TY - JOUR
T1 - Home-based monitoring of persons with advanced Parkinson’s disease using smartwatch-smartphone technology
AU - Fay-Karmon, Tsviya
AU - Galor, Noam
AU - Heimler, Benedetta
AU - Zilka, Asaf
AU - Bartsch, Ronny P.
AU - Plotnik, Meir
AU - Hassin-Baer, Sharon
N1 - Publisher Copyright:
© 2024, The Author(s).
PY - 2024/12
Y1 - 2024/12
N2 - Movement deterioration is the hallmark of Parkinson’s disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms’ variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations’ profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms’ levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations’ profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.
AB - Movement deterioration is the hallmark of Parkinson’s disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms’ variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations’ profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms’ levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations’ profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.
UR - http://www.scopus.com/inward/record.url?scp=85181243610&partnerID=8YFLogxK
U2 - 10.1038/s41598-023-48209-y
DO - 10.1038/s41598-023-48209-y
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C2 - 38167434
AN - SCOPUS:85181243610
SN - 2045-2322
VL - 14
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 9
ER -