Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at, first published .
Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study

Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study

Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study


  1. Kong Y, Posada-Quintero H, Chon K. Real-Time High-Level Acute Pain Detection Using a Smartphone and a Wrist-Worn Electrodermal Activity Sensor. Sensors 2021;21(12):3956 View
  2. Wells C, Xu W, Penfold J, Keane C, Gharibans A, Bissett I, O’Grady G. Wearable devices to monitor recovery after abdominal surgery: scoping review. BJS Open 2022;6(2) View
  3. Afandizadeh Zargari A, Aqajari S, Khodabandeh H, Rahmani A, Kurdahi F. An Accurate Non-accelerometer-based PPG Motion Artifact Removal Technique using CycleGAN. ACM Transactions on Computing for Healthcare 2023;4(1):1 View
  4. Tronstad C, Amini M, Bach D, Martinsen Ø. Current trends and opportunities in the methodology of electrodermal activity measurement. Physiological Measurement 2022;43(2):02TR01 View
  5. Bhatkar V, Picard R, Staahl C. Combining Electrodermal Activity With the Peak-Pain Time to Quantify Three Temporal Regions of Pain Experience. Frontiers in Pain Research 2022;3 View
  6. 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
  7. Montero Quispe K, Utyiama D, dos Santos E, Oliveira H, Souto E. Applying Self-Supervised Representation Learning for Emotion Recognition Using Physiological Signals. Sensors 2022;22(23):9102 View
  8. Kong Y, Posada-Quintero H, Tran H, Talati A, Acquista T, Chen I, Chon K. Differentiating between stress- and EPT-induced electrodermal activity during dental examination. Computers in Biology and Medicine 2023;155:106695 View
  9. Liikkanen S, Mäkinen M, Huttunen T, Sarapohja T, Stenfors C, Eccleston C. Body movement as a biomarker for use in chronic pain rehabilitation: An embedded analysis of an RCT of a virtual reality solution for adults with chronic pain. Frontiers in Pain Research 2022;3 View
  10. Klimek A, Mannheim I, Schouten G, Wouters E, Peeters M. Wearables measuring electrodermal activity to assess perceived stress in care: a scoping review. Acta Neuropsychiatrica 2023:1 View
  11. Gröhn T, Liikkanen S, Huttunen T, Mäkinen M, Liljeberg P, Marttinen P. Quantifying Movement Behavior of Chronic Low Back Pain Patients in Virtual Reality. ACM Transactions on Computing for Healthcare 2023;4(2):1 View
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  13. Johansen A, Mølgaard J, Rasmussen S, Gu Y, Grønbæk K, Sørensen H, Aasvang E, Meyhoff C. Deviations in continuously monitored electrodermal activity before severe clinical complications: a clinical prospective observational explorative cohort study. Journal of Clinical Monitoring and Computing 2023;37(6):1573 View
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  15. Pinzon-Arenas J, Kong Y, Chon K, Posada-Quintero H. Design and Evaluation of Deep Learning Models for Continuous Acute Pain Detection Based on Phasic Electrodermal Activity. IEEE Journal of Biomedical and Health Informatics 2023;27(9):4250 View
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  17. Zargari A, AshrafiAmiri M, Seo M, Pudukotai Dinakarrao S, Fouda M, Kurdahi F. CAPTIVE: Constrained Adversarial Perturbations to Thwart IC Reverse Engineering. Information 2023;14(12):656 View
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Books/Policy Documents

  1. Bieńkowska M, Badura A, Myśliwiec A, Pietka E. Information Technology in Biomedicine. View
  2. 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