2020/01/21 by Joy Egede, Egede, Joy O., Siyang Song +17 · 1 citation
Medicine · Neuroscience · Psychology · #Computer Vision and Pattern Recognition (cs.CV) #EEG and Brain-Computer Interfaces #Emotion and Mood Recognition #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Musculoskeletal pain and rehabilitation #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2001.07739
openalex publication_date 2020/01/21 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
The EmoPain 2020 Challenge is the first international competition aimed at\ncreating a uniform platform for the comparison of machine learning and\nmultimedia processing methods of automatic chronic pain assessment from human\nexpressive behaviour, and also the identification of pain-related behaviours.\nThe objective of the challenge is to promote research in the development of\nassistive technologies that help improve the quality of life for people with\nchronic pain via real-time monitoring and feedback to help manage their\ncondition and remain physically active. The challenge also aims to encourage\nthe use of the relatively underutilised, albeit vital bodily expression signals\nfor automatic pain and pain-related emotion recognition. This paper presents a\ndescription of the challenge, competition guidelines, bench-marking dataset,\nand the baseline systems' architecture and performance on the three sub-tasks:\npain estimation from facial expressions, pain recognition from multimodal\nmovement, and protective movement behaviour detection.\n