NDLI: A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair

Content Provider	Springer Nature Link
Author	Kaiser, M. Shamim Chowdhury, Zamshed Iqbal Mamun, Shamim Al Hussain, Amir Mahmud, Mufti
Copyright Year	2016
Abstract	This paper presents the design and implementation of a low-cost solar-powered wheelchair for physically challenged people. The signals necessary to maneuver the wheelchair are acquired from different muscles of the hand using surface electromyography (sEMG) technique. The raw sEMG signals are collected from the upper limb muscles which are then processed, characterized, and classified to extract necessary features for the generation of control signals to be used for the automated movement of the wheelchair. An artificial neural network-based classifier is constructed to classify the patterns and features extracted from the raw sEMG signals. The classification accuracy of the extracted parameters from the sEMG signals is found to be relatively high in comparison with the existing methods. The extracted parameters used to generate control signals that are then fed into a microcomputer-based control system (MiCS). A solar-powered wheelchair prototype is developed, and the above MiCS is introduced to control its maneuver using the sEMG signals. The prototype is then thoroughly tested with sEMG signals from patients of different age groups. Also, the life cycle cost analysis of the proposed wheelchair revealed that it is financially feasible and cost-effective.
Starting Page	946
Ending Page	954
Page Count	9
File Format	PDF
ISSN	18669956
Journal	Cognitive Computation
Volume Number	8
Issue Number	5
e-ISSN	18669964
Language	English
Publisher	Springer US
Publisher Date	2016-03-24
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Surface EMG signals Rehabilitation Neuro-fuzzy system Solar-powered wheelchair Wheelchair navigation Neurosciences Computation by Abstract Devices Artificial Intelligence (incl. Robotics) Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Cognitive Neuroscience Computer Science Applications Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

On pattern classification of EMG signals for walking motions

Development of the electric wheelchair hands-free semi-automatic control system using the surface-electromyogram of facial muscles

Discriminative Lasso

Cognitive Computation: An Introduction

An Interactive Fuzzy Inference System for Teletherapy of Older People

Sentic Computing

Actor-Critic Learning for Platform-Independent Robot Navigation

Computational Creativity, Intelligence and Autonomy

A Perceptual Visual Feature Extraction Method Achieved by Imitating V1 and V4 of the Human Visual System

A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair

Similar Documents

On pattern classification of EMG signals for walking motions

Development of the electric wheelchair hands-free semi-automatic control system using the surface-electromyogram of facial muscles

Discriminative Lasso

Cognitive Computation: An Introduction

An Interactive Fuzzy Inference System for Teletherapy of Older People

Sentic Computing

Actor-Critic Learning for Platform-Independent Robot Navigation

Computational Creativity, Intelligence and Autonomy

A Perceptual Visual Feature Extraction Method Achieved by Imitating V1 and V4 of the Human Visual System

A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair