Surface electromyography (SEMG) normalization method based on pre fatigue maximal voluntary contraction
Surface electromyography (sEMG) pattern recognition task requires high accuracy classification. However, current technology suffers from two main problems. The first problem is inconsistent pattern due to fatigue while the second is robustness of sEMG features due to low signal to noise ratio, SNR....
Saved in:
Main Author: | Mohd Sabri, Muhammad Ihsan |
---|---|
Format: | Thesis |
Language: | English English |
Published: |
2017
|
Subjects: | |
Online Access: | http://eprints.utem.edu.my/id/eprint/20616/1/Surface%20Electromyography%20%28SEMG%29%20Normalization%20Method%20Based%20On%20Pre%20Fatigue%20Maximal%20Voluntary%20Contraction.pdf http://eprints.utem.edu.my/id/eprint/20616/2/Surface%20electromyography%20%28SEMG%29%20normalization%20method%20based%20on%20pre%20fatigue%20maximal%20voluntary%20contraction.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
by: Too, Jing Wei
Published: (2020) -
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
by: Mohd Hanafi, Muhammad Sidik
Published: (2020) -
Temporal spectral approach to surface electromyography based fatigue classification of biceps brachii during dynamic contraction
by: Kamaruddin, Nurul Asyikin
Published: (2016) -
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
by: Burhan, Nuradebah
Published: (2018) -
Electromyography (EMG) Signal Analysis For Manual lifting Using Time-Frequency Distribution
by: Tengku Zawawi, Tengku Nor Shuhada
Published: (2016)