Using Fitbit to Implement Personalized Walking Programs in Older Adults

Walking is an accessible and popular form of physical activity (PA) among the elderly, providing significant health advantages, including better cardiovascular health, stability, and cognitive function. Personalized PA prescriptions tailored to the individual health needs of older adults can optimize these benefits.This study explores implementing personalized walking programs using Fitbit devices to monitor and prescribe PA in older adults. The Home Automated Telemanagement (HAT) system was developed to enable remote monitoring and management of PA through a user-friendly interface and robust backend system. The HAT system integrates the Fitbit login, prescription management, and automatic record functionalities, allowing healthcare providers to prescribe individualized walking programs, monitor adherence, and adjust prescriptions based on real-time data. Data from the Fitbit devices, including daily steps, heart rate, calories burned, and sleep patterns, are collected and analyzed. The HAT system’s automated features enable timely patient and clinician feedback, promoting adherence to PA prescriptions and supporting clinical decision-making. Alerts are generated when patients fail to meet prescribed activity levels, prompting clinician intervention.The successful deployment of the HAT system demonstrates its potential to enhance the management of PA in older adults, providing a scalable solution for improving health outcomes through personalized PA prescriptions. Further research will focus on incorporating additional health metrics, such as real-time monitoring, to enhance the system’s capabilities and address the unique needs of older populations.

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Published
2024-10-17
DOI
https://doi.org/10.1109/uemcon62879.2024.10754777
Citations
1
Primary Topic
Stroke Rehabilitation and Recovery
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article
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article

Using Fitbit to Implement Personalized Walking Programs in Older Adults

Finkelstein Joseph, Te-Yi Tsai, Smiley Aref
1 citations
Stroke Rehabilitation and Recovery
0.25
article

Using Fitbit to Implement Personalized Walking Programs in Older Adults

Finkelstein Joseph, Te-Yi Tsai, Smiley Aref
article en
1 citations

Abstract

Walking is an accessible and popular form of physical activity (PA) among the elderly, providing significant health advantages, including better cardiovascular health, stability, and cognitive function. Personalized PA prescriptions tailored to the individual health needs of older adults can optimize these benefits.This study explores implementing personalized walking programs using Fitbit devices to monitor and prescribe PA in older adults. The Home Automated Telemanagement (HAT) system was developed to enable remote monitoring and management of PA through a user-friendly interface and robust backend system. The HAT system integrates the Fitbit login, prescription management, and automatic record functionalities, allowing healthcare providers to prescribe individualized walking programs, monitor adherence, and adjust prescriptions based on real-time data. Data from the Fitbit devices, including daily steps, heart rate, calories burned, and sleep patterns, are collected and analyzed. The HAT system’s automated features enable timely patient and clinician feedback, promoting adherence to PA prescriptions and supporting clinical decision-making. Alerts are generated when patients fail to meet prescribed activity levels, prompting clinician intervention.The successful deployment of the HAT system demonstrates its potential to enhance the management of PA in older adults, providing a scalable solution for improving health outcomes through personalized PA prescriptions. Further research will focus on incorporating additional health metrics, such as real-time monitoring, to enhance the system’s capabilities and address the unique needs of older populations.

University of Utah (US)
Openalex Percentile: Top 36%
Stroke Rehabilitation and Recovery
0.25
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Using Fitbit to Implement Personalized Walking Programs in Older Adults — Finkelstein Joseph, Te-Yi Tsai, et al. · (2024) | TGRS Research Map | TGRS