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

Neurotech Innovations, Diagnostic Tools and Techniques (38) Depression and Mood Disorders; Suicide Prevention (1401) Digital Biomarkers and Digital Phenotyping (200) Diagnostic Tools in Mental Health (252) mHealth for Data Collection and Research (992) Methods and New Tools in Mental Health Research (468) Wearable Devices and Sensors (914) Fitness Trackers and Smart Pedometers/Accelerometers (576) Longitudinal and Cohort Studies in Public Health (319) Stroke (169)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56679, first published .
Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis

Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis

Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis

Authors of this article:

Stephanie J Zawada1 Author Orcid Image ;   Ali Ganjizadeh2 Author Orcid Image ;   Gian Marco Conte2 Author Orcid Image ;   Bart M Demaerschalk1, 3 Author Orcid Image ;   Bradley J Erickson2, 4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Stephanie J Zawada   1 , PhD, MS ;   Ali Ganjizadeh   2 , MD ;   Gian Marco Conte   2 , MD, PhD ;   Bart M Demaerschalk   1, 3 , MD, MSc ;   Bradley J Erickson   2, 4 , MD, PhD

1 Mayo Clinic College of Medicine and Science, Phoenix, AZ, United States

2 AI Laboratory, Department of Radiology, Mayo Clinic, Rochester, MN, United States

3 Department of Neurology, Division of Cerebrovascular Diseases, Mayo Clinic, Phoenix, AZ, United States

4 Mayo Clinic College of Medicine and Science, Rochester, MN, United States

Corresponding Author: