Machine Learning-Based Pain Intensity Estimation: Where Pattern Recognition Meets Chaos Theory—An Example Based on the BioVid Heat Pain Database
Author:
Affiliation:
1. Institute of Neural Information Processing, Ulm University, Ulm, Germany
2. Institute of Medical Systems Biology, Ulm University, Ulm, Germany
Funder
Project Multimodal Recognition of Affect Over the Course of a Tutorial Learning Experiment through the German Research Foundation
German Research Foundation
German Federal Ministery of Education and Research (BMBF) e:MED Confirm and TRAN-SCAN VI—PMTR-pNET
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09900327.pdf?arnumber=9900327
Reference32 articles.
1. Automatic Recognition Methods Supporting Pain Assessment: A Survey
2. Automatic Pain Assessment with Facial Activity Descriptors
3. Twofold-Multimodal Pain Recognition with the X-ITE Pain Database
4. Chaos II
5. Adaptive confidence learning for the personalization of pain intensity estimation systems
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2. Survey on Pain Detection using Machine Learning Models (Preprint);JMIR AI;2023-09-22
3. Survey on Pain Detection using Machine Learning Models (Preprint);2023-09-22
4. Children’s Pain Identification Based on Skin Potential Signal;Sensors;2023-07-31
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