Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait

作者：

Highlights：

• A novel method for automatic detection of Parkinson disease and severity prediction.

• 1D-Convnet architecture specifically designed to process signals from foot sensors.

• Parkinsonian gate is detected without manual feature extraction.

• We achieved improved accuracy compared to recent state-of-the art algorithms.

摘要

•A novel method for automatic detection of Parkinson disease and severity prediction.•1D-Convnet architecture specifically designed to process signals from foot sensors.•Parkinsonian gate is detected without manual feature extraction.•We achieved improved accuracy compared to recent state-of-the art algorithms.

论文关键词：1D-Convnet,Parkinson,Gait,Classification,Deep learning

论文评审过程：Received 22 February 2019, Revised 4 November 2019, Accepted 5 November 2019, Available online 9 November 2019, Version of Record 13 November 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113075