This paper is in the following e-collection/theme issue:

Development and Evaluation of Research Methods, Instruments and Tools (743) Digital Pain Assessment and Management (232) Artificial Intelligence (2118) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1730) New Methods (1134) Machine Learning (2072) Tools, Programs and Algorithms (376) Postoperative Pain Management (38) Perioperative Software Tools for Clinicians (19)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67969, first published .
Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach

Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach

Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach

Authors of this article:

Ajan Subramanian1 Author Orcid Image ;   Rui Cao2 Author Orcid Image ;   Emad Kasaeyan Naeini1 Author Orcid Image ;   Seyed Amir Hossein Aqajari2 Author Orcid Image ;   Thomas D Hughes3 Author Orcid Image ;   Michael-David Calderon4 Author Orcid Image ;   Kai Zheng5 Author Orcid Image ;   Nikil Dutt1 Author Orcid Image ;   Pasi Liljeberg6 Author Orcid Image ;   Sanna Salanterä7, 8 Author Orcid Image ;   Ariana M Nelson9 Author Orcid Image ;   Amir M Rahmani1, 2, 3, 10 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

Journals

  1. Defaz Defaz L, Sisalema Bonito K, Tituaña Saquinga J, Torres Iza L, Acosta Nuñez J. Use of pain assessment scales in non-communicative patients. Community and Interculturality in Dialogue 2025;5:154 View
  2. Jang E, Eum Y, Yoon D, Byun S. Classifying social and physical pain from multimodal physiological signals using machine learning. Scientific Reports 2025;15(1) View
  3. Defaz Defaz L, Sisalema Bonito K, Tituaña Saquinga J, Torres Iza L, Acosta Nuñez J. Use Of Pain Assessment Scales In Non-Communicative And Communicative Patients. Community and Interculturality in Dialogue 2025;5:127 View
  4. Özdemir C. Çok Modlu Biyosinyallerle Akut Ağrıların Makine Öğrenmesiyle Tespiti. Türkiye Teknoloji ve Uygulamalı Bilimler Dergisi 2025;6(2):85 View
  5. Mukherjee P, Halder Roy A, Konar A, Nagar A. EEG and EMG Induced Pain-Sensitive Learning Controller for Robotic Knee Rehabilitation Using Deep Learning. IEEE Access 2025;13:179944 View

Conference Proceedings

  1. Bonilla L, Aguirre-Usandizaga J, Garcia-Perez A, Osa M, Belacortu I, Diaz-de-Arcaya J, Aroca J, Torre-Bastida A, Milioñ R, Almeida A. 2025 IEEE International Conference on Smart Computing (SMARTCOMP). Towards a Framework for Intelligent Sampling: Comprehensive Review of Challenges, AI Techniques, and Tools View
  2. Datta S, Datta G, Gedeon T, Hossain M. Companion Proceedings of the 27th International Conference on Multimodal Interaction. Painthenticate: Feature Engineering on Multimodal Physiological Signals View