Kim, B. et al., 20201515 Kim B, McKay SM, Lee J. Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study. J Med Internet Res 2020;22(9):e19732; http://doi.org/10.2196/19732. https://doi.org/10.2196/19732...
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Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study |
Prospective Study Conducted in Canada, participants wore a monitoring device for a minimum of 8 days. |
To prove that the use of a wearable device to assess frailty in older adults home care clients may be possible. |
N = 37 participants Mean age= 82.23 (±10.84) female sex = 76% |
Xiaomi Mi Band Pulse 1S |
Daily step count, sleep measures (deep sleep time, light sleep time, total sleep time, sleep quality), heart rate measures. |
Mach, M. et al., 20201616 Mach M, Watzal V, Hasan W, Andreas M, Winkler B, Weiss G, et al. Fitness-Tracker Assisted Frailty-Assessment Before Transcatheter Aortic Valve Implantation: Proof-of-Concept Study. JMIR MHealth UHealth 2020;8(10):e19227; http://doi.org/10.2196/19227. https://doi.org/10.2196/19227...
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Fitness-Tracker Assisted Frailty-Assessment Before Transcatheter Aortic Valve Implantation: Proof-of-Concept Study |
Prospective Study Conducted in Austria in 2017-2018, each patient used a monitoring device for 1 week before the surgical procedure. |
To develop a simple, efficient and cost-effective method for assessing pre-procedure frailty of transcatheter aortic valve implantation, based on parameters measured by a wearable health monitoring device |
N = 50 patients Mean age= 77.5 (±5.1) years female sex = 44% |
Garmin Vivosmart 3 |
Daily step count, distance covered (in kilometers), calories burned, time spent at different stress levels, hours and depth of sleep, minimum and maximum heart rate, and number of flights of stairs climbed. |
Kim, B.; Kim, A., 20211717 Kim B, Hunt M, Muscedere J, Maslove DM, Lee J. Using Consumer-Grade Physical Activity Trackers to Measure Frailty Transitions in Older Critical Care Survivors: Exploratory Observational Study. JMIR Aging 2021;4(1):e19859; http://doi.org/10.2196/19859. https://doi.org/10.2196/19859...
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Using Consumer-Grade Physical Activity Trackers to Measure Frailty Transitions in Older Critical Care Survivors: Exploratory Observational Study |
Prospective Study Performed in Canada, patients were followed up for 4 weeks after hospital discharge |
Examine data generated from wearable devices for their association with frailty progression after hospital discharge. |
N = 12 Mean age= 66.75 (±6.80) years. female sex = 58.3% |
Fitbit Charge HR |
Daily step count, active and sedentary time, sleep efficiency (obtained from the percentage of sleep time over total sleep time) and heart rate. |
Schmidle, S. et al., 20231818 Schmidle S, Gulde P, Koster R, Maslove DM, Lee J. The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults – a multicentric cross-sectional study. BMC Geriatr 2023;23(1):43; http://doi.org/10.1186/s12877-022-03711-2. https://doi.org/10.1186/s12877-022-03711...
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The relationship between self-reported physical frailty and sensor-based physical activity measures in older adults – a multicentric cross-sectional study |
Multicenter cross-sectional study Conducted in Germany and France between May and November 2019, the average time of use of the smartwatch was 17.5 (± 5.1) days with ≥8 hours per day |
Assess whether and to what extent a self-reported assessment of frailty is associated with daily physical activity patterns. |
N = 88 Mean age= 80.6 (±9.1) female = 55% |
Huawei 2 (4G) |
Measure the intensity of acceleration changes, i.e. the intensity of physical activity, for every five seconds of data and daily step count. |