TY - JOUR
T1 - Foot pressure wearable sensors for freezing of gait detection in parkinson’s disease
AU - Marcante, Andrea
AU - Di Marco, Roberto
AU - Gentile, Giovanni
AU - Pellicano, Clelia
AU - Assogna, Francesca
AU - Pontieri, Francesco Ernesto
AU - Spalletta, Gianfranco
AU - Macchiusi, Lucia
AU - Gatsios, Dimitris
AU - Giannakis, Alexandros
AU - Chondrogiorgi, Maria
AU - Konitsiotis, Spyridon
AU - Fotiadis, Dimitrios I.
AU - Antonini, Angelo
N1 - Funding Information:
Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 643706 (PD_Manager project) and No. 825785 (PD_Pal project).
Publisher Copyright:
© 2020 by the authors.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - 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.
AB - 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.
KW - Accelerometer
KW - Freezing of gait
KW - Gait monitoring
KW - Insoles
KW - Parkinson’s disease
KW - Wearable device
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U2 - 10.3390/s21010128
DO - 10.3390/s21010128
M3 - Article
AN - SCOPUS:85098579400
VL - 21
SP - 1
EP - 12
JO - Sensors
JF - Sensors
SN - 1424-3210
IS - 1
M1 - 128
ER -