Gait Parameters Change Prior to Freezing in Parkinson's Disease: A Data-Driven Study with Wearable Inertial Units

• Main Authors: Maria Laura Ferster, Sinziana Mazilu, Gerhard Tröster
• Format: Article
• Language: English
• Published: European Alliance for Innovation (EAI) 2015-12-01
• Series: EAI Endorsed Transactions on Ambient Systems
• Subjects: prediction; wearable sensors; freezing of gait; parkinson's disease; gait parameters; motor impairment analysis
• Online Access: http://eudl.eu/doi/10.4108/eai.28-9-2015.2261411

Freezing of gait (FoG) is a motor impairment among patients with advanced Parkinson's disease which is associated with falls and has a negative impact on a patient's quality of life. Wearable systems have been developed to detect FoG and to help patients resume walking by means of rhythmical cueing. A step further is to predict the FoG and start cueing a few seconds before it happens, which might help patients avoid the gait freeze entirely. We characterize the gait parameters continuously with up to 10-12 seconds prior to FoG, observe if and how they change before subjects enter FoG, and compare them with the gait before turns. Moreover, we introduce and discuss new frequency-based features to describe gait and motor anomalies prior to FoG. Using inertial units mounted on the ankles of 5 subjects, we show specific changes in the stride duration and length with up to four seconds prior to FoG on all subjects, compared with turns. Moreover, the dominant frequency migrates towards [3, 8] Hz band with up to six seconds prior to FoG on 3 subjects. These findings open the path to real-time prediction of FoG from inertial measurement units.