TY - GEN

T1 - Adaptive CSP for user independence in MI-BCI paradigm for upper LIMB stroke rehabilitation

AU - Costa, Ana P.

AU - Moller, Jakob S.

AU - Iversen, Helle K.

AU - Puthusserypady, Sadasivan

N1 - Publisher Copyright: © 2018 IEEE.

PY - 2019

Y1 - 2019

N2 - A 3-class motor imagery (MI) Brain-Computer Interface (BCI) system, that implements subject adaptation with short to non-existing calibration sessions is proposed. The proposed adaptive common spatial patterns (ACSP) algorithm was tested on two datasets (an open source data set (4-class MI), and an in-house data set (3-class MI)). Results show that when long calibration data is available, the ACSP performs only slightly better (4%) than the CSP, but for short calibration sessions, the ACSP significantly improved the performance (up to 4-fold). An investigation into class separability of the in-house data set was performed and was concluded that the »Pinch»movement was more easily discriminated than »Grasp» and »Elbow Flexion». The proposed paradigm proved feasible and provided insights to help choose the motor tasks leading to best results in potential real-life applications. The ACSP enabled a successful semi user independent scenario and showed potential to be a tool towards an improved, personalized stroke rehabilitation protocol.

AB - A 3-class motor imagery (MI) Brain-Computer Interface (BCI) system, that implements subject adaptation with short to non-existing calibration sessions is proposed. The proposed adaptive common spatial patterns (ACSP) algorithm was tested on two datasets (an open source data set (4-class MI), and an in-house data set (3-class MI)). Results show that when long calibration data is available, the ACSP performs only slightly better (4%) than the CSP, but for short calibration sessions, the ACSP significantly improved the performance (up to 4-fold). An investigation into class separability of the in-house data set was performed and was concluded that the »Pinch»movement was more easily discriminated than »Grasp» and »Elbow Flexion». The proposed paradigm proved feasible and provided insights to help choose the motor tasks leading to best results in potential real-life applications. The ACSP enabled a successful semi user independent scenario and showed potential to be a tool towards an improved, personalized stroke rehabilitation protocol.

KW - Adaptive Common Spatial Patterns (ACSP)

KW - Brain-computer interface (BCI)

KW - Sensorimotor rhythms (SMR)

KW - Stroke rehabilitation

U2 - 10.1109/GlobalSIP.2018.8646403

DO - 10.1109/GlobalSIP.2018.8646403

M3 - Article in proceedings

AN - SCOPUS:85063092467

T3 - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

SP - 420

EP - 423

BT - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

PB - IEEE

T2 - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018

Y2 - 26 November 2018 through 29 November 2018

ER -