Author

Jun Leng

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Preprint Oct 2026

A Flow-Theoretic Multimodal Control Framework Fusing Mental and Physical Engagement for Upper-Limb Rehabilitation

While Assist-as-Needed (AAN) control aims to maximize user participation in robot-assisted training, existing methods relying solely on physical metrics cannot distinguish muscular inability from mental disengagement, leading to suboptimal interventions. To address this ambiguity, a Flow-theoretic multimodal AAN framew...

Jun Leng, Peng-Cheng Li, Han-Ze Wang et al. · 0 citations

Conference Aug 2026

FAST-TCN: A Frequency-Aware Spatio-Temporal Network for sEMG-Based Continuous Motion Prediction in Upper Limb Rehabilitation Robotics

Practical sEMG-based motion prediction for rehabilitation robotics faces two critical challenges: low robustness caused by inter-subject variability and signal non-stationarity, and mechanical safety hazards due to jittery control signals. Conventional Temporal Convolutional Network(TCN)-based methods often prioritize...

Junlin Jiang, Pengcheng Li, Jun Leng et al. · 2026 IEEE International Conf... · 0 citations

Conference Aug 2026

A Composite Variable Impedance Control Architecture with Adaptive Feedforward Assistance for Rehabilitation Exoskeletons

Home-based rehabilitation exoskeletons often suffer from control instability due to low-cost force sensors. This paper presents a robust, sensorless Composite Variable Impedance Control architecture that separates trajectory tracking (virtual stiffness K) from active assistance (adaptive feedforward torque τassist). By...

Jun Leng, Pengcheng Li, Hanze Wang et al. · 2026 IEEE International Conf... · 0 citations