Author:
Zhang Wei,Yang Zhuokun,Li Hantao,Huang Debin,Wang Lipeng,Wei Yanzhao,Zhang Lei,Ma Lin,Feng Huanhuan,Pan Jing,Guo Yuzhu,Chan Piu
Abstract
AbstractFreezing of gaits (FOG) is a very disabling symptom of Parkinson’s Disease (PD), affecting about 50% of PD patients and 80% of advanced PD patients. Studies have shown that FOG is related to a complex interplay between motor, cognitive and affective factors. A full characterization of FOG is crucial for FOG detection/prediction and prompt intervention. A protocol has been designed to acquire multimodal physical and physiological information during FOG, including gait acceleration (ACC), electroencephalogram (EEG), electromyogram (EMG), and skin conductance (SC). Two tasks were designed to trigger FOG, including gait initiation failure and FOG during walking. A total number of 12 PD patients completed the experiments and produced a length of 3 hours and 42 minutes of valid data including 2 hours and 14 minutes of normal gait and 1 hour and 28 minutes of freezing of gait. The FOG episodes were labeled by two qualified physicians. The multimodal data have been validated by a FOG detection task.
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
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