Multiview MAX-VAR canonical correlation approach for enhancing SSVEP based BCIs
19 May 2019-pp 1-4
TL;DR: From the statistical significance tests, it is observed that the proposed approach effectively achieves superior performance at short window lengths making it a propitious algorithm for real time brain computer interfaces (BCI).
Abstract: This study proposes and validates a novel steady-state visual evoked potential (SSVEP) detection approach, multiview MAX-VAR canonical correlation, that finds a common unique subspace that encompasses all the SSVEP responses pertaining to a specific subject. The method employs a generalized canonical correlation framework that efficiently computes a projection matrix that optimizes test data to achieve higher SSVEP identification performance. We used a SSVEP benchmark dataset using a 40 target BCI experiment to evaluate the proposed method. The results demonstrate that the multiview MAX-VAR canonical correlation approach outperforms the compared methods with respect to both accuracy and information transfer rates (ITRs). From the statistical significance tests, it is observed that the proposed approach effectively achieves superior performance at short window lengths making it a propitious algorithm for real time brain computer interfaces (BCI).
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TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
6,803 citations
"Multiview MAX-VAR canonical correla..." refers background in this paper
...Brain computer interface (BCI) describes a broad range of methods and technologies that enable the direct control of applications or devices by the brain and removes its reliance on the motor pathways [1]....
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TL;DR: This study presents an electroencephalogram-based BCI speller that can achieve information transfer rates (ITRs) up to 5.32 bits per second, the highest ITRs reported inBCI spellers using either noninvasive or invasive methods, and demonstrates that BCIs can provide a truly naturalistic high-speed communication channel using noninvasively recorded brain activities.
Abstract: The past 20 years have witnessed unprecedented progress in brain-computer interfaces (BCIs). However, low communication rates remain key obstacles to BCI-based communication in humans. This study presents an electroencephalogram-based BCI speller that can achieve information transfer rates (ITRs) up to 5.32 bits per second, the highest ITRs reported in BCI spellers using either noninvasive or invasive methods. Based on extremely high consistency of frequency and phase observed between visual flickering signals and the elicited single-trial steady-state visual evoked potentials, this study developed a synchronous modulation and demodulation paradigm to implement the speller. Specifically, this study proposed a new joint frequency-phase modulation method to tag 40 characters with 0.5-s-long flickering signals and developed a user-specific target identification algorithm using individual calibration data. The speller achieved high ITRs in online spelling tasks. This study demonstrates that BCIs can provide a truly naturalistic high-speed communication channel using noninvasively recorded brain activities.
618 citations
"Multiview MAX-VAR canonical correla..." refers background in this paper
...Of the various BCI modalities, steady-state visual evoked potential (SSVEP) based BCIs have shown great potential in recent studies due to their high ITR and low training time [3]....
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TL;DR: The current status and future prospects of BCI technology and its clinical applications are discussed, BCI is defined, the BCI-relevant signals from the human brain are reviewed, and the functional components of BCIs are described.
Abstract: Braincomputer interfaces (BCIs) allow their users to communicate or control external devices using brain signals rather than the brain's normal output pathways of peripheral nerves and muscles. Motivated by the hope of restoring independence to severely disabled individuals and by interest in further extending human control of external systems, researchers from many fields are engaged in this challenging new work. BCI research and development has grown explosively over the past two decades. Efforts have begun recently to provide laboratory-validated BCI systems to severely disabled individuals for real-world applications. In this paper, we discuss the current status and future prospects of BCI technology and its clinical applications. We will define BCI, review the BCI-relevant signals from the human brain, and describe the functional components of BCIs. We will also review current clinical applications of BCI technology and identify potential users and potential applications. Lastly, we will discuss current limitations of BCI technology, impediments to its widespread clinical use, and expectations for the future.
439 citations
Additional excerpts
...They can also be used as alternative and augmentative communication method and for other human computer interaction modalities such as cursors, gaming etc [2]....
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TL;DR: This paper presents a high-speed BCI based on code modulation of visual evoked potentials (c-VEP), which achieved an average information transfer rate (ITR) of 108 ± 12 bits min(-1) on five subjects with a maximum ITR of 123 bits min−1 for a single subject.
Abstract: Recently, electroencephalogram-based brain-computer interfaces (BCIs) have attracted much attention in the fields of neural engineering and rehabilitation due to their noninvasiveness. However, the low communication speed of current BCI systems greatly limits their practical application. In this paper, we present a high-speed BCI based on code modulation of visual evoked potentials (c-VEP). Thirty-two target stimuli were modulated by a time-shifted binary pseudorandom sequence. A multichannel identification method based on canonical correlation analysis (CCA) was used for target identification. The online system achieved an average information transfer rate (ITR) of 108 ± 12 bits min(-1) on five subjects with a maximum ITR of 123 bits min(-1) for a single subject.
272 citations
"Multiview MAX-VAR canonical correla..." refers methods in this paper
...ITCCA is an extension of CCA that replaces the synthetic SSVEP references with averaged templates in the CCA detection framework [9]....
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01 Oct 2017
TL;DR: This paper presents a benchmark steady-state visual evoked potential (SSVEP) dataset acquired with a 40-target brain– computer interface (BCI) speller that provides high-quality data for computational modeling of SSVEPs.
Abstract: This paper presents a benchmark steady-state visual evoked potential (SSVEP) dataset acquired with a 40-target brain– computer interface (BCI) speller. The dataset consists of 64-channel Electroencephalogram (EEG) data from 35 healthy subjects (8 experienced and 27 naive) while they performed a cue-guided target selecting task. The virtual keyboard of the speller was composed of 40 visual flickers, which were coded using a joint frequency and phase modulation (JFPM) approach. The stimulation frequencies ranged from 8 Hz to 15.8 Hz with an interval of 0.2 Hz. The phase difference between two adjacent frequencies was $0.5\pi $ . For each subject, the data included six blocks of 40 trials corresponding to all 40 flickers indicated by a visual cue in a random order. The stimulation duration in each trial was five seconds. The dataset can be used as a benchmark dataset to compare the methods for stimulus coding and target identification in SSVEP-based BCIs. Through offline simulation, the dataset can be used to design new system diagrams and evaluate their BCI performance without collecting any new data. The dataset also provides high-quality data for computational modeling of SSVEPs. The dataset is freely available from http://bci.med.tsinghua.edu.cn/download.html .
244 citations
"Multiview MAX-VAR canonical correla..." refers background or methods in this paper
...55 s and 2 s respectively to estimate both practical and theoretical values [6]....
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...The performance across the three compared methods is evaluated by fixing the number of electrodes to nine, calibration trials to five and number of harmonics for combCCA to five [6]....
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