Machine Learning, Deep Learning and Affective Computing
Rui Qin is a postdoctoral researcher in department of Electronic and Electrical Engineering, University College of London (UCL). He received his PhD in Brunel University London in 2019, MSc in Brunel University London in 2014, B.S. in Universiy of Eletronic Science and Technology of China in 2012. He works as Autonomy Scientist in AIDRIVERS from 2019 to 2020 developed autonomous driving systems.
Abstract: Chronic pain is a disease that the patients suffers a lot in their daily life and it is difficult to be released completely. It is difficult to manage because pain can come anytime and it is unpredictable. However, the pain can be represented by the pain related behaviors such as guiding and abrupt actions. In this paper, we will develop a machine learning based system that can detect the pain related behaviors from patient’s Electromyography (EMG) signals and body movements continuously. The system includes data collection, feature extraction, modeling and classification. The data were collected using biosensor sensor for EMG and motion capture for body movement. Specific features are extracted from the body movement data. Then Random Forest and a Two Stage Classification (TSC) scheme (KNN coupled with Hidden Markov Model (HMM)) were used for pain related behavior detection in a continuous manner. The proposed method was tested on Emo-Pain corpus dataset provided by UCL and experimental results demonstrate the efficiency of the proposed method.
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