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

Non-randomized Protocols and Methods (ehealth) (571) Digital Pain Assessment and Management (170) Telehealth and Telemonitoring (1709) Machine Learning (1487) Wearable Devices and Sensors (900) Postoperative Monitoring and Telemonitoring (127)

Published on in Vol 9, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17783, first published .
Prospective Study Evaluating a Pain Assessment Tool in a Postoperative Environment: Protocol for Algorithm Testing and Enhancement

Prospective Study Evaluating a Pain Assessment Tool in a Postoperative Environment: Protocol for Algorithm Testing and Enhancement

Prospective Study Evaluating a Pain Assessment Tool in a Postoperative Environment: Protocol for Algorithm Testing and Enhancement

Authors of this article:

Emad Kasaeyan Naeini1 Author Orcid Image ;   Mingzhe Jiang2 Author Orcid Image ;   Elise Syrjälä2 Author Orcid Image ;   Michael-David Calderon3 Author Orcid Image ;   Riitta Mieronkoski4 Author Orcid Image ;   Kai Zheng5 Author Orcid Image ;   Nikil Dutt1 Author Orcid Image ;   Pasi Liljeberg2 Author Orcid Image ;   Sanna Salanterä4, 6 Author Orcid Image ;   Ariana M Nelson7 Author Orcid Image ;   Amir M Rahmani1, 8 Author Orcid Image
Article Authors Cited by (7) Tweetations (1) Metrics

Journals

  1. Aqajari S, Cao R, Kasaeyan Naeini E, Calderon M, Zheng K, Dutt N, Liljeberg P, Salanterä S, Nelson A, Rahmani A. Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study. JMIR mHealth and uHealth 2021;9(5):e25258 View
  2. Kasaeyan Naeini E, Subramanian A, Calderon M, Zheng K, Dutt N, Liljeberg P, Salantera S, Nelson A, Rahmani A. Pain Recognition With Electrocardiographic Features in Postoperative Patients: Method Validation Study. Journal of Medical Internet Research 2021;23(5):e25079 View
  3. Somani S, Yu K, Chiu A, Sykes K, Villwock J. Consumer Wearables for Patient Monitoring in Otolaryngology: A State of the Art Review. Otolaryngology–Head and Neck Surgery 2022;167(4):620 View
  4. Cascella M, Schiavo D, Cuomo A, Ottaiano A, Perri F, Patrone R, Migliarelli S, Bignami E, Vittori A, Cutugno F, Hu L. Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives. Pain Research and Management 2023;2023:1 View
  5. Subramanian A, Cao R, Naeni E, Aqajari S, Hughes T, Calderon M, Zheng K, Dutt N, Liljeberg P, Salanterä S, Nelson A, Rahmani A. Multimodal Pain Recognition in Postoperative Patients: A Machine Learning Approach (Preprint). JMIR Formative Research 2024 View

Books/Policy Documents

  1. Kanduri A, Shahhosseini S, Naeini E, Alikhani H, Liljeberg P, Dutt N, Rahmani A. Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing. View