Michael R. Dawson
Glenrose Rehabilitation Hospital, University of Alberta, Alberta Health Services
Papers
15
Total Citations
760
H-Index
8
About
Michael R. Dawson is a leading researcher in the field of prosthetics control, human-machine interaction, and assistive robotics, whose work has profoundly advanced the lives of upper-limb amputees. His research sits at the intersection of machine learning, myoelectric control, and sensory feedback, focusing on developing intelligent, adaptive systems that allow amputees to operate prosthetic limbs with greater ease and naturalness. Dawson's most influential contribution — his 2018 study on illusory movement perception (201 citations) — demonstrated how restoring kinesthetic feedback can dramatically improve prosthetic motor control. His pioneering application of actor-critic reinforcement learning to myoelectric devices (158 citations) opened new avenues for real-time, user-adaptive prosthesis training, while his work on targeted sensory reinnervation (145 citations) offered amputees a novel path to regaining functional hand sensation. Across multiple studies, Dawson has consistently tackled the fundamental challenge of mismatched control channels in human-machine systems, introducing dynamic switching algorithms and real-time machine learning frameworks that reduce cognitive burden on users. With hundreds of citations accumulated across a focused body of work, his contributions represent a cornerstone of modern intelligent prosthetics research.
Research Focus
Key Achievements
Top Papers
- 1Illusory movement perception improves motor control for prosthetic hands201 citations · 2018
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- 5Application of real-time machine learning to myoelectric prosthesis control62 citations · 2015
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- 7The Development of a Myoelectric Training Tool for Above-Elbow Amputees36 citations · 2012
- 8The Development of a Myoelectric Training Tool for Above-Elbow Amputees11 citations · 2012
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