Parkinson's disease - overview
Parkinson's (PD) is a chronic, degenerative neurological disorder characterized by motor disturbances, such as involuntary tremors, bradykinesia (slowness of movement), rigidity (stiffness and resistance to passive movement), and gait and balance difficulties. It's estimated that over 1 million people live with the disease in the United States and more than 5 million people have Parkinson's worldwide. PD has no cure and available treatments are limited to managing symptoms and are primarily based on dopamine replacement therapy.
The current standard of care for PD patients is based on episodic assessment of their symptoms using the Movement Disorder Society’s Unified Parkinson’s Disease Rating Scale (or MDS-UPDRS). This scale includes multiple sections that cover all the different symptoms that a PD patient might experience. The evaluation is performed in-clinic by a trained physician based on patient interviews and clinical observations. The resulting score is used by clinicians to monitor a patient’s disease progression but also, as part of clinical trials, as an endpoint to prove the effectiveness of new therapies.
Another commonly used measure is the Hauser diary, which is basically a motor diary that a PD patient needs to keep for several days and report every 30 minutes on their condition. Both these measures have known biases and as a consequence are not very accurate. Another issue is their intrinsic “episodic” nature which fails to capture day-to-day fluctuations of motor symptoms.
The goal of this project is to continuously monitor motor symptoms of PD patients without requiring them to go to a clinical consultation or even perform specific tasks. To this end we employ fixed and wearable sensor technologies that can capture in real-time movement features of subjects as they go about their day doing work around their house, cooking, cleaning, etc. To evaluate these new technologies, we are actively collecting data from PD patients in both their home environment and in the clinic.
While our initial focus is on Parkinson’s, similar technologies might be applied to different disease areas where patients experience certain motor symptoms (e.g. Alzheimer’s) or to monitor rehabilitation after accidents or even elder care.