Literature DB >> 25080406

Beyond maximum speed--a novel two-stimulus paradigm for brain-computer interfaces based on event-related potentials (P300-BCI).

Tobias Kaufmann1, Andrea Kübler.   

Abstract

OBJECTIVE: The speed of brain-computer interfaces (BCI), based on event-related potentials (ERP), is inherently limited by the commonly used one-stimulus paradigm. In this paper, we introduce a novel paradigm that can increase the spelling speed by a factor of 2, thereby extending the one-stimulus paradigm to a two-stimulus paradigm. Two different stimuli (a face and a symbol) are presented at the same time, superimposed on different characters and ERPs are classified using a multi-class classifier. Here, we present the proof-of-principle that is achieved with healthy participants. APPROACH: Eight participants were confronted with the novel two-stimulus paradigm and, for comparison, with two one-stimulus paradigms that used either one of the stimuli. Classification accuracies (percentage of correctly predicted letters) and elicited ERPs from the three paradigms were compared in a comprehensive offline analysis. MAIN
RESULTS: The accuracies slightly decreased with the novel system compared to the established one-stimulus face paradigm. However, the use of two stimuli allowed for spelling at twice the maximum speed of the one-stimulus paradigms, and participants still achieved an average accuracy of 81.25%. This study introduced an alternative way of increasing the spelling speed in ERP-BCIs and illustrated that ERP-BCIs may not yet have reached their speed limit. Future research is needed in order to improve the reliability of the novel approach, as some participants displayed reduced accuracies. Furthermore, a comparison to the most recent BCI systems with individually adjusted, rapid stimulus timing is needed to draw conclusions about the practical relevance of the proposed paradigm. SIGNIFICANCE: We introduced a novel two-stimulus paradigm that might be of high value for users who have reached the speed limit with the current one-stimulus ERP-BCI systems.

Entities:  

Mesh:

Year:  2014        PMID: 25080406     DOI: 10.1088/1741-2560/11/5/056004

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  8 in total

1.  Performance improvement of ERP-based brain-computer interface via varied geometric patterns.

Authors:  Zheng Ma; Tianshuang Qiu
Journal:  Med Biol Eng Comput       Date:  2017-06-28       Impact factor: 2.602

2.  Different effects of using pictures as stimuli in a P300 brain-computer interface under rapid serial visual presentation or row-column paradigm.

Authors:  Álvaro Fernández-Rodríguez; María Teresa Medina-Juliá; Francisco Velasco-Álvarez; Ricardo Ron-Angevin
Journal:  Med Biol Eng Comput       Date:  2021-03-20       Impact factor: 2.602

3.  Rapid P300 brain-computer interface communication with a head-mounted display.

Authors:  Ivo Käthner; Andrea Kübler; Sebastian Halder
Journal:  Front Neurosci       Date:  2015-06-05       Impact factor: 4.677

4.  An auditory multiclass brain-computer interface with natural stimuli: Usability evaluation with healthy participants and a motor impaired end user.

Authors:  Nadine Simon; Ivo Käthner; Carolin A Ruf; Emanuele Pasqualotto; Andrea Kübler; Sebastian Halder
Journal:  Front Hum Neurosci       Date:  2015-01-09       Impact factor: 3.169

5.  Comparison of Four Control Methods for a Five-Choice Assistive Technology.

Authors:  Sebastian Halder; Kouji Takano; Kenji Kansaku
Journal:  Front Hum Neurosci       Date:  2018-06-06       Impact factor: 3.169

6.  Stimulus modality influences session-to-session transfer of training effects in auditory and tactile streaming-based P300 brain-computer interfaces.

Authors:  P Ziebell; J Stümpfig; M Eidel; S C Kleih; A Kübler; M E Latoschik; S Halder
Journal:  Sci Rep       Date:  2020-07-17       Impact factor: 4.379

7.  Multimodal signal dataset for 11 intuitive movement tasks from single upper extremity during multiple recording sessions.

Authors:  Ji-Hoon Jeong; Jeong-Hyun Cho; Kyung-Hwan Shim; Byoung-Hee Kwon; Byeong-Hoo Lee; Do-Yeun Lee; Dae-Hyeok Lee; Seong-Whan Lee
Journal:  Gigascience       Date:  2020-10-07       Impact factor: 6.524

Review 8.  Brain-Computer Interface Spellers: A Review.

Authors:  Aya Rezeika; Mihaly Benda; Piotr Stawicki; Felix Gembler; Abdul Saboor; Ivan Volosyak
Journal:  Brain Sci       Date:  2018-03-30
  8 in total

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