TY - GEN
T1 - A Generic Error-related Potential Classifier Offers a Comparable Performance to a Personalized Classifier
AU - Lopes-Dias, Catarina
AU - Sburlea, Andreea Ioana
AU - Müller-Putz, Gernot
PY - 2020/7
Y1 - 2020/7
N2 - Brain-computer interfaces (BCIs) provide more independence to people with severe motor disabilities but current BCIs' performance is still not optimal and often the user's intentions are misinterpreted. Error-related potentials (ErrPs) are the neurophysiological signature of error processing and their detection can help improving a BCI's performance.A major inconvenience of BCIs is that they commonly require a long calibration period, before the user can receive feedback of their own brain signals. Here, we use the data of 15 participants and compare the performance of a personalized ErrP classifier with a generic ErrP classifier. We concluded that there was no significant difference in classification performance between the generic and the personalized classifiers (Wilcoxon signed rank tests, two-sided and one-sided left and right). This results indicate that the use of a generic ErrP classifier is a good strategy to remove the calibration period of a ErrP classifier, allowing participants to receive immediate feedback of the ErrP detections.
AB - Brain-computer interfaces (BCIs) provide more independence to people with severe motor disabilities but current BCIs' performance is still not optimal and often the user's intentions are misinterpreted. Error-related potentials (ErrPs) are the neurophysiological signature of error processing and their detection can help improving a BCI's performance.A major inconvenience of BCIs is that they commonly require a long calibration period, before the user can receive feedback of their own brain signals. Here, we use the data of 15 participants and compare the performance of a personalized ErrP classifier with a generic ErrP classifier. We concluded that there was no significant difference in classification performance between the generic and the personalized classifiers (Wilcoxon signed rank tests, two-sided and one-sided left and right). This results indicate that the use of a generic ErrP classifier is a good strategy to remove the calibration period of a ErrP classifier, allowing participants to receive immediate feedback of the ErrP detections.
UR - http://www.scopus.com/inward/record.url?scp=85091025498&partnerID=8YFLogxK
U2 - 10.1109/EMBC44109.2020.9176640
DO - 10.1109/EMBC44109.2020.9176640
M3 - Conference paper
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2995
EP - 2998
BT - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
T2 - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Y2 - 20 July 2020 through 24 July 2020
ER -