title: Utilizing a Wristband Sensor to Measure the Stress Level for People with Dementia.
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.
authors.affiliation: Department of Health Sciences, Luleå University of Technology, 97187 Luleå, Sweden. basel.kikhia@ltu.se.
authors.forename: Basel
authors.initials: B
authors.lastname: Kikhia
authors.affiliation: Information Technologies Institute, Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece. athstavr@iti.gr.
authors.forename: Thanos G
authors.initials: TG
authors.lastname: Stavropoulos
authors.affiliation: Information Technologies Institute, Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece. andreadisst@iti.gr.
authors.forename: Stelios
authors.initials: S
authors.lastname: Andreadis
authors.affiliation: Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, 97187 Luleå, Sweden. niklas.karvonen@ltu.se.
authors.forename: Niklas
authors.initials: N
authors.lastname: Karvonen
authors.affiliation: Information Technologies Institute, Centre for Research & Technology Hellas, 57001 Thessaloniki, Greece. ikom@iti.gr.
authors.forename: Ioannis
authors.initials: I
authors.lastname: Kompatsiaris
authors.affiliation: Department of Health Sciences, Luleå University of Technology, 97187 Luleå, Sweden. stefan.savenstedt@ltu.se.
authors.forename: Stefan
authors.initials: S
authors.lastname: Sävenstedt
authors.affiliation: Personal Health Solutions, Philips Research, 5656 AE Eindhoven, The Netherlands. marten.pijl@philips.com.
authors.forename: Marten
authors.initials: M
authors.lastname: Pijl
authors.affiliation: Department of Health Sciences, Luleå University of Technology, 97187 Luleå, Sweden. catharina.melander@ltu.se.
authors.forename: Catharina
authors.initials: C
authors.lastname: Melander
mesh_terms: D015374:Biosensing Techniques / Q000379:methods*; D003704:Dementia / Q000175:diagnosis*; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods*; D009735:Nursing Homes; D000076251:Wearable Electronic Devices
keywords: clinical assessment; dementia; nursing homes; sensors; stress monitoring