Andrew Mao

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About

Andrew Mao is a leading researcher at the intersection of wearable sensing, soft robotics, and human-machine interaction for rehabilitation. His work focuses on developing intuitive, non-invasive systems that can detect user intent during physical therapy, particularly for hand rehabilitation. Mao’s major contribution lies in pioneering the use of force myography (FMG) — a technique that measures muscle pressure rather than electrical activity — to control soft robotic gloves. His most cited work (35 citations) introduces a wearable FMG sensor band using force-sensitive resistors, paired with supervised learning classifiers to accurately decode a user’s intended hand movements. This approach offers a more robust and user-friendly alternative to traditional electromyography, enabling smoother, more natural control of assistive devices. By bridging the gap between biomechanical sensing and soft actuation, Mao’s research has significant implications for stroke recovery and motor rehabilitation. His work is widely recognized for its practical, patient-centered design, and continues to influence the development of smart, adaptive rehabilitation technologies that empower users through seamless, real-time intent detection.