DOIONLINE 
DOIONLINE Publish In |
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC |
 Journal Home Volume Issue |
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Issue |
Volume-8,Issue-9 ( Sep, 2020 ) | |||||||||
Paper Title |
Pain Intensity Estimation using EMG Signal | |||||||||
Author Name |
Mrunali Patil, Mahesh Kumbhar, Shailaja Nalawade | |||||||||
Affilition |
Student, Rajarambapu Institute of Technology, Islampur, India Assistant professor, Rajarambapu Institute of Technology, Islampur, India | |||||||||
Pages |
30-33 | |||||||||
Abstract |
Pain is an unpredictable and emotional experience that represents various estimation challenges. While self-report by the patient is seen as the best quality level of pain assessment. Pain is considered as the most important symptom to detect which type of disease is present. Here, we present a pain force estimation strategy based on the EMG signal. In this proposed work discrimination is achieved by analysing EMG signals obtained from freely accessible databases. This paper shows the pain intensity detection analysis using EMG signals for the patient's treatment method assisting technology. The pain in patients is associated during surgery or due to some injuries in which the right level of anesthetic medicines providing to the patients is the main reason behind the objective of this work. The medicine levels to be provided are supposed to be considered. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in this work presents a classification of normal and Pain activities. Keywords - Electromyography Signal (EMG), Feature Extraction, Feature Reduction, Support Vector Machine (SVM) | |||||||||
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