The Development of an Interface Instrument for Collecting Electromyography Data and Controlling a Continuous Passive Motion Machine

Author:

Jastania Rayan12ORCID,Wang Peng13,Alqahtani Bijad4ORCID,Alzahrani Abdullah4,Wang Weijie1ORCID

Affiliation:

1. Institute of Motion Analysis and Research (IMAR), Department of Orthopaedic and Trauma Surgery, Tayside Orthopaedic and Rehabilitation Technology Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, UK

2. Department of Physical Therapy, Faculty of Medical Rehabilitation Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia

3. Intelligent Manufacture School, Tianjin Sino-German University of Applied Sciences, Tianjin 300350, China

4. Department of Rehabilitation Sciences, College of Applied Medical Sciences, Shaqra University, Riyadh 11961, Saudi Arabia

Abstract

There is a lack of research in using electromyography (EMG) signals to control a continuous passive motion (CPM) machine. This study aimed to develop an interface instrument for digitalising EMG signals and controlling a CPM machine. Methods: The proposed device was designed with the following: (1) a signal processing unit which converted the EMGs from analogue to digital for the controller; (2) a personal computer which stored and displayed the EMG signals; (3) an LCD device to display the running angle of the CPM; and (4) a microcontroller unit to control the input/output signals and process the algorithm, driving the CPM. To validate the reliability of the proposed system, a total of 600 EMG trials were collected from 10 healthy subjects by using the proposed device via the Delsys® TringoTM EMG system and simultaneously using the Vicon® motion capture system. Result: This proposed device was able to digitalise and process EMG signals from eight channels of muscles, and the signals were able to drive a CPM. The validated results showed that the digitalised EMG signals by the proposed device were statistically similar to and correlated with the signals by the Vicon system with a median correlation coefficient of 0.81, with the 25% and 75% range being 0.56–0.92 with all pairs (300 pairs of EMG trials) (p < 0.001). Conclusions: This study confirmed that the developed device can digitalise EMG signals and drive a CPM as an applicable prototype that can work as an interface between EMG and CPM devices with high reliability.

Funder

The University of Dundee the Library’s Institutional Open Access Fund

Economy Partnership KEP-058 of Pakistan–UK of British Council

King Abdulaziz University and the Government of Saudi Arabia

Chinese government

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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3. Almusawi, H., and Husi, G. (2021). Design and Development of Continuous Passive Motion (CPM) for Fingers and Wrist Grounded-Exoskeleton Rehabilitation System. Appl. Sci., 11.

4. Subba, T., and Chingtham, T.S. (2019). Advances in Communication, Cloud, and Big Data, Springer.

5. EMG signal classification for human computer interaction: A review;Ahsan;Eur. J. Sci. Res.,2009

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