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Article

AI-Assisted In-House Power Monitoring for the Detection of Cognitive Impairment in Older Adults

1
Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan
2
Division of Epidemiology, Kobe University Graduate School of Medicine, Kobe 650-0017, Japan
3
Department of Neurology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan
4
National Cerebral and Cardiovascular Center, Suita 564-8565, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Agostino Forestiero
Sensors 2021, 21(18), 6249; https://doi.org/10.3390/s21186249
Received: 30 August 2021 / Revised: 13 September 2021 / Accepted: 14 September 2021 / Published: 17 September 2021
In-home monitoring systems have been used to detect cognitive decline in older adults by allowing continuous monitoring of routine activities. In this study, we investigated whether unobtrusive in-house power monitoring technologies could be used to predict cognitive impairment. A total of 94 older adults aged ≥65 years were enrolled in this study. Generalized linear mixed models with subject-specific random intercepts were used to evaluate differences in the usage time of home appliances between people with and without cognitive impairment. Three independent power monitoring parameters representing activity behavior were found to be associated with cognitive impairment. Representative values of mean differences between those with cognitive impairment relative to those without were −13.5 min for induction heating in the spring, −1.80 min for microwave oven in the winter, and −0.82 h for air conditioner in the winter. We developed two prediction models for cognitive impairment, one with power monitoring data and the other without, and found that the former had better predictive ability (accuracy, 0.82; sensitivity, 0.48; specificity, 0.96) compared to the latter (accuracy, 0.76; sensitivity, 0.30; specificity, 0.95). In summary, in-house power monitoring technologies can be used to detect cognitive impairment. View Full-Text
Keywords: power monitoring; in-house monitoring; cognitive impairment; dementia power monitoring; in-house monitoring; cognitive impairment; dementia
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MDPI and ACS Style

Nakaoku, Y.; Ogata, S.; Murata, S.; Nishimori, M.; Ihara, M.; Iihara, K.; Takegami, M.; Nishimura, K. AI-Assisted In-House Power Monitoring for the Detection of Cognitive Impairment in Older Adults. Sensors 2021, 21, 6249. https://doi.org/10.3390/s21186249

AMA Style

Nakaoku Y, Ogata S, Murata S, Nishimori M, Ihara M, Iihara K, Takegami M, Nishimura K. AI-Assisted In-House Power Monitoring for the Detection of Cognitive Impairment in Older Adults. Sensors. 2021; 21(18):6249. https://doi.org/10.3390/s21186249

Chicago/Turabian Style

Nakaoku, Yuriko, Soshiro Ogata, Shunsuke Murata, Makoto Nishimori, Masafumi Ihara, Koji Iihara, Misa Takegami, and Kunihiro Nishimura. 2021. "AI-Assisted In-House Power Monitoring for the Detection of Cognitive Impairment in Older Adults" Sensors 21, no. 18: 6249. https://doi.org/10.3390/s21186249

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