Automatic Pain Detection in Video Sequences for Neuro-Rehabilitation

Abstract:

Adaptive and interactive mental engagement combined with positive emotional state are requirements for an optimal outcome of the neuro-rehabilitation process for patients with brain damage usually caused by TBI (traumatic brain injury), stroke or brain disease such as cancer, epilepsy, and Alzheimer's disease. We propose a method for automatic pain recognition in video sequences using the landmarks data from Supervised Descent Method and applying Support Vector Machine (SVM) for data classification. This method is suitable for being part of assistive medical system for neuro-rehabilitation of patients with TBI. The experiments with a video dataset with patients with shoulder pain show very good recognition rate (95,7%) for recognizing the painful facial states of the subjects.

• Periodical: Materials Science Forum (Volume 856)
• Pages: 213-218
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.856.213
• Online since: May 2016
• Authors: Nikolay Neshov*, Agata Manolova
• Keywords: Face Alignment, Facial Expression, Pain Estimation, Supervised Descent Method (SDM), Support Vector Machine (SVM) Classifier

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