A Non-Invasive Closed-Loop Myoelectric Prosthetic Hand Featuring Electrotactile Sensory Feedback
Guanyu Zhu, Yilong Dou, Qiong Wu, Qichuan Ding
AI summary
Problem
Current myoelectric prostheses lack sensory feedback, forcing users to rely on visual monitoring and high cognitive load, while existing non-invasive feedback methods struggle with real-time performance, EMG signal interference during stimulation, and limited information richness.
Approach
The system uses a muscle spindle-inspired algorithm to map real-time prosthetic angle and force data to four-channel electrical stimulation parameters, while employing a time-division blanking method to eliminate EMG interference during gesture recognition.
Key results
- Development of a muscle spindle-inspired multidimensional stimulation paradigm mapping finger kinematics and kinetics to frequency and amplitude.
- Implementation of a real-time closed-loop system with a time-division blanking method to successfully separate EMG acquisition from stimulation artifacts.
- Experimental validation with able-bodied and amputee users demonstrating accurate conveyance of prosthetic state information.
- Successful user discrimination of object size, length, shape, and stiffness using only electrotactile feedback.
Why it matters
This framework provides a safe, practical pathway to restore natural embodiment and improve daily utility for upper-limb amputees by bridging the critical gap between motor control and sensory perception.
Abstract
The absence of sensory feedback has been a criti- cal challenge for myoelectric prostheses in recent years. While electrotactile feedback has emerged as an effective non-invasive solution, significant challenges remain in simultaneously en- suring real-time performance, processing EMG signals under electrical stimulation interference, and transmitting richer sen- sory information. This study proposes a multidimensional bio- inspired electrical stimulation feedback paradigm, implemented on a self-developed closed-loop myoelectric prosthetic hand sys- tem with real-time interference avoidance capability. Utilizing the human cutaneous nervous system as the feedback pathway, our paradigm establishes diverse electrotactile patterns through real-time modulation of four-channel stimulation parameters (frequency and current intensity). Experimental results with both able-bodied participants and amputees demonstrate that the proposed paradigm can accurately convey prosthetic state information, enabling users to perceive object size, length, shape, and stiffness through the prosthetic hand. This feedback framework provides a viable sensory restoration solution for prosthetic applications.