Development of a Wireless Surface Electromyography (sEMG) Signal Acquisition Device for Power-Assisted Wheelchair System
M. H. Muhammad Sidik1, S.A. Che Ghani2, Mahfodzah M Padzi3

1M. H. Muhammad Sidik, Mechanical Engineering Section, University Kuala Lumpur MFI (Unikl MFI), Bandar Baru Bangi, Malaysia.
2S.A. Che Ghani, Faculty of Mechanical Engineering, University Malaysia Pahang, Pekan, Pahang, Malaysia.
3Mahfodzah M Padzi, Mechanical Engineering Section, University Kuala Lumpur MFI (Unikl MFI), Bandar Baru Bangi, Malaysia
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 103-105 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9511088619/2019©BEIESP | DOI: 10.35940/ijeat.F9511.088619
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Abstract: Muscle fatigue due to long-term of manual wheelchair propulsion is an issue faced by most of users. A power-assisted wheelchair developed to amplify propulsion force that activated by surface electromyography (sEMG). A sEMG detection wireless device to trigger the assistive system is an advantage to ease installation on user’s body and wheelchair which is developed in this study. A device that operated on Arduino Nano processor connected to 2 (two) Myoware sEMG sensors to record muscles electrical potential (EP), recognise the pattern and activate DC motors wirelessly connected through radio frequency. Data monitoring on personal computer and smart phone associated with Bluetooth to store and ease observation on recorded information. Tested on 1 healthy participant by propelling a manual wheelchair on tiled floor. Developed device’s performance tested and the result are average sampling rate (33.55 ms) and average reading latency was just 12.38 ms. Compared to wired device, sampling rate is faster by % and reading latency slower by 1.04 %. Result demonstrate that developed wireless device would improve in speed in signal reading and enhancement on reading latency is needed to provide a reliable device for power-assisted system in the future.
Keywords: Surface Electromyography, Radio Frequency, Bluetooth, Arduino, Electrical Potential