Real-time finger force prediction via parallel convolutional neural networks: A preliminary study

Feng Xu, Yang Zheng, Xiaogang Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

Continuous and accurate decoding of intended motions is critical for human-machine interactions. Here, we developed a novel approach for real-time continuous prediction of forces in individual fingers using parallel convolutional neural networks (CNNs). We extracted populational motor unit discharge frequency using CNNs in a parallel structure without spike sorting. The CNN parameters were trained based on two features from high-density electromyogram (HD-EMG), namely temporal energy heatmaps and frequency spectrum maps. The populational motor unit discharge frequency was then used to continuously predict finger forces based on a linear regression model. The force prediction performance was compared with a motor unit decomposition method and the conventional EMG amplitude-based method. Our results showed that the correlation coefficient between the predicted and the recorded forces of the CNN approach was on average 0.91, compared with the offline decomposition method of 0.89, the online decomposition method of 0.82, and the EMG amplitude method of 0.81. Additionally, the CNN based approach showed generalizable performance, with CNN trained on one finger applicable to a different finger. The outcomes suggest that our CNN based algorithm can offer an accurate and efficient force decoding method for human-machine interactions.

Original languageEnglish (US)
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3126-3129
Number of pages4
ISBN (Electronic)9781728119908
DOIs
StatePublished - Jul 2020
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: Jul 20 2020Jul 24 2020

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/TerritoryCanada
CityMontreal
Period7/20/207/24/20

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint

Dive into the research topics of 'Real-time finger force prediction via parallel convolutional neural networks: A preliminary study'. Together they form a unique fingerprint.

Cite this