Parkinson’s disease (PD) is a neurodegenerative disease that can affect a person’s movement, speech, dexterity, and cognition. Physicians primarily diagnose Parkinson’s disease by performing a clinical assessment of symptoms. One factor that contributes to misdiagnoses is that the symptoms of Parkinson’s disease may not be prominent during the clinical assessment. Furthermore, the clinical assessments can be cumbersome and subjective. We have developed a mobile app that integrates several tests using integrated sensors. We have recorded high resolution data from PD patients to investigate in detail the performance these tests.
The goal of this work is to analyse the sensor data, extract salient information, and develop algorithms to automate this process so it can be integrated into future devices.