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

Formative Evaluation of Digital Health Interventions (2410) Fitness Trackers and Smart Pedometers/Accelerometers (561) Tools, Programs and Algorithms (266) Medication Adherence (83) Instruments and Questionnaires for Physical Activity and Lifestyle (72) Quantified Self and Wellness (77) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1514) Innovations in Mental Health Systems (390) Implantable Drug Delivery Systems, Ingestible Sensors and Digital Pills (15)

Published on in Vol 5, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17993, first published .
A Rest Quality Metric Using a Cluster-Based Analysis of Accelerometer Data and Correlation With Digital Medicine Ingestion Data: Algorithm Development

A Rest Quality Metric Using a Cluster-Based Analysis of Accelerometer Data and Correlation With Digital Medicine Ingestion Data: Algorithm Development

A Rest Quality Metric Using a Cluster-Based Analysis of Accelerometer Data and Correlation With Digital Medicine Ingestion Data: Algorithm Development

Authors of this article:

Zahra Heidary1 Author Orcid Image ;   Jeffrey M Cochran1 Author Orcid Image ;   Timothy Peters-Strickland1 Author Orcid Image ;   Jonathan Knights1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Cochran J. A Noninterventional, Observational Sleep Study to Develop a Sleep Algorithm to Support a Digital Medicine System (Preprint). JMIR Mental Health 2024 View