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Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease
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. Vari...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794778/ https://www.ncbi.nlm.nih.gov/pubmed/33379174 http://dx.doi.org/10.3390/s21010128 |
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author | Marcante, Andrea Di Marco, Roberto Gentile, Giovanni Pellicano, Clelia Assogna, Francesca Pontieri, Francesco Ernesto Spalletta, Gianfranco Macchiusi, Lucia Gatsios, Dimitris Giannakis, Alexandros Chondrogiorgi, Maria Konitsiotis, Spyridon Fotiadis, Dimitrios I. Antonini, Angelo |
author_facet | Marcante, Andrea Di Marco, Roberto Gentile, Giovanni Pellicano, Clelia Assogna, Francesca Pontieri, Francesco Ernesto Spalletta, Gianfranco Macchiusi, Lucia Gatsios, Dimitris Giannakis, Alexandros Chondrogiorgi, Maria Konitsiotis, Spyridon Fotiadis, Dimitrios I. Antonini, Angelo |
author_sort | Marcante, Andrea |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7794778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77947782021-01-10 Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease Marcante, Andrea Di Marco, Roberto Gentile, Giovanni Pellicano, Clelia Assogna, Francesca Pontieri, Francesco Ernesto Spalletta, Gianfranco Macchiusi, Lucia Gatsios, Dimitris Giannakis, Alexandros Chondrogiorgi, Maria Konitsiotis, Spyridon Fotiadis, Dimitrios I. Antonini, Angelo Sensors (Basel) Article 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. MDPI 2020-12-28 /pmc/articles/PMC7794778/ /pubmed/33379174 http://dx.doi.org/10.3390/s21010128 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Marcante, Andrea Di Marco, Roberto Gentile, Giovanni Pellicano, Clelia Assogna, Francesca Pontieri, Francesco Ernesto Spalletta, Gianfranco Macchiusi, Lucia Gatsios, Dimitris Giannakis, Alexandros Chondrogiorgi, Maria Konitsiotis, Spyridon Fotiadis, Dimitrios I. Antonini, Angelo Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease |
title | Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease |
title_full | Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease |
title_fullStr | Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease |
title_full_unstemmed | Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease |
title_short | Foot Pressure Wearable Sensors for Freezing of Gait Detection in Parkinson’s Disease |
title_sort | foot pressure wearable sensors for freezing of gait detection in parkinson’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794778/ https://www.ncbi.nlm.nih.gov/pubmed/33379174 http://dx.doi.org/10.3390/s21010128 |
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