MATEC Web Conf.
Volume 87, 2017The 9th International Unimas Stem Engineering Conference (ENCON 2016) “Innovative Solutions for Engineering and Technology Challenges”
|Number of page(s)||6|
|Published online||04 August 2017|
Development of Hand Grip Assistive Device Control System for Old People through Electromyography (EMG) Signal Acquisitions
1 Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, Malaysia
2 Department of Bioscience and Engineering, College of System Engineering and Science, Shibaura Institute of Technology, 3308570 Saitama, Japan
a Corresponding author: email@example.com
The hand grip assistive device is a glove to assist old people who suffer from hand weakness in their daily life activities. The device earlier control system only use simple on and off switch. This required old people to use both hand to activate the device. The new control system of the hand grip assistive device was developed to allow single hand operation for old people. New control system take advantages of electromyography (EMG) and flex sensor which was implemented to the device. It was programmed into active and semi-active mode operation. EMG sensors were placed on the forearm to capture EMG signal of Flexor Digitorum Profundus muscle to activate the device. Flex sensor was used to indicate the finger position and placed on top of the finger. The signal from both sensors then used to control the device. The new control system allowed single hand operation and designed to prevent user from over depended on the device by activating it through moving their fingers.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.