Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson's Disease.

Andrea Marcante,Roberto Di Marco,Alexandros Giannakis,Clelia Pellicano,Angelo Antonini,Spyridon Konitsiotis,Francesco Ernesto Pontieri,Dimitris Gatsios,Dimitrios I Fotiadis,Gianfranco Spalletta,Lucia Macchiusi,Giovanni Gentile,Maria Chondrogiorgi,Francesca Assogna

doi:10.3390/s21010128

Abstract

Freezing of Gait (FoG) is a common symptom in Parkinson’s Disease (PD) occurring with significant variability and severity and is associated with increased risk of falls. FoG detection in everyday life is not trivial, particularly in patients manifesting the symptom only in specific conditions. Various wearable devices have been proposed to detect PD symptoms, primarily based on inertial sensors. We here report the results of the validation of a novel system based on a pair of pressure insoles equipped with a 3D accelerometer to detect FoG episodes. Twenty PD patients attended a motor assessment protocol organized into eight multiple video recorded sessions, both in clinical and ecological settings and both in the ON and OFF state. We compared the FoG episodes detected using the processed data gathered from the insoles with those tagged by a clinician on video recordings. The algorithm correctly detected 90% of the episodes. The false positive rate was 6% and the false negative rate 4%. The algorithm reliably detects freezing of gait in clinical settings while performing ecological tasks. This result is promising for freezing of gait detection in everyday life via wearable instrumented insoles that can be integrated into a more complex system for comprehensive motor symptom monitoring in PD.

Highlights

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder, and its prevalence is increasing due to the population aging [1,2]
The aim of this study was to test a wearable system to automatically detect Freezing of Gait (FoG) episodes in PD patients, combining the analysis of foot pressure distributions and signals from a 3D accelerometer to be used in everyday life to detect the presence or absence of FoG
Even if they used a different approach in data analysis and not a 3D accelerometer to complement the pressure data, the authors demonstrated that their system was sensitive to various freezing with results obtained from only 24 FoG episodes

Summary

Introduction

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder, and its prevalence is increasing due to the population aging [1,2]. The efficacy of pharmacological therapy progressively reduces along the disease course, leading to motor and non-motor fluctuations. Medical visits typically occur with a several week interval, limiting the possibility to capture Freezing of Gait (FoG). As the disease progresses, FoG becomes less sensitive to drug therapies, and despite their careful management, advanced treatment (i.e., deep brain stimulation, DuodopaTM), and personalized rehabilitation therapies, people experiencing FoG are often exposed to falls and fall-related injuries [4,5,6]. Brief, and frequently linked to the OFF phase, FoG episodes do not necessarily and spontaneously occur during neurological examinations in scheduled visits. It is difficult to correctly evaluate FoG severity and impact on daily life activities

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