» Articles » PMID: 35591222

The Development and Concurrent Validity of a Multi-Sensor-Based Frailty Toolkit for In-Home Frailty Assessment

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2022 May 20
PMID 35591222
Authors
Affiliations
Soon will be listed here.
Abstract

Early identification of frailty is crucial to prevent or reverse its progression but faces challenges due to frailty’s insidious onset. Monitoring behavioral changes in real life may offer opportunities for the early identification of frailty before clinical visits. This study presented a sensor-based system that used heterogeneous sensors and cloud technologies to monitor behavioral and physical signs of frailty from home settings. We aimed to validate the concurrent validity of the sensor measurements. The sensor system consisted of multiple types of ambient sensors, a smart speaker, and a smart weight scale. The selection of these sensors was based on behavioral and physical signs associated with frailty. Older adults’ perspectives were also included in the system design. The sensor system prototype was tested in a simulated home lab environment with nine young, healthy participants. Cohen’s Kappa and Bland−Altman Plot were used to evaluate the agreements between the sensor and ground truth measurements. Excellent concurrent validity was achieved for all sensors except for the smart weight scale. The bivariate correlation between the smart and traditional weight scales showed a strong, positive correlation between the two measurements (r = 0.942, n = 24, p < 0.001). Overall, this work showed that the Frailty Toolkit (FT) is reliable for monitoring physical and behavioral signs of frailty in home settings.

Citing Articles

Cross-sectional study comparing smart insoles and manual methods for short physical performance battery in hip fracture patients.

Kim S, Kim S, Kim H, Kim H, Yoo J Aging Clin Exp Res. 2025; 37(1):61.

PMID: 40021544 PMC: 11870933. DOI: 10.1007/s40520-025-02960-6.


Longitudinal fragility phenotyping contributes to the prediction of lifespan and age-associated morbidity in C57BL/6 and Diversity Outbred mice.

Luciano A, Robinson L, Garland G, Lyons B, Korstanje R, Di Francesco A Geroscience. 2024; 46(5):4937-4954.

PMID: 38935230 PMC: 11639350. DOI: 10.1007/s11357-024-01226-9.


The Cooperation Between Nurses and a New Digital Colleague "AI-Driven Lifestyle Monitoring" in Long-Term Care for Older Adults: Viewpoint.

Groeneveld S, Bin Noon G, den Ouden M, van Os-Medendorp H, van Gemert-Pijnen J, Verdaasdonk R JMIR Nurs. 2024; 7:e56474.

PMID: 38781012 PMC: 11157177. DOI: 10.2196/56474.


Longitudinal Fragility Phenotyping Predicts Lifespan and Age-Associated Morbidity in C57BL/6 and Diversity Outbred Mice.

Luciano A, Robinson L, Garland G, Lyons B, Korstanje R, Di Francesco A bioRxiv. 2024; .

PMID: 38370707 PMC: 10871234. DOI: 10.1101/2024.02.06.579096.


Validation of the Short Physical Performance Battery via Plantar Pressure Analysis Using Commercial Smart Insoles.

Jang C, Park K, Paek M, Jee S, Park J Sensors (Basel). 2023; 23(24).

PMID: 38139603 PMC: 10747671. DOI: 10.3390/s23249757.

References
1.
Hajek A, Bock J, Saum K, Matschinger H, Brenner H, Holleczek B . Frailty and healthcare costs-longitudinal results of a prospective cohort study. Age Ageing. 2017; 47(2):233-241. DOI: 10.1093/ageing/afx157. View

2.
Millor N, Lecumberri P, Gomez M, Martinez-Ramirez A, Izquierdo M . An evaluation of the 30-s chair stand test in older adults: frailty detection based on kinematic parameters from a single inertial unit. J Neuroeng Rehabil. 2013; 10:86. PMC: 3735415. DOI: 10.1186/1743-0003-10-86. View

3.
Schreier G, Eckmann H, Hayn D, Kreiner K, Kastner P, Lovell N . Web versus app: compliance of patients in a telehealth diabetes management programme using two different technologies. J Telemed Telecare. 2012; 18(8):476-80. DOI: 10.1258/jtt.2012.gth112. View

4.
Mondor L, Maxwell C, Hogan D, Bronskill S, Campitelli M, Seitz D . The Incremental Health Care Costs of Frailty Among Home Care Recipients With and Without Dementia in Ontario, Canada: A Cohort Study. Med Care. 2019; 57(7):512-520. DOI: 10.1097/MLR.0000000000001139. View

5.
Stone E, Skubic M, Rantz M, Abbott C, Miller S . Average in-home gait speed: investigation of a new metric for mobility and fall risk assessment of elders. Gait Posture. 2014; 41(1):57-62. DOI: 10.1016/j.gaitpost.2014.08.019. View