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

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

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BORIS DOI
10.7892/boris.137333
Publisher DOI
10.3390/s19235169
PubMed ID
31779108
Description
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.
Date of Publication
2019-11-26
Publication Type
Article
Subject(s)
600 - Technology::610 - Medicine & health
Keyword(s)
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
Language(s)
en
Contributor(s)
Botros, Angela Amiraorcid-logo
ARTORG Center - Gerontechnology and Rehabilitation
Schütz, Narayan
ARTORG Center - Gerontechnology and Rehabilitation
Camenzind, Martin
Urwyler-Harischandra, Prabithaorcid-logo
ARTORG Center - Gerontechnology and Rehabilitation
Bolliger, Daniel
Vanbellingen, Tim
ARTORG Center - Gerontechnology and Rehabilitation
Kistler, Rolf
Bohlhalter, Stephan
Luzerner Kantonsspital, Departement Medizin, Luzern
Müri, René Martinorcid-logo
Department for BioMedical Research, Forschungsgruppe Neurologie
Universitätsklinik für Neurologie
Mosimann, Urs Peter
ARTORG Center - Gerontechnology and Rehabilitation
Nef, Tobiasorcid-logo
ARTORG Center - Gerontechnology and Rehabilitation
Additional Credits
Department for BioMedical Research, Forschungsgruppe Neurologie
ARTORG Center - Gerontechnology and Rehabilitation
Luzerner Kantonsspital, Departement Medizin, Luzern
Series
Sensors
Publisher
MDPI
ISSN
1424-8220
Access(Rights)
open.access
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