dc.contributor.author | Malik, Wasim Qamar | |
dc.contributor.author | Truccolo, Wilson | |
dc.contributor.author | Brown, Emery N. | |
dc.contributor.author | Hochberg, Leigh R. | |
dc.date.accessioned | 2012-05-09T20:10:40Z | |
dc.date.available | 2012-05-09T20:10:40Z | |
dc.date.issued | 2011-02 | |
dc.identifier.issn | 1534-4320 | |
dc.identifier.issn | 1558-0210 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/70553 | |
dc.description.abstract | The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics.We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor
cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5[plus-over-minus sign]0.5 s (mean[plus-over-minus sign]s.d.) . The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing
rates of 25[plus-over-minus sign]3 single units by a factor of 7.0[plus-over-minus sign]0.9. We expect that the gain in computational efficiency will be much higher in
systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future
large-dimensional, multisignal neural interface systems. | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant R01 DC009899) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant RC1 HD063931) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant N01 HD053403) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant 5K01 NS057389) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant DP1-OD003646) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant R01-EB006385) | en_US |
dc.description.sponsorship | United States. Dept. of Veterans Affairs (Office of Research and Development, Rehabilitation R&D Service) | en_US |
dc.description.sponsorship | Massachusetts General Hospital (Deane Institute for Integrated Research on Atrial Fibrillation and Stroke) | en_US |
dc.description.sponsorship | Doris Duke Charitable Foundation | en_US |
dc.description.sponsorship | Spaulding Rehabilitation Hospital | en_US |
dc.language.iso | en_US | |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/tnsre.2010.2092443 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike 3.0 | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/ | en_US |
dc.source | PubMed Central | en_US |
dc.title | Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Malik, W Q et al. “Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 19.1 (2011): 25–34. Web. | en_US |
dc.contributor.department | Harvard University--MIT Division of Health Sciences and Technology | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences | en_US |
dc.contributor.approver | Brown, Emery N. | |
dc.contributor.mitauthor | Brown, Emery N. | |
dc.contributor.mitauthor | Malik, Wasim Qamar | |
dc.relation.journal | IEEE Transactions on Neural Systems and Rehabilitation Engineering | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Malik, W Q; Truccolo, W; Brown, E N; Hochberg, L R | en |
dc.identifier.orcid | https://orcid.org/0000-0003-2668-7819 | |
dc.identifier.orcid | https://orcid.org/0000-0002-7260-7560 | |
dspace.mitauthor.error | true | |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |