Coherence analysis for movement disorder motion captured by six degree-of-freedom inertial sensing

Abstract

The use of inertial sensors (accelerometer and gyroscopes) for evaluation of movement disorder motion, including essential tremor (ET) and Parkinson's disease (PD), is becoming prevalent. This paper uses a novel combination of six degree-of-freedom motion analysis and coherence based processing methodologies to uncover differences in the signature of motion for the ET and PD movement disorders. This is the first analysis of such motions utilizing the novel methodology outlined, and it displays a distinct motion profile differentiating between these two groups. Such an analysis can be used to assist medical professionals in diagnosing movement disorders given a currently high error rate of diagnosis. As well, the Kalman smoothing analysis performed in this paper can be quite useful for any application when tracking of human motion is required. Another contribution of the work is the use of wavelets in zero phase lag filtering, which helped in preparing the data for analysis by removing unwanted frequencies without introducing distortions into the data.