Mobile Phone Sensors Can Discern Medication-related Gait Quality Changes in Parkinson\u27s Patients in the Home Environment

Patients with Parkinson\u27s Disease (PD) experience daytime symptom fluctuations, which result in small amplitude, slow and unstable walking during times when medication attenuates. The ability to identify dysfunctional gait patterns throughout the day from raw mobile phone acceleration and gyroscope signals would allow the development of applications to provide real-time interventions to facilitate walking performance by, for example, providing external rhythmic cues. Patients (n = 20, mean Hoehn and Yahr: 2.25) had their ambulatory data recorded and were directly observed twice during one day: once after medication abstention, (OFF) and once approximately 30 min after intake of their medication (ON). Regularized generalized linear models (RGLM), neural networks (NN), and random forest (RF) classification models were individually trained for each participant. Across all subjects, our best performing classifier on average achieved an accuracy of 92.5%. This study demonstrated that smartphone accelerometers and gyroscopes can be used to distinguish between ON versus OFF times, potentially making smartphones useful intervention tools

Adaptations in Trunk-Pelvis Coordination Variability in Response to Fatiguing Exercise

Background During walking, variability in how movement is coordinated between body segments from stride to stride facilitates adaptation to changing environmental or task constraints. Magnitude of this inter-segmental coordination variability is reduced in patient populations and may also decrease in response to muscle fatigue. Previously, stride-to-stride variability has been quantified with the Vector Coding (VC) method, however recent research introduced a new Ellipse Area Method (EAM) to avoid statistical artifacts associated with VC. Research question Determine changes in trunk-pelvis coordination variability during walking turns in response to fatiguing exercise and to compare coordination variability quantified with VC to the EAM method. Methods 15 young adults (mean age: 23.7 (±3.2) years) performed 15 trials of a 90-degree walking turn before and after fatiguing paraspinal muscle exercise. Angular kinematics of the trunk and pelvis segments in the axial plane were quantified using three-dimensional motion capture. Stride to stride variability of axial coordination between the trunk and pelvis pre- and post-fatigue was calculated using both VC and EAM methods. Magnitudes of pre- and post-fatigue variability for VC and EAM were compared with paired t-tests and relationship between the magnitude of variability for the two methods was calculated using Pearson correlation coefficients. Results Using both analytical approaches, trunk-pelvis coordination variability decreased significantly post-fatiguing exercise across the stride cycle and within the stance phase of the turn (p \u3c 0.034 for all comparisons). Average magnitudes of variability calculated with VC and EAM were highly correlated. Time series cross correlations pre-post fatigue ranged from 0.81 to 0.98. Significance In healthy individuals, magnitude of trunk-pelvis stride-to-stride coordination variability is reduced following fatiguing exercise but the temporal distribution of variability across the stride cycle is maintained. This finding is robust to the method used to quantify coordination variability

Supplementary Material to the Manuscript Titled: Mobile Phone Sensors Can Discern Medication-Related Gait Quality Changes in Parkinson\u27s Patients in a Real-World Setting

This file contains the data that was used to classify high and low quality gait patterns in patients with Parkinson\u27s disease. Acceleration and gyroscope data was recorded with a conventional smartphone in a real-world environment. High (i.e. ON medication) and low (i.e. OFF medication) quality labels were given by a human observer according to medication intake times