Distinguishing Medication ON and OFF for Parkinson’s Disease Through Repetitive Foot Motion Recognition and Analysis

As Parkinson’s disease (PD) progresses, patients experience difficult times to distinguish their medication effective (ON) and non-effective (OFF) periods, due to subjective judgements on observations of motor symptoms and self-recording in diaries. Thus, a simple-to-use tool to objectively identify and record ON and OFF in daily life is in great need. This study proposes a method to distinguish medication ON and OFF for PD patients through 4 repetitive foot motions– toe tapping, heel tapping, toe pivoting and heel pivoting by wearing a pair of monitoring insoles (MONI). After collecting data from 16 patients and 9 age-matched healthy controls, we extract over 1200 features from all repetitive foot motions and provides comprehensive analytical results of feature importance with Analysis on Variance (ANOVA). Then, we use Random Forest Classifier to first identify foot motions through motion recognition and then extract features to distinguish ON and OFF. Through evaluation on 2-month long data collected from 5 individual patients, we identify motions performed mistakenly by one patient during an experimental session and show 85% ON
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OFF distinguishment accuracy for the rest 20 sessions, compared to 60% accuracy from a baseline model referencing to observation judgement in clinical tests. The proposed method and experimental procedures can be transformed into an assistant tool, including an application (APP) and MONI, as a potential solution to help patients with Parkinson’s disease understand and objectively record their medication effectiveness in daily life.