Papers
22
Total Citations
358
H-Index
10
About
Jingeng Mai is a prominent robotics and biomedical engineering researcher whose work sits at the intersection of wearable robotics, human-robot interaction, and assistive technology for individuals with physical disabilities. His research has made significant contributions to the design and intelligent control of robotic prostheses and exoskeletons, with a particular focus on enabling seamless, real-time human locomotion recognition. His landmark 2018 paper on continuous locomotion mode recognition for transtibial prostheses (65 citations) demonstrated a sophisticated cascaded classification strategy capable of identifying six locomotion modes and ten transitions, a critical advance in prosthetic control. Mai has further broadened the field through innovations in energy regeneration for wearable devices, developing self-charging robotic prostheses that harvest mechanical energy during walking (34 citations), and pioneering bioinspired cable-driven actuation systems that mimic natural muscle activation patterns (30 citations). His work extends to stroke rehabilitation, IMU-based gait recognition, and trunk support robotics, reflecting a holistic approach to assistive device development. With over 297 cumulative citations across ten highly regarded publications, Mai's research meaningfully advances the autonomy, efficiency, and clinical applicability of next-generation wearable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Controlling a Robotic Hip Exoskeleton With Noncontact Capacitive Sensors37 citations · 2019
- 3Skill learning framework for human–robot interaction and manipulation tasks36 citations · 2022
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- 7IMU-Based Gait Phase Recognition for Stroke Survivors24 citations · 2019
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