Design of Multi-channel Electrical Stimulator Integrated with Online Impedance Measurement
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ORIGINAL ARTICLE
Design of Multi‑channel Electrical Stimulator Integrated with Online Impedance Measurement Dapeng Yang1,2 · Qi Huang3 · Zainan Jiang1 · Li Jiang1 Received: 26 July 2020 / Accepted: 24 September 2020 © Taiwanese Society of Biomedical Engineering 2020
Abstract Purpose An intuitive perception about the hand is essentially important for a prosthesis user. However, it is not well addressed in current bidirectional human–machine interface (HMI) design due to various electrode–skin conditions. Herein, we intend to propose a multi-channel transcutaneous nerve electrical stimulator (TNES) with online skin-impedance measurement. Methods Using non-woven electrode and flexible printed circuit (FPC) electrode, the time-varying behavior of the skin impedance is explored and the linear relationship between sensory threshold and skin impedance is verified. An online approach on adjusting the stimulus parameters is also proposed on basis of the real-time impedance measurement. Results Experiments show that this method can adaptively adjust the stimulation intensity in line with the changing impedance, which improves the safety and applicability of the electrical stimulation feedback system. Conclusion As the stimulator measures the impedance between the skin and the electrode in real time, it can achieve a progressive electrotactile sensory feedback at different body locations. Keywords Electrical stimulation · Electrotactile feedback · Impedance measurement
1 Introduction Although the dexterity of commercial prosthesis has made great progress [1], its clumsy control and sensory loss still make many amputees unwilling to use [2, 3]. Restoring the nature feeling of the prosthetic hand enables patients to use it as part of the body, rather than a simple tool, which plays an important role in improving the acceptance rate of the prosthetic system [4, 5]. The development of a bidirectional human–machine interface with reliable control and rich sensing capabilities to promote the recovery of patient’s proprioception has become the key to the successful application of the prosthesis. * Qi Huang [email protected] * Li Jiang [email protected] 1
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China
2
Artificial Intelligence Laboratory, Harbin Institute of Technology, Harbin 150080, China
3
Zhejiang Brain-Enhance Technology Co. LTD, Hangzhou 311100, China
Currently, there are two technical routes to implement a human–machine interface: invasive and non-invasive. Due to the higher security, reliability, and ease of use, non-invasive human–machine interface is favored by researchers and commercial organizations. According to the human body’s response to sensory information, the smart prosthetic sensory feedback system can be divided into three categories, namely Nerve Remapping, Modality Matched Feedback and Sensory Substitution Feedback (SSF) [6]. Among them, the SSF is more flexible as it can transmit sensor information from the prosthetic hand to the
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