Tactile, Visual, and Bimodal P300s: Could Bimodal P300s Boost BCI Performance?

Brouwer, A.; Erp, J.B.F. van; Aloise, Fabio; Cincotti, Febo

doi:10.3814/2010/967027

Cited by 21 publications

(14 citation statements)

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“…Tactile ERP–BCIs utilize stimulation units (further referred to as tactors; e.g., vibration motors or piezo elements) placed at different body locations, e.g., on hands, around the waist or on the back of participants (e.g., Aloise et al, 2007; Brouwer and Van Erp, 2010; Brouwer et al, 2010; Thurlings et al, 2012; van der Waal et al, 2012; Kaufmann et al, 2013b). Users focus their attention on tactile stimulation of one location they intend to select (target stimulus) and ignore stimuli on all other locations.…”

Section: Introductionmentioning

confidence: 99%

Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state

Kaufmann¹,

Holz²,

Kübler³

2013

Front. Neurosci.

114

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This paper describes a case study with a patient in the classic locked-in state, who currently has no means of independent communication. Following a user-centered approach, we investigated event-related potentials (ERP) elicited in different modalities for use in brain-computer interface (BCI) systems. Such systems could provide her with an alternative communication channel. To investigate the most viable modality for achieving BCI based communication, classic oddball paradigms (1 rare and 1 frequent stimulus, ratio 1:5) in the visual, auditory and tactile modality were conducted (2 runs per modality). Classifiers were built on one run and tested offline on another run (and vice versa). In these paradigms, the tactile modality was clearly superior to other modalities, displaying high offline accuracy even when classification was performed on single trials only. Consequently, we tested the tactile paradigm online and the patient successfully selected targets without any error. Furthermore, we investigated use of the visual or tactile modality for different BCI systems with more than two selection options. In the visual modality, several BCI paradigms were tested offline. Neither matrix-based nor so-called gaze-independent paradigms constituted a means of control. These results may thus question the gaze-independence of current gaze-independent approaches to BCI. A tactile four-choice BCI resulted in high offline classification accuracies. Yet, online use raised various issues. Although performance was clearly above chance, practical daily life use appeared unlikely when compared to other communication approaches (e.g., partner scanning). Our results emphasize the need for user-centered design in BCI development including identification of the best stimulus modality for a particular user. Finally, the paper discusses feasibility of EEG-based BCI systems for patients in classic locked-in state and compares BCI to other AT solutions that we also tested during the study.

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Section: Introductionmentioning

confidence: 99%

Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state

Kaufmann¹,

Holz²,

Kübler³

2013

Front. Neurosci.

114

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“…Typically, the input signals used to drive BCIs are the fluctuations in electrical potential elicited by cognitive activity in response to sensory input, measured by electrodes placed on the scalp (i.e., electroencephalography [EEG]; e.g., Farwell & Donchin, 1988;Townsend et al, 2010), or by electrode grids implanted directly onto the cortical surface of the brain (i.e., electrocorticography; e.g., Brunner, Ritaccio, van Erp, Aloise, & Cincotti, 2011;Leuthardt, Schalk, Wolpaw, Ojemann, & Moran, 2004). Many BCIs for augmentative communication elicit brain signals using visual stimuli (e.g., Farwell & Donchin, 1988;Guger et al, 2009;Jin et al, 2010;Minett, Peng, Zhou, Zheng, & Wang, 2010;Serby, Yom-Tov, & Inbar, 2005;Townsend et al, 2010), but effective use has also been made of both auditory stimuli (e.g., Furdea et al, 2009;Höhne, Schreuder, Blankertz, & Tangermann, 2010;Klobassa et al, 2009) and tactile stimuli (e.g., Brouwer, van Erp, Aloise, & Cincotti, 2010).…”

Section: Introductionmentioning

confidence: 96%

A Chinese Text Input Brain–Computer Interface Based on the P300 Speller

Minett

Zheng

Fong

et al. 2012

International Journal of Human-Computer Interaction

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A visual speller is a brain-computer interface that empowers users with limited motor functionality to input text into a computer by measuring their electroencephalographic responses to visual stimuli. Most prior research on visual spellers has focused on input of alphabetic text. Adapting a speller for other types of segmental or syllabic script is straightforward because such scripts comprise sufficiently few characters that they may all be displayed to the user simultaneously. Logographic scripts, such as Chinese hanzi, however, impose a challenge: How should the thousands of Chinese characters be displayed to the user? Here, we present a visual speller, based on Farwell and Donchin's P300 Speller, for Chinese character input. The speller uses a novel shape-based method called the First-Last, or FLAST, method to encode more than 7,000 Chinese characters. Characters are input by selecting two components, from a set of 56 distinct components, that match the shape of the target character, followed by selection of the character itself. At the input speed of one character per 107 s, 24 able-bodied participants achieved mean online accuracy of 82.8% per component selection and 63.5% per character input. At the faster input speed of one character per 77 s, mean online accuracy was 59.4% per component selection and 33.3% per character input.

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“…EEGbased BCI uses various kinds of responses of the brain. For example, the potentials in sensorimotor cortex which evoked by imaging the movement of the body parts [2], steadystate visual evoked potentials (SSVEP) which are responses of visual cortex to flickering visual stimulations [3] and event related potentials (ERP) which are responses to specific sensory or cognitive events [4].…”

Section: Introductionmentioning

confidence: 99%

Responses in posterior parietal cortex to movement intention task with visual and tactile cues

Kamikawa

Tanaka

2015

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Posterior parietal cortex (PPC) is considered to be related to forming of motor intention. The detection of the direction intended movements and the type of intended movement is a challenging goal in neuroscience and engineering applications such as brain-computer interfacing (BCI). In previous studies, it has been reported that EEG signals extracted from PPC can be used to decode intended movement direction. However, it is not clear whether extracted EEG signals are related to motor intention, because visually evoked potential (VEP) which evoked by visual cue in their experiment may be included in their extracted EEG signals. The purpose of this study is to investigate the possibility of VEP mixed into extracted EEG signals. Therefore experiments with not only visual but also tactile cues were conducted. EEG components that could be related to PPC were extracted by using independent component analysis (ICA). We compared event related potential (ERP) waveforms between two experiments. In the result, ERP waveforms of the experiment with tactile cue were significantly different from that of the experiment with visual cue. This result suggests that VEP was included in the EEG signals extracted from PPC in the experiment with visual cue.

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Tactile, Visual, and Bimodal P300s: Could Bimodal P300s Boost BCI Performance?

Cited by 21 publications

References 50 publications

Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state

Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state

A Chinese Text Input Brain–Computer Interface Based on the P300 Speller

Responses in posterior parietal cortex to movement intention task with visual and tactile cues

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