New sensing devices can generate objective, frequent, sensitive assessments of PD. However, many devices, like smartphones, require individuals to complete activities. Because PD, unlike colon cancer, for example, has clear external features (e.g., slow gait, frequent sleep interruptions), it is well suited for passive assessment. In Research Project 4, we will evaluate three leading technologies to assess PD principally (but not exclusively) through passive means. These technologies include wearable sensors that can measure motor and autonomic function, a video analytical tool that can measure elements of the standard PD motor examination, and an ?invisible? radio wave sensing tool that can assess the natural history of PD in the home. These three tools will enhance our understanding and generate objective measures of PD that can be used to accelerate therapeutic development and improve care. The first project will examine a wearable sensor that has embedded accelerometers, gyroscope, and ECG capabilities to assess function inside and outside the clinic. In one of the largest PD sensor studies, we will seek to confirm and extend findings that individuals with PD exhibit distinct diurnal activity patterns from controls (e.g., lie down more, walk less), evaluate autonomic function, and in partnership with the University of Michigan's Udall Center, explore whether gait function is worse in individuals with a hypocholinergic state. The second project will evaluate a recently developed video analytics tool that applies machine learning algorithms to evaluate motor assessments (e.g., facial expression, finger tapping) that are routinely assessed through the motor portion the MDS-UPDRS to see if these assessments, conducted without an investigator, can differentiate those with PD from those without and correlate with traditional assessments. The third project will evaluate motor and non-motor function of individuals with PD in their homes using a novel radio wave sensing device. This device can assess existing measures (e.g., gait speed, respiratory rate) and novel measures (e.g., path tortuosity, time alone) that will provide novel insights into the disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Specialized Center (P50)
Project #
1P50NS108676-01
Application #
9615385
Study Section
Special Emphasis Panel (ZNS1)
Project Start
Project End
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Rochester
Department
Type
DUNS #
041294109
City
Rochester
State
NY
Country
United States
Zip Code
14627