» Articles » PMID: 30910279

Data Management and Wearables in Older Adults: A Systematic Review

Overview
Journal Maturitas
Specialty Geriatrics
Date 2019 Mar 27
PMID 30910279
Citations 26
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Wearable trackers as research or clinical tools are increasingly used to support the care of older adults, due to their practicality in self-monitoring and potential to promote healthy lifestyle behaviours. However, there is limited understanding of appropriate data collection and analysis methods in different contexts.

Aim: To summarise evidence on wearable data generation and management in older adults, focusing on physical activity (PA), electrocardiogram (ECG), and vital signs monitoring. In addition to examine the accuracy and utility of wearable trackers in the care of older people.

Methods: A systematic search of CINAHL, MEDLINE, PubMed and a manual search were conducted. Twenty studies on the use of wearable trackers by older adults met the inclusion criteria.

Results: Methodological designs for data collection and analysis were heterogeneous, with diverse definitions of wear and no-wear time, the number and type of valid days, and proprietary algorithms. Wearable trackers had adequate accuracy for measuring step counts, moderate to vigorous physical activity (MVPA), ECG and heart rate (HR), but not for respiratory rate. Participants reported ease of use and had high-level adherence over daily long-term use. Moreover, wearable trackers encouraged users to increase their daily level of physical activity and decrease waist circumference, facilitating atrial fibrillation (AF) diagnoses and predicting length of stay.

Conclusion: Wearable trackers are multi-dimensional technologies offering a viable and promising approach for sustained and scaled monitoring of older people's health. Frameworks and/or guidelines, including standards for the design, data management and application of use specifically for older adults, are required to enhance validity and reliability.

Citing Articles

Evaluation of Photoplethysmography-Based Monitoring of Respiration Rate During High-Intensity Interval Training: Implications for Healthcare Monitoring.

Muller M, Ebrahimkheil K, Vijgeboom T, van Eijck C, Ronner E Biosensors (Basel). 2024; 14(12).

PMID: 39727896 PMC: 11674237. DOI: 10.3390/bios14120631.


Perceived Benefit and Satisfaction With a Tablet Computer and an Emergency Smartwatch by Older Adults and Their Relatives: Prospective Real-World Pilot Study.

Wiegel P, Fotteler M, Kohn B, Mayer S, Verri F, Dallmeier D JMIR Hum Factors. 2024; 11:e53811.

PMID: 39104048 PMC: 11310738. DOI: 10.2196/53811.


Physical Activity Evaluation Using a Voice Recognition App: Development and Validation Study.

Namba H JMIR Biomed Eng. 2024; 6(1):e19088.

PMID: 38907383 PMC: 11041261. DOI: 10.2196/19088.


Impact of automated data flow and reminders on adherence and resource utilization for remotely monitoring physical activity in individuals with stroke or chronic obstructive pulmonary disease.

French M, Balasubramanian A, Hansel N, Penttinen S, Wise R, Raghavan P medRxiv. 2024; .

PMID: 38699312 PMC: 11064997. DOI: 10.1101/2024.04.15.24305852.


Mobile app activity engagement by cancer patients and their caregivers informs remote monitoring.

Yunis R, Fonda S, Aghaee S, Kubo A, Davis S, Liu R Sci Rep. 2024; 14(1):3375.

PMID: 38336943 PMC: 10858186. DOI: 10.1038/s41598-024-53373-w.