Ryan J. McKindles
MIT Lincoln Laboratory, Massachusetts Institute of Technology
Papers
2
Total Citations
41
H-Index
2
About
Ryan J. McKindles is a researcher at the forefront of biomechatronics and human-machine interaction, specializing in the neural control of movement and assistive robotics. His work focuses on developing non-invasive methods to estimate human joint dynamics, with a particular emphasis on ankle torque during locomotion. McKindles’ major contributions include pioneering the use of machine learning—specifically neural networks—to fuse electromyography (EMG) and accelerometry signals for real-time torque prediction. His most-cited paper (2021, 31 citations) demonstrates a novel approach to estimating ankle torques, offering a pathway to more intuitive control of wearable robotic devices like prostheses and exoskeletons. By enabling anticipatory robot control, his research bridges the gap between biological signals and mechanical actuation, with direct implications for rehabilitation and patient care. An earlier foundational work (2020, 10 citations) established the feasibility of using portable sensors outside costly lab settings, making clinical torque estimation more accessible. McKindles’ work is notable for its practical impact on therapy planning and assistive device design, positioning him as a key contributor to the future of adaptive, human-aware robotics.
Research Focus
Key Achievements
Top Papers
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