms in human movement rehabilitation and enhancement, bridging physiological strategies and assistive device design. It showcases advanced algorithms and applications, mapping out theoretical and engineering directions for the future. Authors are invited to contribute research and review papers, presenting cutting-edge insights and applications in human movement rehabilitation and enhancement.
Potential topics include but are not limited to the following:
- Design and Control of Assistive Robotics
- Robot-Assisted Rehabilitation and Diagnostics
- Neurorehabilitation and Brain-Machine Interfaces
- Virtual Reality and Gamification for Rehabilitation
- Wearable Sensors and Feedback Systems
- Biomedical Signal Process (sEMG, EEG, ECG, etc.) and Biologically-Inspired Rehabilitation
- Biomechanics of Balance Control
- Data Analytics and Machine Learning in Rehabilitation
- Interdisciplinary Collaborations in Human Movement Science
- Integrations of visual cognition, decision making, and motion control.
- Machine Learning in medical records, clinical decision making, and virtual nursing assistants
- Machine Learning in medical device control
Neurorehabilitation delves into neuroplasticity, unraveling the brain's adaptability for recovery. Advanced imaging and neurophysiology guide interventions, enabling rewiring of neural pathways in individuals with neurological injuries. Assistive robotics fuse human potential with sophisticated devices, aiding recovery through tailored support. These allies enhance muscle activation, joint movement, and gait training, driving functional independence. Human-machine interaction deciphers neural signals, blurring lines between humans and technology. A seamless collaboration empowers individuals to guide and benefit from technological assistance. Investigating balance control strategies is crucial for designing assistive robotics that revolutionize rehabilitation and mobility. By understanding users' perspectives, we uncover the intricate link between human thinking, neuromuscular coordination, and balance maintenance. This insight informs the development of user-centered robotics, enhancing natural movement patterns and enabling effective rehabilitation, ultimately restoring stability and confidence in mobility.
This Research Topic serves as a platform for the exploration of key mechanisms in human movement rehabilitation and enhancement, bridging physiological strategies and assistive device design. It showcases advanced algorithms and applications, mapping out theoretical and engineering directions for the future. Authors are invited to contribute research and review papers, presenting cutting-edge insights and applications in human movement rehabilitation and enhancement.
Potential topics include but are not limited to the following:
- Design and Control of Assistive Robotics
- Robot-Assisted Rehabilitation and Diagnostics
- Neurorehabilitation and Brain-Machine Interfaces
- Virtual Reality and Gamification for Rehabilitation
- Wearable Sensors and Feedback Systems
- Biomedical Signal Process (sEMG, EEG, ECG, etc.) and Biologically-Inspired Rehabilitation
- Biomechanics of Balance Control
- Data Analytics and Machine Learning in Rehabilitation
- Interdisciplinary Collaborations in Human Movement Science
- Integrations of visual cognition, decision making, and motion control.
- Machine Learning in medical records, clinical decision making, and virtual nursing assistants
- Machine Learning in medical device control
Keywords: Neurorehabilitation, Assistive robotics, Human-machine interaction, Balance control, Movement recovery
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
