Artikel ; Online: Force decoding using local field potentials in primary motor cortex: PLS or Kalman filter regression?
Australasian physical & engineering sciences in medicine
2020
Abstract: The development of brain-computer interface (BCI) systems is an important approach in brain studies. Control of communication devices and prostheses in real-world scenarios requires complex movement parameters. Decoding a variety of neural signals ... ...
Abstract | The development of brain-computer interface (BCI) systems is an important approach in brain studies. Control of communication devices and prostheses in real-world scenarios requires complex movement parameters. Decoding a variety of neural signals captured by micro-wire arrays is a potential applicant for extracting movement-related information. The present work was conducted to compare the functionality of partial least square (PLS) regression and Kalman filter to predict the force parameter from local field potential (LFP) signals of the primary motor cortex (M1). The signals were recorded using a 16-channel micro-wire array from the forelimb-related area of the M1 of three rats performing a behavioral task in which the force signal of the rat's forelimb paw was generated. Our results show that PLS regression and Kalman filters with the mean performance of 0.75 and 0.72 in terms of the correlation coefficient (CC) and 0.37 and 0.48 in terms of normalized mean square error (NMSE), respectively, are effective methods for decoding the force parameter from LFPs. Kalman filter underperforms PLS both in performance and speed. Although adding nonlinearity to the Kalman filter results in equally accurate CC performance as PLS, it has even more computational cost. Therefore, it is inferred that nonlinear methods do not necessarily have better functionality than linear ones and PLS, as a simple fast linear method could be an effectively applicable regression technique for BCIs. |
---|---|
Sprache | Englisch |
Erscheinungsdatum | 2020-01-02 |
Erscheinungsland | Netherlands |
Dokumenttyp | Journal Article |
ZDB-ID | 46226-3 |
ISSN | 1879-5447 ; 0158-9938 |
ISSN (online) | 1879-5447 |
ISSN | 0158-9938 |
DOI | 10.1007/s13246-019-00833-7 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
Volltext online
Zusatzmaterialien
Kategorien
Verfügbar in ZB MED Köln/Königswinter
Zs.B 2684: Hefte anzeigen | Standort: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG) |
Über subito bestellen
Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.