Objective Quality of Life Detection Validation

Study Overview
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Brief Summary
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The purpose of this research study is to: Collect data to use in the development of a standardized tool for identifying patients with Parkinson's disease (PD) who would benefit from advanced therapies (AT) such as deep brain stimulation (DBS) and drug pumps. Determine the level to which specific activities reflect with quality of life in individuals with PD. Obtain feedback from individuals with Parkinson's disease and clinicians on the usability of the system.

Detailed Description
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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.

Official Title
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DiSCERN Phase I - Objective Quality of Life Detection Validation

Conditions
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Parkinson Disease

Intervention / Treatment
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* Device: Kinesia 360 and Smartphone sensors


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Able to provide informed consent Diagnosed with PD Hoehn and Yahr scale I-III Able to travel to Great Lakes NeuroTechnologies Ambulatory and capable of using the Kinesia 360 system Able to understand and follow instructions regarding using the device 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.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Parkinson's Disease<br>Parkinson's Disease patients | Device: Kinesia 360 and Smartphone sensors<br>* Data will be recorded from the Kinesia 360 system and smartphone sensors using the AWARE Framework.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Kinesia Symptom Scores during Daily Wear | Kinesia 360 scoring of Parkinson's Disease motor symptoms (tremor, slowness, dyskinesia, gait): The Kinesia 360 system translates recorded motion into 0-4 scores that correlate to rating scales used by clinicians (lower scores are signifiers of better outcomes and higher scores signify worse outcomes). A separate 0-4 score is generated for tremor, slowness, and dyskinesia, and gait is tracked for step count and percent of day walking. | Continuous during wear over four days | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| User environment audio activity | Using the AWARE Framework, the microphone in the smartphone will be used to measure ambient noise and detect conversation during wear. The output will be detection of conversation and ambient noise level for each recorded timepoint. The time involved in conversation and around active ambient noise will be compared to the symptom scores to measure user involvement in active environments as an impact on Parkinson's disease symptoms. | Continuous during wear over four days | 
| Patient physical activity | Using the AWARE Framework, accelerometers in the smartphone will be used to determine the activity of the user. The accelerometers will detect if the phone is being carried (using orientation of gravity) and predict most likely physical activity (using pre-existing activity recognition algorithms). The output will be predicted user activity for each timepoint recorded which will be correlated to Kinesia symptom scores. | Continuous during wear over four days | 
| Patient locations and travel | Using the AWARE Framework, Global Positioning System (GPS) tracking in the smartphone will be used to determine the locations and activity of the user. The GPS sensor will be used to track changes in location and determine when an user is at home (primary location), in a secondary location, or in active motion (car, bike, or walking). The outcome will be time spent in each location, percent of day at each location, and time and speed travelling between locations. These outcomes will be correlated to the Kinesia symptom scores and detected physical activity. | Continuous during wear over four days |