Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Gait Parameters Measured From Wearable Sensors Reliably Detect Freezing of Gait in a Stepping in Place Task

Version 1 : Received: 6 March 2021 / Approved: 8 March 2021 / Online: 8 March 2021 (16:15:41 CET)

A peer-reviewed article of this Preprint also exists.

Diep, C.; O’Day, J.; Kehnemouyi, Y.; Burnett, G.; Bronte-Stewart, H. Gait Parameters Measured from Wearable Sensors Reliably Detect Freezing of Gait in a Stepping in Place Task. Sensors 2021, 21, 2661. Diep, C.; O’Day, J.; Kehnemouyi, Y.; Burnett, G.; Bronte-Stewart, H. Gait Parameters Measured from Wearable Sensors Reliably Detect Freezing of Gait in a Stepping in Place Task. Sensors 2021, 21, 2661.

Journal reference: Sensors 2021, 21, 2661
DOI: 10.3390/s21082661

Abstract

Freezing of gait (FOG), a debilitating symptom of Parkinson’s disease (PD), can be safely studied using the stepping in place (SIP) task. However, clinical, visual identification of FOG during SIP is subjective and time consuming, and automatic FOG detection during SIP currently requires measuring center of pressure on dual force plates. This study examines whether FOG elicited during SIP in 10 individuals with PD could be reliably detected using kinematic data measured from wearable inertial measurement unit sensors (IMUs). A general, logistic regression model (AUC = 0.81) determined that three gait parameters together were overall the most robust predictors of FOG during SIP: arrhythmicity, swing time coefficient of variation, and swing angular range. Participant-specific models revealed varying sets of gait parameters that best predicted FOG for each participant, highlighting variable FOG behaviors, and demonstrated equal or better performance for 6 out of the 10 participants, suggesting the opportunity for model personalization. The results of this study demonstrated that gait parameters measured from wearable IMUs reliably detected FOG during SIP, and the general and participant-specific gait parameters allude to variable FOG behaviors that could inform more personalized approaches for treatment of FOG and gait impairment in PD.

Keywords

Parkinson’s disease; wearables; inertial measurement unit; sensors; freezing of gait

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