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Scientific data · 2021

Accelerometer data collected with a minimum set of wearable sensors from subjects with Parkinson's disease.

DatasetСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Daneault Jean-Francois, Vergara-Diaz Gloria, Parisi Federico, Admati Chen, Alfonso Christina, Bertoli Matilde, Bonizzoni Edoardo, Carvalho Gabriela Ferreira, Costante Gianluca, Fabara Eric Eduardo, Fixler Naama, Golabchi Fatemah Noushin, Growdon John, Sapienza Stefano, Snyder Phil, Shpigelman Shahar, Sudarsky Lewis, Daeschler Margaret, Bataille Lauren, Sieberts Solveig K, Omberg Larsson, Moore Steven, Bonato Paolo

Аннотация

Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты