Tobias Steinmetzer, Ingrid Bönninger, Barbara Priwitzer, F. Reinhardt, Markus Reckhardt, Dorela Erk, C. Travieso-González
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引用次数: 10
摘要
我们提出了一种新的方法来检测步态障碍根据他们的体育场使用聚类方法的传感器数据。21名健康受试者和18名帕金森受试者进行了Time Up and Go测试。时间序列被分割成不同的步骤。为了进行分析，考虑了移动传感器系统测量的水平加速度。我们使用动态时间扭曲和分层集群来区分体育场。特异性达到92%。
Clustering of Human Gait with Parkinson's Disease by Using Dynamic Time Warping
We present a new method for detecting gait disorders according to their stadium using cluster methods for sensor data. 21 healthy and 18 Parkinson subjects performed the Time Up and Go test. The time series were segmented into separate steps. For the analysis the horizontal acceleration measured by a mobile sensor system was considered. We used Dynamic Time Warping and Hierarchical Custering to distinguish the stadiums. A specificity of 92% was achieved.
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