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Automatic Recognition Methods Supporting Pain Assessment: A Survey

Author(s)
Werner, Philipp; Lopez-Martinez, Daniel; Walter, Steffen; Al-Hamadi, Ayoub; Gruss, Sascha; Picard, Rosalind W.; ... Show more Show less
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Abstract
IEEE Automated tools for pain assessment have great promise but have not yet become widely used in clinical practice. In this survey paper, we review the literature that proposes and evaluates automatic pain recognition approaches, and discuss challenges and promising directions for advancing this field. Prior to that, we give an overview on pain mechanisms and responses, discuss common clinically used pain assessment tools, and address shared datasets and the challenge of validation in the context of pain recognition.
Date issued
2019
URI
https://hdl.handle.net/1721.1/136497
Department
Massachusetts Institute of Technology. Media Laboratory
Journal
IEEE Transactions on Affective Computing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)

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