Unscented Kalman filter for neural decoding of human treadmill walking from non-invasive electroencephalography

Trieu Phat Luu, Yongtian He, Sho Nakagame, Jeffrey Gorges, Kevin Nathan, Jose L. Contreras-Vidal

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

9 Scopus citations

Abstract

The feasibility of decoding lower limb kinematics in human treadmill walking from noninvasive electroencephalography (EEG) has been demonstrated with linear Wiener filter. However, nonlinear relationship between neural activities and limb movements may challenge the linear decoders in real-time brain computer interface (BCI) applications. In this study, we propose a nonlinear neural decoder using an Unscented Kalman Filter (UKF) to infer lower limb joint angles from noninvasive scalp EEG signals during human treadmill walking. Our results demonstrate that lower limb joint angles during treadmill walking can be decoded from the fluctuations in the amplitude of slow cortical potentials in the delta band (0.1-3Hz). Overall, the average decoding accuracy were 0.43 ± 0.18 for Pearson's r value and 1.82 ± 3.07 for signal to noise ratio (SNR), and robust to ocular, muscle, or movement artifacts. Moreover, the signal preprocessing scheme and the design of UKF allow the implementation of the proposed EEG-based BCI for real-time applications. This has implications for the development of closed-loop EEG-based BCI systems for gait rehabilitation after stroke.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1548-1551
Number of pages4
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2016-October
ISSN (Print)1557-170X

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
CountryUnited States
CityOrlando
Period8/16/168/20/16

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Unscented Kalman filter for neural decoding of human treadmill walking from non-invasive electroencephalography'. Together they form a unique fingerprint.

Cite this