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The purpose of this research study is to:
Full description
The investigators aim to develop a standardized tool for identifying patients with Parkinson's disease (PD) who would benefit from advanced therapies (AT) and identify when AT recipients are in need of a therapy adjustment. This system will integrate ambulatory PD monitoring with context aware activity detection as the daily activities a patient performs are often the best predictors of quality of life (QoL). In this study the Kinesia 360 system will collect motion data to measure tremor, bradykinesia (slow movement), and dyskinesia (involuntary movements) from individuals with PD to track their symptoms throughout the day. A smartphone will collect information on subject location and activity using the GPS, accelerometers, and microphone within the phone to find correlations between activity and patient wellness. This data will be used to improve detection over time and predict whether patients are candidates for advanced therapies.
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Exclusion criteria
Any subject that does not meet the subject selection criteria will be excluded from this study. Children will be excluded from this study due to the fact that they are unlikely to have PD. Subjects that are not capable of functioning independently or are so symptomatic as to compromise their safety will also be excluded.
10 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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