health life sciences medicine
Parkinson’s disease (PD) is the second-most common neurodegenerative disorder, while incidence and worldwide burden are further increasing. In the era of digital health transformation, smart devices and mobile sensors, including smartphones and smartwatches, can provide an affordable source to capture and analyse digital objective biomarkers. These can aid in early diagnosis and studying phenotypical characteristics. The Parkinson’s Disease Smartwatch (PADS) dataset comprises clinical assessments of a broad spectrum of PD patients, other similar movement disorders and healthy controls. The assessments were recorded using a smart-device-based system consisting of two smartwatches and one smartphone. The two smartwatches were worn on each of the patient’s wrists and their sensors synchronously recorded 11 interactive movement tasks that were designed by expert neurologists to provoke subtle changes in movement pathologies. In total, 5159 measurement steps of 469 individuals were captured. The PADS dataset includes all acceleration and rotation sensor signals, as well as details on movement steps, demographics, medical history, and PD-specific non-motor symptoms. We believe that our extensively annotated dataset provides a well-suited data foundation for the training, validation, and optimisation of future technology- and sensor-driven systems for movement disorders.
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License
https://doi.org/10.13026/m0w9-zx22
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PADS - Parkinsons Disease Smartwatch dataset was accessed on DATE from https://registry.opendata.aws/parkinsons-disease-smartwatch.
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