Use of Digital Biomarkers from Sensing Technologies to Explore the Relationship Between Daytime Activity Levels and Sleep Quality in Nursing Home Residents with Dementia: A Proof-of-Concept Study

Inactivity and increases in psychological and behavioral symptoms are common for people with dementia, and current assessment relies on proxy-rated tools. We investigate the feasibility and adherence of the use of sensor technology by exploring the relationship between daytime activity and sleep quality. For a total of 42 day-night data pairs in nursing home residents with dementia (N = 11), Garmin Vivoactive5 and Somnofy monitored continuous physical activity levels, sleep efficiency (SE), sleep score, sleep regularity index (SRI), and wake after sleep onset (WASO). Using the Spearman coefficient, we explored correlations between digital and proxy-rated tools (Personal Self Maintenance Scale (PSMS) and Neuropsychiatric Inventory-Nursing Home version (NPI-NH)) and the relationships between the digital biomarkers (SE, SRI, WASO, sleep score, physical activity). Participants (mean age 84 years) had moderate to severe degrees of dementia. Daytime activity levels correlated to sleep quality parameters WASO (-0.34, <i>p</i> = 0.03), and SRI (0.43, <i>p</i> = 0.01), and traditional sleep measures were associated with digital biomarkers (WASO/NPI-NH-K, <i>p</i> = 0.03). We found a relationship between daytime activity and sleep quality; however, the bidirectional relationship remains ambiguous and should be further investigated. The use of sensing technologies for people with dementia residing in a nursing home is feasible, although not without limitations, and has the potential to identify subtle changes, improving clinical assessment and the corresponding care recommendations.

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Journal
Sensors
Published
2025-10-29
DOI
https://doi.org/10.3390/s25216635
Citations
1
Primary Topic
Sleep and related disorders
Type
article
Field-Weighted Citation Impact
2.12

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article

Use of Digital Biomarkers from Sensing Technologies to Explore the Relationship Between Daytime Activity Levels and Sleep Quality in Nursing Home Residents with Dementia: A Proof-of-Concept Study

Lydia D. Boyle, Monica Pătraşcu, Brice Marty, Bettina S. Husebø et al.
1 citations
Sensors
Sleep and related disorders
2.12
article

Use of Digital Biomarkers from Sensing Technologies to Explore the Relationship Between Daytime Activity Levels and Sleep Quality in Nursing Home Residents with Dementia: A Proof-of-Concept Study

Lydia D. Boyle, Monica Pătraşcu, Brice Marty, Bettina S. Husebø, Kristoffer Haugarvoll, Ole Martin Steihaug
article en
1 citations

Abstract

Inactivity and increases in psychological and behavioral symptoms are common for people with dementia, and current assessment relies on proxy-rated tools. We investigate the feasibility and adherence of the use of sensor technology by exploring the relationship between daytime activity and sleep quality. For a total of 42 day-night data pairs in nursing home residents with dementia (N = 11), Garmin Vivoactive5 and Somnofy monitored continuous physical activity levels, sleep efficiency (SE), sleep score, sleep regularity index (SRI), and wake after sleep onset (WASO). Using the Spearman coefficient, we explored correlations between digital and proxy-rated tools (Personal Self Maintenance Scale (PSMS) and Neuropsychiatric Inventory-Nursing Home version (NPI-NH)) and the relationships between the digital biomarkers (SE, SRI, WASO, sleep score, physical activity). Participants (mean age 84 years) had moderate to severe degrees of dementia. Daytime activity levels correlated to sleep quality parameters WASO (-0.34, <i>p</i> = 0.03), and SRI (0.43, <i>p</i> = 0.01), and traditional sleep measures were associated with digital biomarkers (WASO/NPI-NH-K, <i>p</i> = 0.03). We found a relationship between daytime activity and sleep quality; however, the bidirectional relationship remains ambiguous and should be further investigated. The use of sensing technologies for people with dementia residing in a nursing home is feasible, although not without limitations, and has the potential to identify subtle changes, improving clinical assessment and the corresponding care recommendations.

SensorsVol. 25(21)
Haukeland University Hospital (NO), Haraldsplass Diakonale Sykehus (NO), University of Bergen (NO), Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Universitetet i Bergen, GC Rieber Fondene
Openalex Percentile: Top 10%
Sleep and related disorders
2.12
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