Detection of Parkinson's disease by Shifted One Dimensional Local Binary Patterns from gait

作者：

Highlights：

• This study showed that the PD can be diagnosed by using sensors attached at underfoot from gait.

• Feature extracted by Shifted 1D-LBP, which is sensitive to local changes in time signals.

• Shifted 1D-LBP has a simple algorithm. It can be used in real time applications.

• Obtained detection accuracy is 88.8889%.

• The accuracy results were compared with the results of previous studies in literature.

摘要

•This study showed that the PD can be diagnosed by using sensors attached at underfoot from gait.•Feature extracted by Shifted 1D-LBP, which is sensitive to local changes in time signals.•Shifted 1D-LBP has a simple algorithm. It can be used in real time applications.•Obtained detection accuracy is 88.8889%.•The accuracy results were compared with the results of previous studies in literature.

论文关键词：Parkinson's disease,Shifted one-dimensional local binary pattern,Automatic diagnosis,Expert systems,Biomedical,Gait

论文评审过程：Available online 15 March 2016, Version of Record 26 March 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.03.018