| Literature DB >> 33379174 |
Andrea Marcante1, Roberto Di Marco2, Giovanni Gentile2,3, Clelia Pellicano4,5, Francesca Assogna4, Francesco Ernesto Pontieri4,6, Gianfranco Spalletta4, Lucia Macchiusi4, Dimitris Gatsios7,8, Alexandros Giannakis8, Maria Chondrogiorgi8, Spyridon Konitsiotis8, Dimitrios I Fotiadis7, Angelo Antonini2.
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.Entities:
Keywords: Parkinson’s disease; accelerometer; freezing of gait; gait monitoring; insoles; wearable device
Mesh:
Year: 2020 PMID: 33379174 PMCID: PMC7794778 DOI: 10.3390/s21010128
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.576