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

New Methods (909) Sensors at Home and Domotics (51) Home Care (159) Design and Usability of Consumer Health Tech and Home Monitoring Devices (188) Fitness Trackers and Smart Pedometers/Accelerometers (541) mHealth for Telemedicine and Homecare (364) Wearable Devices and Sensors (818) Assisted Living for the Elderly and Nursing Home Care (147) Falls Prevention in the Elderly (64) Physical Activity for Older People (150) Frailty Detection, Assessment and Prediction (19)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19732, first published .
Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study

Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study

Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study

Authors of this article:

Ben Kim1 Author Orcid Image ;   Sandra M McKay2, 3 Author Orcid Image ;   Joon Lee4, 5, 6 Author Orcid Image
Article Authors Cited by (9) Tweetations (4) Metrics

Journals

  1. Piau A, Steinmeyer Z, Charlon Y, Courbet L, Rialle V, Lepage B, Campo E, Nourhashemi F. A Smart Shoe Insole to Monitor Frail Older Adults’ Walking Speed: Results of Two Evaluation Phases Completed in a Living Lab and Through a 12-Week Pilot Study. JMIR mHealth and uHealth 2021;9(7):e15641 View
  2. Abbas M, Le Bouquin Jeannès R. A Review of Frailty Analysis in Older Adults: From Clinical Tools Towards Fully Automated Preventive Systems. IRBM 2023;44(2):100743 View
  3. Calvillo-Arbizu J, Naranjo-Hernández D, Barbarov-Rostán G, Talaminos-Barroso A, Roa-Romero L, Reina-Tosina J. A Sensor-Based mHealth Platform for Remote Monitoring and Intervention of Frailty Patients at Home. International Journal of Environmental Research and Public Health 2021;18(21):11730 View
  4. Abbas M, Saleh M, Somme D, Le Bouquin Jeannès R, Cè E. Data-driven systems to detect physical weakening from daily routine: A pilot study on elderly over 80 years old. PLOS ONE 2023;18(1):e0274306 View
  5. Gao Y, Chen Y, Hu M, Gan T, Sun X, Zhang Z, He W, Wu I. Characteristics and Quality of Diagnostic and Risk Prediction Models for Frailty in Older Adults: A Systematic Review. Journal of Applied Gerontology 2022;41(9):2113 View
  6. Leghissa M, Carrera Á, Iglesias C. Machine learning approaches for frailty detection, prediction and classification in elderly people: A systematic review. International Journal of Medical Informatics 2023;178:105172 View
  7. Pitt J, Zeineddin S, Carter M, Figueroa A, Park E, Kwon S, Ghomrawi H, Abdullah F. Using Consumer Wearable Devices to Profile Postoperative Complications After Pediatric Appendectomy. Journal of Surgical Research 2024;295:853 View
  8. Effah Kaufmann E, Tackie R, Pitt J, Mba S, Akwetey B, Quaye D, Mills G, Nyame C, Bulley H, Glucksberg M, Ghomrawi H, Appeadu-Mensah W, Abdullah F, Larizza C. Feasibility of Leveraging Consumer Wearable Devices with Data Platform Integration for Patient Vital Monitoring in Low-Resource Settings. International Journal of Telemedicine and Applications 2024;2024:1 View
  9. Camerlingo N, Shaafi Kabiri N, Psaltos D, Kelly M, Wicker M, Messina I, Auerbach S, Zhang H, Messere A, Isik Karahanoglu F, Santamaria M, Demanuele C, Caouette D, Thomas K. Monitoring Gait and Physical Activity of Elderly Frail Individuals in Free-Living Environment: A Feasibility Study. Gerontology 2024;70(4):439 View