फिजियोथेरेपी और शारीरिक पुनर्वास जर्नल

Analyzing Multimodal Signals with Wavelet Scattering for Pain Detection in Physiotherapy

Abstract

Julian Grayson

Surgery that is successful but uncomfortable is facial treatment. In order to modify your treatment and prevent tissue damage, the physiotherapist needs to know how much pain you are experiencing. We have developed a method due to the necessity of automated pain-related reaction assessment in physiotherapy and the subjectivity of a self-report. Using a multimodal data set, we calculate the feature vector, which also includes the coefficients of the wavelet scattering transform. The AdaBoost classification model differentiates between no pain, moderate pain, and severe pain. The assumption that is made in our survey is that every patient will react to pain in a different way and be more or less resistant to it. The outcomes show how different pain feels for each patient. In addition, they demonstrate that multiclass evaluation outperforms binary recognition.