Papers
2
Total Citations
135
H-Index
2
About
Michael To is a leading researcher at the intersection of neural engineering and soft robotics, specializing in brain-computer interfaces (BCI) and rehabilitation technologies. His most impactful work centers on developing assistive devices that restore hand function for post-stroke patients, particularly through the integration of non-invasive BCI control with soft robotic systems. To’s landmark 2022 study on an SSVEP-based BCI-controlled soft robotic glove, which has garnered over 100 citations, demonstrated a novel approach to neural rehabilitation by enabling patients to control a wearable glove using visual evoked potentials from the brain. This work represents a significant advance over traditional motor imagery-based BCIs, offering faster and more reliable control for hand rehabilitation. His earlier 2020 simulation analysis on pneumatic bellow actuators provided the foundational design framework for optimizing soft robotic gloves, achieving 34 citations and influencing subsequent device development. To’s contributions bridge the gap between neural decoding and practical rehabilitation engineering, offering new hope for functional recovery in stroke survivors. His research continues to push the boundaries of how brain signals can directly interface with soft, wearable robotics to restore motor function.
Research Focus
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Top Papers
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