UMA-BCI Speller: An easily configurable P300 speller tool for end users

Velasco-Álvarez, Francisco; Sancha-Ros, Salvador; García-Garaluz, Esther; Fernández-Rodríguez, Álvaro; Medina-Juliá, María Teresa; Ron-Angevín, Ricardo

doi:10.1016/j.cmpb.2019.02.015

Cited by 29 publications

(20 citation statements)

References 37 publications

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“…The BCI Systems can be divided into the two main categories: invasive and noninvasive [3,82]. Most of the EEG-based BCI systems rely on the listed below paradigms [15,64,70,[83][84][85][86][87][88]]:…”

Section: Non-invasive Bci Systemsmentioning

confidence: 99%

“…The most popular and effective are, based on thorough literature review, the ERPbased BCI systems [86,89]. However, the SSVEP systems are considered to be high-speed BCIs as they require less training and are easier to configure [84,85,90]. However, they need gaze control and have been reported as tiring and uncomfortable for users [85].…”

mentioning

confidence: 99%

“…However, the SSVEP systems are considered to be high-speed BCIs as they require less training and are easier to configure [84,85,90]. However, they need gaze control and have been reported as tiring and uncomfortable for users [85]. The P300based BCIs are very popular as they are the oldest studied paradigms and need relatively little training [84][85][86].…”

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confidence: 99%

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Summary of over Fifty Years with Brain-Computer Interfaces—A Review

et al. 2021

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Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

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Section: Non-invasive Bci Systemsmentioning

confidence: 99%

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confidence: 99%

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Summary of over Fifty Years with Brain-Computer Interfaces—A Review

et al. 2021

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“…El software utilizado para diseñar la interfaz fue el UMA-BCI speller, que sirve como un front-end de BCI2000 de fácil manejo (Velasco-Álvarez et al, 2019). El presente trabajo emplea cuatro condiciones, basadas en la combinación de los dos paradigmas (RCP y RSVP) y dos configuraciones de estímulos (letras e imágenes con letras).…”

Section: Condicionesunclassified

Libro de Actas - 11 Simposio CEA de Bioingeniería

Lois¹

2019

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We present an experimental study for the description of the paths described by the thoracohumeral instantaneous helical axis (IHA) in cyclical movements. The movement was recorded by means of a motion analysis technique with videophotogrammetry that allows the measurement of the IHA with an error lower than 1 cm, in a very reproducible way. This makes it possible to represent the IHA as an axoid, whose mediolateral displacement is related to the angular velocities of the sternoclavicular, acromioclavicular and glenohumeral joints, and whose vertical position is associated with glenohumeral joint elevation. The study was carried out with 41 healthy subjects and 15 subjects with pathologies of the shoulder, analyzing the cyclic movement of elevation-lower of the humerus in the frontal and scapular planes. The location and shape of the axoids is sensitive to the effects of the load and the functional ability of the subjects. The results obtained show that the IHA can be useful in the biomechanical functional assessment of the shoulder, by offering information on the coordination of the different joints that constitute it.

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“…Four letters for simulation are used to represent low-, medium-, and high-speed states and stop states. As one of the most easily observed ERP, P300 is also used for spelling by constantly flashing the rows and columns of a 6 × 6 alphabet matrix when the subjects are focusing on a target letter, which stimulates the P300 response (Velasco-Álvarez et al, 2019 ). Therefore, we chose P300 because it was more stable to be observed in most people and less prone to fatigue.…”

Section: Introductionmentioning

confidence: 99%

A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot

et al. 2020

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Background and Objective: Electroencephalography (EEG) can be used to control machines with human intention, especially for paralyzed people in rehabilitation exercises or daily activities. Some effort was put into this but still not enough for online use. To improve the practicality, this study aims to propose an efficient control method based on P300, a special EEG component. Moreover, we have developed an upper-limb assist robot system with the method for verification and hope to really help paralyzed people. Methods: We chose P300, which is highly available and easily accepted to obtain the user's intention. Preprocessing and spatial enhancement were firstly implemented on raw EEG data. Then, three approaches-linear discriminant analysis, support vector machine, and multilayer perceptron-were compared in detail to accomplish an efficient P300 detector, whose output was employed as a command to control the assist robot. Results: The method we proposed achieved an accuracy of 94.43% in the offline test with the data from eight participants. It showed sufficient reliability and robustness with an accuracy of 80.83% and an information transfer rate of 15.42 in the online test. Furthermore, the extended test showed remarkable generalizability of this method that can be used in more complex application scenarios. Conclusion: From the results, we can see that the proposed method has great potential for helping paralyzed people easily control an assist robot to do numbers of things.

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UMA-BCI Speller: An easily configurable P300 speller tool for end users

Cited by 29 publications

References 37 publications

Summary of over Fifty Years with Brain-Computer Interfaces—A Review

Summary of over Fifty Years with Brain-Computer Interfaces—A Review

Libro de Actas - 11 Simposio CEA de Bioingeniería

A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot

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