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

Mobile Health (mhealth) (2748) Ecological Momentary Assessment (EMA) (294) New Methods (901) mHealth for Wellness, Behavior Change and Prevention (2728) Wearable Devices and Sensors (811) Anxiety and Stress Disorders (999) mHealth for Data Collection and Research (907)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39995, first published .
Detecting Prolonged Stress in Real Life Using Wearable Biosensors and Ecological Momentary Assessments: Naturalistic Experimental Study

Detecting Prolonged Stress in Real Life Using Wearable Biosensors and Ecological Momentary Assessments: Naturalistic Experimental Study

Detecting Prolonged Stress in Real Life Using Wearable Biosensors and Ecological Momentary Assessments: Naturalistic Experimental Study

Authors of this article:

Rayyan Tutunji1 Author Orcid Image ;   Nikos Kogias1 Author Orcid Image ;   Bob Kapteijns1 Author Orcid Image ;   Martin Krentz1 Author Orcid Image ;   Florian Krause1 Author Orcid Image ;   Eliana Vassena1, 2 Author Orcid Image ;   Erno J Hermans1 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Bahameish M, Stockman T, Requena Carrión J. Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features. Sensors 2024;24(10):3210 View