Long-Term Home-Monitoring Sensor Technology in Patients with Parkinson's Disease-Acceptance and Adherence.

Botros, Angela; Schütz, Narayan; Camenzind, Martin; Urwyler, Prabitha; Bolliger, Daniel; Vanbellingen, Tim; Kistler, Rolf; Bohlhalter, Stephan; Müri, René M.; Mosimann, Urs P.; Nef, Tobias (2019). Long-Term Home-Monitoring Sensor Technology in Patients with Parkinson's Disease-Acceptance and Adherence. Sensors, 19(23) Molecular Diversity Preservation International MDPI 10.3390/s19235169

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Parkinson's disease (PD) is characterized by a highly individual disease-profile as well as fluctuating symptoms. Consequently, 24-h home monitoring in a real-world environment would be an ideal solution for precise symptom diagnostics. In recent years, small lightweight sensors which have assisted in objective, reliable analysis of motor symptoms have attracted a lot of attention. While technical advances are important, patient acceptance of such new systems is just as crucial to increase long-term adherence. So far, there has been a lack of long-term evaluations of PD-patient sensor adherence and acceptance. In a pilot study of PD patients (N = 4), adherence (wearing time) and acceptance (questionnaires) of a multi-part sensor set was evaluated over a 4-week timespan. The evaluated sensor set consisted of 3 body-worn sensors and 7 at-home installed ambient sensors. After one month of continuous monitoring, the overall system usability scale (SUS)-questionnaire score was 71.5%, with an average acceptance score of 87% for the body-worn sensors and 100% for the ambient sensors. On average, sensors were worn 15 h and 4 min per day. All patients reported strong preferences of the sensor set over manual self-reporting methods. Our results coincide with measured high adherence and acceptance rate of similar short-term studies and extend them to long-term monitoring.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DCR Unit Sahli Building > Forschungsgruppe Neurologie
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Botros, Angela Amira; Schütz, Narayan; Urwyler-Harischandra, Prabitha; Vanbellingen, Tim; Bohlhalter, Stephan; Müri, René Martin; Mosimann, Urs Peter and Nef, Tobias

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1424-8220

Publisher:

Molecular Diversity Preservation International MDPI

Language:

English

Submitter:

Chantal Kottler

Date Deposited:

28 Jan 2020 12:33

Last Modified:

28 Jan 2020 12:33

Publisher DOI:

10.3390/s19235169

PubMed ID:

31779108

Uncontrolled Keywords:

Accelerometer PIR sensor Parkinson’s disease acceptance adherence ambient sensors body-worn sensors motor disorders patient monitoring remote sensing technology symptom assessment telemetry wearable electronic devices

BORIS DOI:

10.7892/boris.137333

URI:

https://boris.unibe.ch/id/eprint/137333

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