sEMG time–frequency features for hand movements classification

作者：

Highlights：

• Several combinations of sEMG TF features extraction and DR methods were compared.

• DOST was introduced as a time-efficient method for TF feature extraction.

• MDS was introduced as a non-linear dimension reduction method for sEMG signals.

• Competitive results by DOST with significant reduction of the computational burden.

摘要

•Several combinations of sEMG TF features extraction and DR methods were compared.•DOST was introduced as a time-efficient method for TF feature extraction.•MDS was introduced as a non-linear dimension reduction method for sEMG signals.•Competitive results by DOST with significant reduction of the computational burden.

论文关键词：sEMG classification,Time–frequency domain,Hand gesture,Non-linear dimension reduction

论文评审过程：Received 25 October 2021, Revised 21 June 2022, Accepted 23 July 2022, Available online 30 July 2022, Version of Record 12 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118282