Automatic Identification and Classification of Freezing of Gait Episodes in Parkinson's Disease Patients

被引:55
作者
Djuric-Jovicic, Milica D. [1 ]
Jovicic, Nenad S. [2 ]
Radovanovic, Sasa M. [3 ]
Stankovic, Iva D. [4 ]
Popovic, Mirjana B. [2 ]
Kostic, Vladimir S. [4 ]
机构
[1] Univ Belgrade, Sch Elect Engn, Innovat Ctr, Belgrade 11000, Serbia
[2] Univ Belgrade, Sch Elect Engn, Belgrade 11000, Serbia
[3] Inst Med Res, Belgrade 11000, Serbia
[4] Clin Ctr Serbia, Fac Med, Neurol Clin, Belgrade 11000, Serbia
关键词
Freezing of gait (FOG); gait analysis; gait disturbances; inertial sensors; Parkinson's disease (PD); MOBILITY; SENSORS;
D O I
10.1109/TNSRE.2013.2287241
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Alternation of walking pattern decreases quality of life and may result in falls and injuries. Freezing of gait (FOG) in Parkinson's disease (PD) patients occurs occasionally and intermittently, appearing in a random, inexplicable manner. In order to detect typical disturbances during walking, we designed an expert system for automatic classification of various gait patterns. The proposedmethod is based on processing of data obtained from an inertial sensor mounted on shank. The algorithm separates normal from abnormal gait using Pearson's correlation and describes each stride by duration, shank displacement, and spectral components. A rule-based data processing classifies strides as normal, short short or very short short strides, FOG with tremor FOG or FOG with complete motor block FOG. The algorithm also distinguishes between straight and turning strides. In 12 PD patients, FOG and FOG were identified correctly in 100% of strides, while normal strides were recognized in 95% of cases. Short and short strides were identified in about 84% and 78%. Turning strides were correctly identified in 88% of cases. The proposed method may be used as an expert system for detailed stride classification, providing warning for severe FOG episodes and near-fall situations.
引用
收藏
页码:685 / 694
页数:10
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