Botros, Angela AmiraAngela AmiraBotros0000-0002-1245-2931Schütz, NarayanNarayanSchützCamenzind, MartinMartinCamenzindUrwyler-Harischandra, PrabithaPrabithaUrwyler-Harischandra0000-0002-7641-8898Bolliger, DanielDanielBolligerVanbellingen, TimTimVanbellingenKistler, RolfRolfKistlerBohlhalter, StephanStephanBohlhalterMüri, René MartinRené MartinMüri0000-0001-6990-4188Mosimann, Urs PeterUrs PeterMosimannNef, TobiasTobiasNef0000-0002-8069-94502024-11-242024-11-242019-11-26https://boris-portal.unibe.ch/handle/20.500.12422/190443Parkinson'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.enAccelerometer PIR sensor Parkinson’s disease acceptance adherence ambient sensors body-worn sensors motor disorders patient monitoring remote sensing technology symptom assessment telemetry wearable electronic devices600 - Technology::610 - Medicine & healtharticle10.7892/boris.1373333177910810.3390/s19235169