Artificial Intelligence

   

Automated Classification of Hand-Grip Action on Objects Using Machine Learning

Authors: Anju Mishra, Amity University Uttar Pradesh SHANU SHARMA, Amity University Uttar Pradesh SANJAY KUMAR, Oxford Brooks University PRIYA RANJAN, Amity University Uttar Pradesh AMIT UJLAYAN, Gautam Buddha University

Brain computer interface is the current area of research to provide assistance to disabled persons. To cope up with the growing needs of BCI applications, this paper presents an automated classification scheme for handgrip actions on objects by using Electroencephalography (EEG) data. The presented approach focuses on investigation of classifying correct and incorrect handgrip responses for objects by using EEG recorded patterns. The method starts with preprocessing of data, followed by extraction of relevant features from the epoch data in the form of discrete wavelet transform (DWT), and entropy measures. After computing feature vectors, artificial neural network classifiers used to classify the patterns into correct and incorrect handgrips on different objects. The proposed method was tested on real dataset, which contains EEG recordings from 14 persons. The results showed that the proposed approach is effective and may be useful to develop a variety of BCI based devices to control hand movements. KEYWORDS EEG, Brain computer interface, Machine learning, Hand action recognition

Comments: 10 Pages. This is a preprint of a paper under possible publication consideration.

Download: PDF

Submission history

[v1] 2018-04-06 04:33:26

Unique-IP document downloads: 20 times

Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus