A frequency and pulse-width co-modulation strategy for transcutaneous neuromuscular electrical stimulation based on sEMG time-domain features

Significance Statement

Neuromuscular electrical stimulation (NMES) is commonly used in clinical settings to enhance motor function rehabilitation of paralyzed individuals following stroke, traumatic brain injury, multiple sclerosis, cerebral palsy, or spinal cord injury. Among the neuromuscular electrical stimulation control methods, surface electromyography (sEMG) is often used to control the stimulation patterns. For neuromuscular electrical stimulation, three parameters, i.e., the pulse amplitude, the pulse width, and the frequency, can be altered to control the force output. However, existing EMG-controlled neuromuscular electrical stimulation systems often control the stimulation amplitude using EMG amplitude-based time-domain (TD) features, and therefore are only able to modulate the number of recruited motor units (MUs). In contrast, during voluntary contractions, the central nervous system (CNS) controls muscle force by modulating both the number of activated MUs (recruitment coding) and the activation frequency (rate coding). For traditional sEMG-controlled neuromuscular electrical stimulation, their non-physiological recruitment order and inability to alter recruitment patterns and modulate firing frequency result in increased energy demand for a given task and rapid onset of muscle fatigue.

The present work demonstrates that a pulse width and frequency co-modulation stimulation strategy based on sEMG TD features (MAV/NSS dual-coding (MNDC) algorithm) exhibited a better voluntary force reproduction and stronger fatigue resistance than the traditional sEMG proportional control strategy when the same pulse width modulation range and a similar average total charge were utilized in both strategies. The MNDC strategy tended to use a longer average pulse width and a lower stimulation frequency to recruit more muscle MUs with relatively lower firing rates, which could reduce the metabolic demand on each MU. Due to the simplicity of the transfer functions designed to map the sEMG activity into stimulation patterns, the MNDC strategy can be effectively used in real-time sEMG-controlled neuromuscular electrical stimulation systems and may help to extend the duration of sEMG-controlled FES applications.

Figure Legend: (a) The flowchart for constructing the MNDC strategy; (b) the wrist torque reproduction comparison for different strategies; (c) and the fatigue resistance comparison.

A frequency and pulse-width co-modulation strategy for transcutaneous neuromuscular electrical stimulation based on sEMG time-domain features. Advances in Engineering

About the author

Xiao-Ying Lü was born in Shanghai, China. She received her M.-Med. degree from Shanghai Second Medical University in 1986 and her Dr.-Dent. degree from Freiburg University, Freiburg, Germany, in 1996.

She worked at the 9th Hospital Affiliated to Shanghai Second Medical University as a dentist from 1981 to 1982, and as a researcher from 1982 to 1986. Dr. Lü performed postdoctoral research at Freiburg University from 1996 to 1997. She joined Southeast University, China, as an associate professor of biomedical engineering in 1997, and was appointed professor since 2003.

She has published more than 270 papers, and got 23 Chinese patents and one PCT patent. Her research interests include biocompatibility evaluation and mechanism research on biomaterials, neuron-electronic chip, and implanted bio-electronic devices. 

 

About the author

Zhi-Gong Wang was born in Henan, China. He received the M.-Eng. degree in radio engineering from Nanjing Institute of Technology (now, Southeast University), Nanjing, China, in 1981, and the Dr.-Ing. degree in electronic engineering from Ruhr University, Bochum, Germany, in 1990.

From 1977 to 1981, he worked on radio communication technologies and computer aided circuit designs at Nanjing Institute of Technology. From 1985 to 1990, he worked on high-speed silicon bipolar circuit designs for multi-gigabit/s optic fiber communication at Ruhr University. From 1990 to 1997, he was with the Fraunhofer Institute of Applied Solid State Physics, Freiburg, Germany, working on high-speed GaAs ICs for optic-fiber data transmission and MMICs. Dr. Wang joined Southeast University, Nanjing, China, as a full professor of electrical engineering in Oct. 1997.

He is the author or co-author of 20+ books, 500+ SCI/EI/ISTP-indexed publications, and inventor of 40+ patents in China, Germany, Europe, USA, and Japan.

He is guest professor at 20+ universities in China, Canada, and Australian.

Recently, he is involved in IC design for optic-fiber transmission systems, for RF wireless, microwave, and millimeter-wave applications, and in micro-electronic systems for biomedical applications. 

 

About the author

Yu-Xuan Zhou received the B.S. degree in mechanical engineering and automation from Nanjing University of Science and Technology, Nanjing, China, in 2007, and the M.S. degree in biomedical engineering from Nanjing Medical University, Nanjing, China, in 2010. He is currently working towards his Ph.D. degree in biomedical engineering at the Southeast University, Nanjing, China.

His research interests include biomedical signal processing, neural prostheses system design, and rehabilitation engineering. 

 

Journal Reference

Journal of Neural Engineering, Volume 13, Number 1. (2016)

Yu-Xuan Zhou1, Hai-Peng Wang2, Xue-Liang Bao1, Xiao-Ying Lü1,3 and Zhi-Gong Wang2,3

Show Affiliations
  1. State Key Lab of Bioelectronics, Southeast University, 210096 Nanjing, People’s Republic of China
  2. Institute of RF- & OE-ICs, Southeast University, 210096 Nanjing, People’s Republic of China
  3. Co-innovation Center of Neuroregeneration, Nantong University, 226001 Nantong, People’s Republic of China

Abstract

Objective. Surface electromyography (sEMG) is often used as a control signal in neuromuscular electrical stimulation (NMES) systems to enhance the voluntary control and proprioceptive sensory feedback of paralyzed patients. Most sEMG-controlled neuromuscular electrical stimulation systems use the envelope of the sEMG signal to modulate the stimulation intensity (current amplitude or pulse width) with a constant frequency. The aims of this study were to develop a strategy that co-modulates frequency and pulse width based on features of the sEMG signal and to investigate the torque-reproduction performance and the level of fatigue resistance achieved with our strategy.

Approach. We examined the relationships between wrist torque and two stimulation parameters (frequency and pulse width) and between wrist torque and two sEMG time-domain features (mean absolute value (MAV) and number of slope sign changes (NSS)) in eight healthy volunteers. By using wrist torque as an intermediate variable, customized and generalized transfer functions were constructed to convert the two features of the sEMG signal into the two stimulation parameters, thereby establishing a MAV/NSS dual-coding (MNDC) algorithm. Wrist torque reproduction performance was assessed by comparing the torque generated by the algorithms with that originally recorded during voluntary contractions. Muscle fatigue was assessed by measuring the decline percentage of the peak torque and by comparing the torque time integral of the response to test stimulation trains before and after fatigue sessions.

Main Results. The MNDC approach could produce a wrist torque that closely matched the voluntary wrist torque. In addition, a smaller decay in the wrist torque was observed after the MNDC-coded fatigue stimulation was applied than after stimulation using pulse-width modulation alone.

Significance. Compared with pulse-width modulation stimulation strategies that are based on sEMG detection, the MNDC strategy is more effective for both voluntary muscle force reproduction and muscle fatigue reduction.

Published 8 December 2015 • © 2016 IOP Publishing Ltd

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