Published on in Vol 3, No 1 (2020): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16131, first published .
Descriptive Evaluation and Accuracy of a Mobile App to Assess Fall Risk in Seniors: Retrospective Case-Control Study

Descriptive Evaluation and Accuracy of a Mobile App to Assess Fall Risk in Seniors: Retrospective Case-Control Study

Descriptive Evaluation and Accuracy of a Mobile App to Assess Fall Risk in Seniors: Retrospective Case-Control Study

Journals

  1. Wilmink G, Dupey K, Alkire S, Grote J, Zobel G, Fillit H, Movva S. Artificial Intelligence–Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study. JMIR Aging 2020;3(2):e19554 View
  2. Fuchs D, Tiebel J, Friedrich P. Device-supported training and assessment for fall prevention of community-dwelling elderly: a pre-post mixed methods study. Procedia Computer Science 2020;176:2322 View
  3. Onyeaka H, Romero P, Healy B, Celano C. Age Differences in the Use of Health Information Technology Among Adults in the United States: An Analysis of the Health Information National Trends Survey. Journal of Aging and Health 2021;33(1-2):147 View
  4. Stamm O, Heimann-Steinert A. Accuracy of Monocular Two-Dimensional Pose Estimation Compared With a Reference Standard for Kinematic Multiview Analysis: Validation Study. JMIR mHealth and uHealth 2020;8(12):e19608 View