A method for predicting the success of a BCI training session based on the classification of the CSP filters itself
نویسندگان
چکیده
We present an offline analysis of a large set of BCI experiments, focusing on common spatial filters and patterns (CSP). First, we show that it is possible to infer from the CSP filters whether the cross-validation error of LDA-classified EEG data preprocessed by this CSP will be high or low and predict thus the future performance of the feedback sessions following the calibration. Our test is 7 to 10 times faster to compute than the cross-validation. Second, from the CSP patterns, we calculate the corresponding source localization of the activations on the cortex. We explore the possibility of applying our method towards the improvement of calibration procedure quality and thus reduce the phenomenon of BCI illiteracy.
منابع مشابه
A review on EEG based brain computer interface systems feature extraction methods
The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...
متن کاملA review on EEG based brain computer interface systems feature extraction methods
The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...
متن کاملبهبود کارایی طبقه‌بندی‌کننده مبتنی بر نمایش تنک برای طبقه‌بندی سیگنالهای مغزی
In this paper, the problem of classification of motor imagery EEG signals using a sparse representation-based classifier is considered. Designing a powerful dictionary matrix, i.e. extracting proper features, is an important issue in such a classifier. Due to its high performance, the Common Spatial Patterns (CSP) algorithm is widely used for this purpose in the BCI systems. The main disadvanta...
متن کاملAbstract— The Filter Bank Common Spatial Pattern (FBCSP) algorithm constructs and selects subject-specific discriminative CSP features from a filter bank of spatial- temporal filters in a motor imagery brain-computer interface
The Filter Bank Common Spatial Pattern (FBCSP) algorithm constructs and selects subject-specific discriminative CSP features from a filter bank of spatialtemporal filters in a motor imagery brain-computer interface (MI-BCI). However, information from other types of features could be extracted and combined with CSP features to enhance the classification performance. Hence this paper proposes a F...
متن کاملControl of a 2-DoF robotic arm using a P300-based brain-computer interface
In this study, a novel control algorithm, based on a P300-based brain-computer interface (BCI) is fully developed to control a 2-DoF robotic arm. Eight subjects including 5 men and 3 women perform a 2-dimensional target tracking in a simulated environment. Their EEG (Electroencephalography) signals from visual cortex are recorded and P300 components are extracted and evaluated to perform a real...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010