Objective Quality of Life Detection Validation
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|ClinicalTrials.gov Identifier: NCT04121793|
Recruitment Status : Recruiting
First Posted : October 10, 2019
Last Update Posted : October 10, 2019
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.
|Condition or disease||Intervention/treatment|
|Parkinson Disease||Device: Kinesia 360 and Smartphone sensors|
|Study Type :||Observational|
|Estimated Enrollment :||20 participants|
|Official Title:||DiSCERN Phase I - Objective Quality of Life Detection Validation|
|Actual Study Start Date :||September 20, 2019|
|Estimated Primary Completion Date :||March 1, 2020|
|Estimated Study Completion Date :||March 1, 2020|
Parkinson's Disease patients
Device: Kinesia 360 and Smartphone sensors
Data will be recorded from the Kinesia 360 system and smartphone sensors using the AWARE Framework.
- Kinesia Symptom Scores during Daily Wear [ Time Frame: Continuous during wear over four days ]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.
- User environment audio activity [ Time Frame: Continuous during wear over four days ]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.
- Patient physical activity [ Time Frame: Continuous during wear over four days ]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.
- Patient locations and travel [ Time Frame: Continuous during wear over four days ]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.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04121793
|Contact: Aaron J Hadley, PhD||(216) firstname.lastname@example.org|
|Contact: Dustin Heldman, PhDemail@example.com|
|United States, Ohio|
|Great Lakes NeuroTechnologies||Recruiting|
|Cleveland, Ohio, United States, 44131|
|Contact: Aaron J Hadley, PhD 216-446-2452 firstname.lastname@example.org|
|Contact: Dustin Heldman, PhD 216-361-5410 email@example.com|
|Principal Investigator:||Dustin Heldman, PhD||Director of Research|