Developing Technology for Nursing Home Implementation: An Engineering and Social Science Collaboration

Abstract Although temperature, light, and noise are known to be key factors for a good night’s sleep, they are difficult to measure in the nursing home. We report on a multidisciplinary collaboration (engineering, psychology, nursing, social work) to develop a flexible, unobtrusive, and affordable a measurement solution feasible for nursing home use. We piloted commercially available instruments that measured volume and light in two nursing homes. We trialed different solutions for powering these devices, downloading the data, and placing the devices in resident rooms and common areas. We concluded that commercially available instruments were too large, noticeable, and expensive. We found that: 1) large noticeable microphones led to privacy concerns even though the devices were only measuring sound levels and were not recording; 2) strategic and customized device placement was key to success – in some resident rooms devices did best when placed above doors, and in other resident rooms the device could be successfully placed on a piece of furniture like a chest of drawers; 3) connecting to nursing home wifi was not typically possible, so data download solutions that relied on removable memory cards worked best. Based on pilot work, the second and third authors developed a small bespoke device on a raspberry pi platform that is wall mountable with heavy-duty Velcro and measures sound, temperature, and light using removable SD memory cards and has both battery and AC power options. The device is being used to supplement wrist actigraph/light meters. We report on nursing home feasibility and acceptability.

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Publication Details

Journal
Innovation in Aging
Published
2025-12-01
DOI
https://doi.org/10.1093/geroni/igaf122.2061
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
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article

Developing Technology for Nursing Home Implementation: An Engineering and Social Science Collaboration

Todd J. Freeborn, Karen Lim, Vanessa Aguilar, Brian S. Cox et al.
Innovation in Aging
Context-Aware Activity Recognition Systems
article

Developing Technology for Nursing Home Implementation: An Engineering and Social Science Collaboration

Todd J. Freeborn, Karen Lim, Vanessa Aguilar, Brian S. Cox, Hope Carwile, A Lynn Snow
article en

Abstract

Abstract Although temperature, light, and noise are known to be key factors for a good night’s sleep, they are difficult to measure in the nursing home. We report on a multidisciplinary collaboration (engineering, psychology, nursing, social work) to develop a flexible, unobtrusive, and affordable a measurement solution feasible for nursing home use. We piloted commercially available instruments that measured volume and light in two nursing homes. We trialed different solutions for powering these devices, downloading the data, and placing the devices in resident rooms and common areas. We concluded that commercially available instruments were too large, noticeable, and expensive. We found that: 1) large noticeable microphones led to privacy concerns even though the devices were only measuring sound levels and were not recording; 2) strategic and customized device placement was key to success – in some resident rooms devices did best when placed above doors, and in other resident rooms the device could be successfully placed on a piece of furniture like a chest of drawers; 3) connecting to nursing home wifi was not typically possible, so data download solutions that relied on removable memory cards worked best. Based on pilot work, the second and third authors developed a small bespoke device on a raspberry pi platform that is wall mountable with heavy-duty Velcro and measures sound, temperature, and light using removable SD memory cards and has both battery and AC power options. The device is being used to supplement wrist actigraph/light meters. We report on nursing home feasibility and acceptability.

Innovation in AgingVol. 9(Supplement_2)
Colorado Christian University (US), University of Alabama (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 33%
Context-Aware Activity Recognition Systems
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