Surface EMG classification for prosthesis control: fuzzy logic vs. artificial neural network
Electromyography control system (ECS) is a well-known technique for prosthesis control application. It consists of two main modules namely feature extraction and classification. This paper presents the investigation of the classification module in the ECS. The surface electromyographic (EMG) signal...
Main Authors: | Ahmad, Siti Anom, Khalid, Mohd Asyraf, Ishak, Asnor Juraiza, Md. Ali, Sawal Hamid |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
SciTePress
2012
|
Online Access: | http://psasir.upm.edu.my/id/eprint/31662/1/31662.pdf |
Similar Items
-
Review of electromyography control systems based on pattern recognition for prosthesis control application
by: Ahmad, Siti Anom, et al.
Published: (2011) -
Developing multichannel surface EMG acquisition system by using instrument opamp INA2141
by: Ghapanchizadeh, Hossein, et al.
Published: (2014) -
Investigate the transcendent adapted of wavelet threshold algorithms for elbow movement by surface EMG signal
by: Ghapanchizadeh, Hossein, et al.
Published: (2014) -
Impact of feature extraction techniques on classification accuracy for EMG based ankle joint movements
by: Al-Quraishi, Maged Saleh Saeed, et al.
Published: (2015) -
Simple and computationally efficient movement classification approach for EMG-controlled prosthetic hand: ANFIS vs. artificial neural network
by: Fariman, Hessam Jahani, et al.
Published: (2015)