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

RCTs - Protocols/Proposals (funded, already peer-reviewed, eHealth) (354) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1428) Hypertension Prevention and Treatment (229) Mobile Health (mhealth) (2982) Design and Usability of Consumer Health Tech and Home Monitoring Devices (228) Machine Learning (1501) Formative Evaluation of Digital Health Interventions (2491) Artificial Intelligence (1421) AI Applications in Biomedical Engineering (9)

Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55615, first published .
Personalized AI-Driven Real-Time Models to Predict Stress-Induced Blood Pressure Spikes Using Wearable Devices: Proposal for a Prospective Cohort Study

Personalized AI-Driven Real-Time Models to Predict Stress-Induced Blood Pressure Spikes Using Wearable Devices: Proposal for a Prospective Cohort Study

Personalized AI-Driven Real-Time Models to Predict Stress-Induced Blood Pressure Spikes Using Wearable Devices: Proposal for a Prospective Cohort Study

Authors of this article:

Ali Kargarandehkordi1 Author Orcid Image ;   Christopher Slade1 Author Orcid Image ;   Peter Washington1 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Ali Kargarandehkordi   1 , MSc ;   Christopher Slade   1 , MSc ;   Peter Washington   1 , PhD

1 Department of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI, United States

Corresponding Author:

  • Peter Washington, PhD
  • Department of Information and Computer Sciences
  • University of Hawaii at Manoa
  • 1680 East-West Road
  • Honolulu, HI, 96822
  • United States
  • Phone: 1 5126800926
  • Email: pyw@hawaii.edu