Sensor Selection with Composite Features for Human-Prosthetic Interfaces (SS-CF)

Matlab implementation of the sensor selection algorithm presented in paper: T. Yu, A. Mohammadi, Y. Tan, P. Choong and D. Oetomo, "Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, pp. 1732-1742, 2023, doi: 10.1109/TNSRE.2023.3258225

Quick Start:

• Run Main_SSCF.m for an example.

Dataset:

• Dataset: dataset.mat contains one non-disabled subject performing forward reaching to spatial target points with their upper limb.
• The goal is to select q sensors that can best differentiate the three elbow poses required by the spatial target points.
• Upper limb and upper body joint kinematics and sEMG signals are recorded with features extracted.
• The full dataset of 10 subjects is available at: https://doi.org/10.26188/23294693.

Citation:

• We would appreciate your acknowledgement by citing the paper:
• @article{Yu2023,
  author={Yu, Tianshi and Mohammadi, Alireza and Tan, Ying and Choong, Peter and Oetomo, Denny},journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
  title={Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces},
  year={2023},
  volume={31},
  pages={1732-1742},
  doi={10.1109/TNSRE.2023.3258225}}

For more details and updates please check: https://github.com/tianshi-yu/SS-CF_Sensor_Selection_with_Composite_Features