Potential of Ambient Sensor Systems for Early Detection of Health Problems in Older Adults

Hugo Saner, Narayan Schütz, Angela Botros, Prabitha Urwyler, Philipp Buluschek, Guillaume du Pasquier, Tobias Nef, Hugo Saner, Narayan Schütz, Angela Botros, Prabitha Urwyler, Philipp Buluschek, Guillaume du Pasquier, Tobias Nef

Abstract

Background: Home monitoring sensor systems are increasingly used to monitor seniors in their apartments for detection of emergency situations. The aim of this study was to deliver a proof-of-concept for the use of multimodal sensor systems with pervasive computing technology for the detection of clinically relevant health problems over longer time periods. Methods: Data were collected with a longitudinal home monitoring study in Switzerland (StrongAge Cohort Study) in a cohort of 24 old and oldest-old, community-dwelling adults over a period of 1 to 2 years. Physical activity in the apartment, toilet visits, refrigerator use, and entrance door openings were quantified using a commercially available passive infrared motion sensing system (Domosafety S.A., Switzerland). Heart rate, respiration rate, and sleep quality were recorded with the commercially available EMFIT QS bed sensor device (Emfit Ltd., Finland). Vital signs and contextual data were collected using a wearable sensor on the upper arm (Everion, Biovotion, Switzerland). Sensor data were correlated with health-related data collected from the weekly visits of the seniors by health professionals, including information about physical, psychological, cognitive, and behavior status, health problems, diseases, medication, and medical diagnoses. Results: Twenty of the 24 recruited participants (age 88.9 ± 7.5 years, 79% females) completed the study; two participants had to stop their study participation because of severe health deterioration, whereas two participants died during the course of the study. A history of chronic disease was present in 12/24 seniors, including heart failure, heart rhythm disturbances, pulmonary embolism, severe insulin-dependent diabetes, and Parkinson's disease. In total, 242,232 person-hours were recorded. During the monitoring period, 963 health status records were reported and repeated clinical assessments of aging-relevant indicators and outcomes were performed. Several episodes of health deterioration, including heart failure worsening and heart rhythm disturbances, could be captured by sensor signals from different sources. Conclusions: Our results indicate that monitoring of seniors with a multimodal sensor and pervasive computing system over longer time periods is feasible and well-accepted, with a great potential for detection of health deterioration. Further studies are necessary to evaluate the full range of the clinical potential of these findings.

Keywords: ambient motion sensors; heart failure; older adults; pervasive computing; preventive health information; rhythm disturbances; safety.

Copyright © 2020 Saner, Schütz, Botros, Urwyler, Buluschek, du Pasquier and Nef.

Figures

Figure 1
Figure 1
Data collection procedures for 24 old and oldest-old adults in the StrongAge Cohort Study.
Figure 2
Figure 2
This is a case of a 97-year-oldest-old community-dwelling senior with recurrent pulmonary embolism and progressive right heart failure decompensation. The dynamics of different measurements are shown over a period of 5 months: hand grip strength and performance in the Time Up and Go (TUG) test during clinical assessments (A); signals from the Emfit bed sensor indicating the heart rate, respiration rate, and motion in bed (B); and signals from the passive infrared motion sensors indicating the total physical activity and the room transition time as indicator for walking speed (C). (A) Results of hand-grip measurements (left) and TUG test (right). (B) Physical activity per day (left) and median room transition duration (right). (C) Results from Emfit bed sensor indicating the nightly heart rate (upper left), heart rate variability (upper right), number of leg movements in bed (lower left), and respiration rate (lower right).
Figure 3
Figure 3
Emfit bed sensor recordings of episodes with increased heart rate between 04:00 and 05:00. This increase of heart rate corresponds well with the complaints of the senior about tachycardia with palpitations during early morning hours.

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