Aims and Hypothesis:
Here we propose to leverage the gait sub-study and add a watch to a subset of participants who are anticipated to return for their second gait assessment. Such addition will enable:
- Comparison between sensors and assessment of specific location metrics.
- Evaluation of multiple outcomes across disease stages through comparison to previously collected data.
- Opportunity for PPMI to evaluate a comprehensive digital biomarker platform, in one on-going sub-study.
Adding watch based monitoring to the existing lumbar sensor protocol would significantly enhance study value in the concepts of interests tailored to the desired context of use (pre-clinical) with minimal additional burden on participants or sites, maximizing the study's impact and translational potential.
Study Design:
30 participants in the gait sub study, who are scheduled for their second annual assessment will be approached to participate in this study. They will be asked to wear and Actrigraph watch on their preffered wrist for 7-14 days. Continoius data will be collected and uploaded via wi-fi connection in real time. The watch is water proof and does not need to be charged during this period. After the collection period, the participants will return the watch, together with the Axivity device to the sites for re-use.
Participants will be evaluated twice with the watch: on their second annual gait visit and 12 months later (3 annual gait visit). The data will then be processed and compared against the axivity to answer aim 1. We will also explore sensitivity metrics to disease stage as well as progression of these metrics across time.
Impact on Diagnosis/Treatment of Parkinson’s disease:
Parkinson’s symptoms vary significantly from person to person and can change day to day, moment to moment. This new technology has the potential to monitor changes in gait, sleep and autonomic function over time. Researchers will look for trends in the sensor data. These trends may help diagnose or track the progression of Parkinson’s disease even in pre-clinical stages. Researchers will also compare the sensor data with the PPMI tests you complete in person. This may help understand the relationship between biology and real-world motor symptoms of PD.
In addition, collecting data with wearable devices like the Axivity sensors and ActiGraph LEAP are a relatively new area of scientific research. These studies help researchers understand the challenges and opportunities in using wearable devices. With more information from studies like these, we can conduct more and better research.
Next Steps for Development:
The ultimate aim is to identify metrics that are sensitive and specific for PD progression, that could also be used in clinical trials to transform clinical research and health.