The objective is to build and clinically assess PDRemote, a system for automated telehealth diagnostics for remote Parkinson's disease (PD) monitoring. Currently in the United States, there are approximately 1.5 million patients living wit PD and 50,000 new cases reported each year. However, there is limited access to movement disorder specialist centers for a significant portion of this population as well as limited opportunity for remote continuous monitoring of motor symptoms to capture complex fluctuation patterns and optimize treatment protocols. PD is characterized by tremors of the fingers, hands, head, and neck, bradykinesia (slowed movements), and rigidity of musculature. Treatments include pharmaceutical interventions such as levodopa and surgical procedures such as deep brain stimulation (DBS). It is important to accurately quantify motor function and disability in PD to assess intervention efficacy. Currently, subjective clinical rating scales, most commonly the Unified Parkinson's Disease Rating Scale (UPDRS), are used to show clinical improvement in PD. While the UPDRS has shown clinical utility, it requires presence of a clinician for scoring and only obtains a snapshot of symptoms during a clinical office visit. Furthermore, access to movement disorder specialists for effective motor symptom monitoring and management is critical for a geographically disparate subset of the PD population or those unable to travel. The location of movement disorder centers can limit access to well-trained clinicians and effective symptom management for many PD patients. Telehealth technologies that can improve access for these patients can have a significant impact on the equity, accessibility, and management of the condition for remote patients or those unable to travel. PDRemote will provide remote, automated, motor symptom severity scoring to accurately quantify intervention effectiveness and limit the required number of office visits for treatment adjustments, thereby improving outcomes and decreasing costs for disparate patient populations. PD patients will be sent home with patient kit including an ergonomically designed touch-screen tablet PC, intuitive software interface for diaries, and a wireless motion sensor unit. Data collected from home sessions will be wirelessly transmitted to an online database that generates a motor symptom severity report for clinicians to review via a web-based interface and video conference with a patient to make appropriate medication changes. Feasibility was demonstrated in Phase I by patients successfully using the patient kit in the home to perform motor assessments and clinicians successfully using the web-based application to prescribe tests and view reports. Phase II will further improve ergonomics, data transfer, reporting capabilities, and result in a clinically deployable technology. The system will be employed in a multi-center clinical trial to determine if using the system can reduce fluctuations, decrease office visits, and improve patient outcomes.

Public Health Relevance

Parkinson's disease is primarily characterized by motor symptoms of tremor, bradykinesia (slowed movements), and rigidity which can be very debilitating, leading to decreased mobility, independence, and quality of life. Clinicians lack quantitative tools for more continuous monitoring that capture how motor symptoms fluctuate during the day in response to treatment protocols to help minimize Parkinson's motor symptoms. PDRemote will be a repeatable, automated system clinicians will use to remotely monitor PD motor symptoms on a more continuous basis in a patient's home that should improve outcomes and decrease costs especially for disparate patient populations in areas not in close proximity to movement disorder specialists.

National Institute of Health (NIH)
National Institute on Minority Health and Health Disparities (NIMHD)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZEB1-OSR-B (M1))
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Tabor, Derrick C
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Great Lakes Neurotechnologies
Valley View
United States
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Heldman, Dustin A; Harris, Denzil A; Felong, Timothy et al. (2017) Telehealth Management of Parkinson's Disease Using Wearable Sensors: An Exploratory Study. Digit Biomark 1:43-51