학술논문

Using Different Features of Signal in EMG Signal Classification
Document Type
Conference
Source
2020 International Conference on Information Science and Communications Technologies (ICISCT) Information Science and Communications Technologies (ICISCT), 2020 International Conference on. :1-5 Nov, 2020
Subject
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Photonics and Electrooptics
Power, Energy and Industry Applications
Signal Processing and Analysis
Time-frequency analysis
Information science
Pattern classification
Electromyography
Communications technology
Indexes
Time-domain analysis
EMG
gesture control
MUAPs
Features
Time-domain
Frequency-domain
PSD
Classification
Language
Abstract
Separation of signal features is the separation of the necessary data by selecting the desired parts of the signal. In this research, a comparative analysis of the classification based on some significant time domain and frequency domain features of the EMG signal is presented. In our research, it became clear analyzed that in the individual and combination application of features in the time and frequency domains, the features in the time domain had a higher rate than the features in the frequency domain with their speed and accuracy.