Surface EMG electrode distribution for thumb motion classification based on wireless communication equipment Online publication date: Fri, 12-Apr-2019
by Wanfen Xu; Gongfa Li; Zhaojie Ju; Honghai Liu
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 16, No. 2, 2019
Abstract: The interaction between humans and computers has become more necessary and more specific. Thumb as the most important finger plays a decisive role in decoding the gesture, especially in controlling smart phones and many other smart devices, etc. As a result, this study aims to decode the different thumb gestures from sEMG signal and to improve the robustness of gesture recognition and decrease the influence of physiological conditions and the electrode displacement between different users. In this paper, we use the Bluetooth wireless communication and focus on the relationship between the EMG signal and the electrode identifier number. We change the electrode's number into a new feature, and combining the traditional features with the new features to verify the electrode's number has a correlation with the thumb gesture. Experiments show that after adding new features, the gesture recognition rate has increased.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook