Pain Classification Using Discrete Wavelet Transform Feature Extraction and Machine Learning Techniques

Electrodermal activity (EDA) measurement has been identified as a useful indicator for evaluating pain levels in patients. This study aims to find features of the EDA signal that influence pain classification. The proposed approach includes signal decomposition, feature extraction from EDA signals,...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Sudimanto, Iman Herwidiana Kartowisastro, Agung Trisetyarso, Widodo Budiharto
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Discrete wavelet transform (DWT) electrodermal activity (EDA) machine learning non-invasive pain monitoring system pain levels signal decomposition
Online Access:	https://ieeexplore.ieee.org/document/10904220/