Multimodal-Based Stream Integrated Neural Networks for Pain Assessment
Author:
Affiliation:
1. School of Computer and Communication Engineering, University of Science and Technology Beijing
2. Department of Computer Science and Engineering, University of South Florida
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E104.D/12/E104.D_2021EDP7065/_pdf
Reference50 articles.
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3. [3] C.C. Johnston and M.E. Strada, “Acute pain response in infants: a multidimensional description,” Pain, vol.24, no.3, pp.373-382, 1986. 10.1016/0304-3959(86)90123-5
4. [4] M.H. Willis, S.I. Merkel, T. Voepel-Lewis, and S. Malviya, “Flacc behavioral pain assessment scale: a comparison with the child's self-report,” Pediatric nursing, vol.29, no.3, p.195, 2003.
5. [5] S. Walter, S. Gruss, H. Ehleiter, J. Tan, H.C. Traue, P. Werner, A. Al-Hamadi, S. Crawcour, A.O. Andrade, and G.M. da Silva, “The biovid heat pain database data for the advancement and systematic validation of an automated pain recognition system,” 2013 IEEE international conference on cybernetics (CYBCO), pp.128-131, IEEE, 2013. 10.1109/cybconf.2013.6617456
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