International Journal of Electrical, Electronics and Data Communication (IJEEDC)
eISSN:2320-2084 , pISSN:2321-2950
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Statistics report
Jun. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 134
Paper Published : 1721
No. of Authors : 4774
  Journal Paper

Paper Title :
Pain Intensity Estimation using EMG Signal

Author :Mrunali Patil, Mahesh Kumbhar, Shailaja Nalawade

Article Citation :Mrunali Patil ,Mahesh Kumbhar ,Shailaja Nalawade , (2020 ) " Pain Intensity Estimation using EMG Signal " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 30-33, Volume-8,Issue-9

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)

Type : Research paper

Published : Volume-8,Issue-9


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