Utilizing a Wristband Sensor to Measure the Stress Level for People with Dementia

Basel Kikhia, Thanos G Stavropoulos, Stelios Andreadis, Niklas Karvonen, Ioannis Kompatsiaris, Stefan Sävenstedt, Marten Pijl, Catharina Melander, Basel Kikhia, Thanos G Stavropoulos, Stelios Andreadis, Niklas Karvonen, Ioannis Kompatsiaris, Stefan Sävenstedt, Marten Pijl, Catharina Melander

Abstract

Stress is a common problem that affects most people with dementia and their caregivers. Stress symptoms for people with dementia are often measured by answering a checklist of questions by the clinical staff who work closely with the person with the dementia. This process requires a lot of effort with continuous observation of the person with dementia over the long term. This article investigates the effectiveness of using a straightforward method, based on a single wristband sensor to classify events of "Stressed" and "Not stressed" for people with dementia. The presented system calculates the stress level as an integer value from zero to five, providing clinical information of behavioral patterns to the clinical staff. Thirty staff members participated in this experiment, together with six residents suffering from dementia, from two nursing homes. The residents were equipped with the wristband sensor during the day, and the staff were writing observation notes during the experiment to serve as ground truth. Experimental evaluation showed relationships between staff observations and sensor analysis, while stress level thresholds adjusted to each individual can serve different scenarios.

Keywords: clinical assessment; dementia; nursing homes; sensors; stress monitoring.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Philips DTI-2 wristband sensor.
Figure 2
Figure 2
An observation note filled in by the staff for a participant over a week.
Figure 3
Figure 3
The overall design of the study.
Figure 4
Figure 4
Class distribution in the dataset as a percentage of instances of stress reported in observation notes out of the total hours logged.
Figure 5
Figure 5
Performance metrics across different stress level thresholds.
Figure 6
Figure 6
Performance metrics of the personalized threshold method to optimize F-Measure, per each user.
Figure 7
Figure 7
Web application showing daily average stress level.
Figure 8
Figure 8
Dashboard for the clinicians to run analysis, setting a personalized stress level threshold (“Threshold”) for each user (anonymized drop-down menu) and time period (“From”–“To” fields).
Figure 9
Figure 9
View of High Stress level problems, according to personalized thresholds.

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Source: PubMed

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