TY  - JOUR
T1  - Intelligent System for Electromyography (EMG) Signals Classification
AU - Khaleel Awsaj, Mahmood AU - Nory Farhan, Rabah 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 5
SP  - 1564
EP  - 1570
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.1564.1570
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.1564.1570
KW  - EMG signal
KW  -muscular disease
KW  -signal processing
KW  -DWT
KW  -SVM
KW  -extraction
AB  - Muscles in the hands of the human are one of the important parts that depend on the performance
of hand dutiest hrough movement which helps the man in the performance of daily functions which carry things
and touch and feel everything around him. Muscle signals extracted by EMG system are used to diagnose
muscle signals and classify them as normal or abnormal. The process of detecting and classifying EMG signals
are difficult and exhausting process and require effort by the specialist doctor to diagnose them. Muscle injury
treatment is complicated and require surgical intervention when the injury is severe but when early detection
of injury may be treated without surgical intervention. In this study will use the EMG signalsthat have been
collected as data. At the beginning extracting, the signals by tracking each signal. These signals are then
analyze dusing DWT for muscle bands extraction that is used in feature extraction and using SVM for
classification. DWT used for tofeature extraction.
ER  -