Clinicians experience difficulties in adjusting medications in individuals with Parkinson’s disease as the disease progresses and patients experience changes in the severity of symptoms between dosages, known as “on” and “off” times. These fluctuations can span several hours, making it difficult for clinicians to observe changes in the severity of symptoms during a routine visit. Patient diaries are often used but are very subjective. These problems could be addressed by developing technology to monitor individuals with Parkinson’s disease in their home.
The study aims to develop a Web-based system to monitor subjects in their homes with miniature sensors attached to the body to capture movement characteristics associated with parkinsonian symptoms. Sensors capture data about movements that can be compared to scores generated by neurologists and used to measure the severity of Parkinson’s symptoms. The Web-based system will provide videoconferencing capability, access to data recorded from the sensors and software to analyze data recorded in order to generate estimates of the severity of parkinsonian symptoms.
Relevance to Diagnosis/Treatment of Parkinson’s Disease:
In routine care, using data recorded in the home environment might facilitate adjusting medications to minimize fluctuations. Another important application would be for use in randomized clinical trials. By gathering objective and sensitive measures of symptoms, one could potentially reduce the number of subjects required to observe an effect in a trial of a new therapy.
The project will provide the first Web-based system to remotely access sensor data recorded from individuals with Parkinson’s disease in combination with video information and subjective patient and clinician input concerning the severity of their symptoms. The project will also deliver methods to interpret the data gathered in order to supply information to clinicians about “on” and “off” times.
The project has achieved encouraging results toward developing technology that could be used in the near future to facilitate the clinical management of patients with late stage Parkinson’s disease via home monitoring of the severity of symptoms. Dr. Bonato and colleagues envision that miniature sensors with wireless capability would be attached to the skin like adhesive bandages and that data would be gathered via a web-based application that would allow one to capture sensors data via the Internet. To derive clinically relevant information from the sensor data, the research team has developed dedicated algorithms that provide estimates of the severity of Parkinsonian symptoms using metrics that clinicians utilize in their clinical practice (i.e. Unified Parkinson’s Disease Rating Scale). During year two of the project, the team will assess the ability of the methodologies developed so far to track longitudinal changes in the severity of symptoms in patients with late stage Parkinson’s disease.