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

Development and Evaluation of Research Methods, Instruments and Tools (744) e-Cardiology and Telemonitoring in Cardiology (221) Mobile Apps for Cardiology (189) Mobile Health (mhealth) (3464) Formative Evaluation of Digital Health Interventions (3229) Design and Formative Evaluation of Mobile Apps (809)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56921, first published .
Examining the Light Heart Mobile Device App for Assessing Human Pulse Interval and Heart Rate Variability: Validation Study

Examining the Light Heart Mobile Device App for Assessing Human Pulse Interval and Heart Rate Variability: Validation Study

Examining the Light Heart Mobile Device App for Assessing Human Pulse Interval and Heart Rate Variability: Validation Study

Authors of this article:

Stephen A Klassen1 Author Orcid Image ;   Jesica Jabbar1 Author Orcid Image ;   Jenna Osborne1 Author Orcid Image ;   Nathaniel J Iannarelli1 Author Orcid Image ;   Emerson S Kirby2 Author Orcid Image ;   Deborah D O'Leary1 Author Orcid Image ;   Sean Locke1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Tawfeek M, Alrashdi I, Alruwaili M, Allahem H, Pedrammehr S. Cardiovascular disease detection: A hybrid machine learning-AI framework for personalized diagnosis and risk assessment. PLOS One 2025;20(10):e0335421 View