Autors: Neshov, N. N., Manolova, A. H.
Title: Automatic pain detection in video sequences for neuro-rehabilitation
Keywords: Pain Estimation, Facial Expression, Face Alignment, Supervis

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.



    Ninth Japanese-Mediterranean Workshop on Applied Electromagnetic Engineering for Magnetic, Super-conducting, Multifunctional and Nanomaterials. JAPMED’9, 2015, Bulgaria,

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    Цитирания (Citation/s):
    1. Saddam, E.N., Abbas, S.M., Ali, W.H. Patient's Pain Recognition by Using Deep Models Based on Transfer Learning (2022) 2022 International Conference on Data Science and Intelligent Computing, ICDSIC 2022, pp. 129-134. - 2022 - в издания, индексирани в Scopus или Web of Science

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