Event-based Low-Power and Low-Latency Regression Method for Hand Kinematics from Surface EMG

Introduction

This repository contains the code to reproduce our paper M. Zanghieri et al., “Event-based low-power and low-latency regression method for hand kinematics from surface EMG” [1].

Usage

1. Run spikification.ipynb (or equivalently spikification.py) to spikify the NinaPro Database 8.
2. Run experiment_taus.ipynb (or equivalently experiment_taus.py) for the regression epxeriments.
3. Run read_results.ipynb to get the results statistics.

Authors

This work was realized at the Neuromorphic Cognitive Systems (NCS) group of the Institute of Neuroinformatics (INI) of University of Zürich and ETH Zürich by:

• Marcello Zanghieri - University of Bologna (work conducted while a visiting PhD student at INI's NCS)
• Prof. Simone Benatti - University of Bologna, University of Modena and Reggio Emilia
• Prof. Luca Benini - University of Bologna, ETH Zürich
• Dr. Elisa Donati - Institute of Neuroinformatics (INI) of University of Zürich and ETH Zürich

Citation

When using or referencing the project, please cite our paper:

@INPROCEEDINGS{10164372,
  author={Zanghieri, Marcello and Benatti, Simone and Benini, Luca and Donati, Elisa},
  booktitle={2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)}, 
  title={Event-based Low-Power and Low-Latency Regression Method for Hand Kinematics from Surface {EMG}}, 
  year={2023},
  volume={},
  number={},
  pages={293-298},
  doi={10.1109/IWASI58316.2023.10164372}}

References

[1] M. Zanghieri, S. Benatti, L. Benini, and E. Donati, “Event-based low-power and low-latency regression method for hand kinematics from surface EMG,” in 2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI), 2023, pp. 293–298. DOI: 10.1109/IWASI58316.2023.10164372

License

All files are released under the LGPL-2.1 license (LGPL-2.1) (see LICENSE).