Effect of Parkinsonism on Proximal Unstructured Movement Captured by Inertial Sensors.

Abstract

In this study, we endeavour to measure characteristic movements of patients with Parkinson's disease (PD). Our eventual aim is to obtain the severity of these exhibited movements entirely based on measurements conducted in un-clinical environments. Indeed, we investigate the feasibility of capturing such un-structured movements using wearable sensors. In particular, as Bradykinesia and axial Bradykinesia are vital characteristics yet challenging to measure, we design a test system of Inertial Measurement (IM) based wearable sensors in order to capture the affected movements of the back. The study evaluated the characteristics of PD patients during the unstructured activities. Our analysis captured back flexibility based on frequency information of the sensors attached to the human back. Satisfactory classification in each test confirms that this testing system can identify as well as evaluate PD patients using a minimal number of sensors during these unstructured movements. Our objective is to enhance the uptake and promote the use of wearable sensors in longer term monitoring scenarios relevant to non-clinical environments. Thus, we envisage clinicians monitoring the progress due to the treatment of patients residing in their homes assisted by sensors with enhanced wearability.