Evaluation of the continuous detection of mental calculation episodes as a BCI control input

Bojorges-Valdez, Erik; Yáñez-Suárez, Oscar

doi:10.1016/j.compbiomed.2015.06.014

Cited by 7 publications

(3 citation statements)

References 38 publications

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“…This statement could be confusing, because it has been shown previously that larger LRTCs are expected during information processing tasks. Analysis of EEG signals has shown that LRTCs are higher during mental calculation [38], motor execution [39] or open eyes [40] in comparison to the rest. On the other hand, Alzheimer's patients show less LRTC for a series than healthy subjects [24].…”

Section: Discussionmentioning

confidence: 99%

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Association between EEG spectral power dynamics and event related potential amplitude on a P300 speller

Bojorges-Valdez¹,

Yáñez-Suárez²

2018

Biomed. Phys. Eng. Express

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Objective: Event related potentials (ERPs) are phenomena that produce alterations on the spectral power of different bands synced with stimuli presentation. Such a perspective overlooks that the spectral power time series present spontaneous oscillations, the dynamics of which have been associated with the state of health and could be also linked to superior processes such as attention, memory, or cognition. In this work, amplitude of the ERP has been associated with dynamics of the power spectral density (PSD) time series. Approach: Data from a public P3 speller database were analyzed. Statistics about latency, amplitude and scalp distribution of the ERP confirm correct task realization. The spectral power over alpha, beta and gamma bands were correlated with ERP amplitude, considering such estimations time-locked with stimuli presentation. Additionally, PSD time series over the same bands were constructed using a sliding window not synced with stimulation. From these time series, a scaling exponent was computed using a detrended fluctuation analysis approach, and such indices were correlated with ERP amplitude of all registered electrodes. Main results: The correlation between ERP amplitude and scaling exponents of PSD series achieve statistical significance in almost all channels and for all analyzed bands (excepting alpha at C4). In particular, beta and gamma PSD series achieve R 2 values above 0.6 for Cz. Meanwhile, the correlation analysis with time-locked PSD achieves a statistically significant relationship with ERP amplitude ( < p 0.05) but with a coefficient of determination (R 2 ) below 0.2, only for gamma and alpha over the C4 and Pz channels. Significance: The ERP amplitude and scaling exponent of the PSD time series show an anticorrelated behavior, suggesting that larger ERP amplitudes are elicited when the PSD series are less autocorrelated, similar to white noise, further suggesting that the processes involved in the generation of such dynamics could be related to the mechanisms of cognitive responses.

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Section: Discussionmentioning

confidence: 99%

“…Examples of a series , b series and g series estimated from a single run. The different DFA estimations summarize the dynamics of such series and were computed with our implementation of Peng's method[31].…”

mentioning

confidence: 99%

Association between EEG spectral power dynamics and event related potential amplitude on a P300 speller

Bojorges-Valdez¹,

Yáñez-Suárez²

2018

Biomed. Phys. Eng. Express

Self Cite

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“…In the single-kernel case, RBF-SVM was more accurate than polynomial-SVM. In [117] authors investigated the continuous evaluation of mental calculation as a valuable signal to control a BCI system. Active states and rest states were discriminated by means of an RBF-SVM.…”

Section: Motor and Non-motor Tasksmentioning

confidence: 99%

Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review

et al. 2017

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Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the applications of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

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Recurrence quantification analysis during a mental calculation task

Ledesma-Ramírez,

Hernández-Gloria,

Bojorges-Valdez

et al. 2023

Chaos: An Interdisciplinary Journal of Nonlinear Science

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The identification of brain dynamical changes under different cognitive conditions with noninvasive techniques such as electroencephalography (EEG) is relevant for the understanding of their underlying neural mechanisms. The comprehension of these mechanisms has applications in the early diagnosis of neurological disorders and asynchronous brain computer interfaces. In both cases, there are no reported features that could describe intersubject and intra subject dynamics behavior accurately enough to be applied on a daily basis. The present work proposes the use of three nonlinear features (recurrence rate, determinism, and recurrence times) extracted from recurrence quantification analysis (RQA) to describe central and parietal EEG power series complexity in continuous alternating episodes of mental calculation and rest state. Our results demonstrate a consistent mean directional change of determinism, recurrence rate, and recurrence times between conditions. Increasing values of determinism and recurrence rate were present from the rest state to mental calculation, whereas recurrence times showed the opposite pattern. The analyzed features in the present study showed statistically significant changes between rest and mental calculation states in both individual and population analysis. In general, our study described mental calculation EEG power series as less complex systems in comparison to the rest state. Moreover, ANOVA showed stability of RQA features along time.

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Evaluation of the continuous detection of mental calculation episodes as a BCI control input

Cited by 7 publications

References 38 publications

Association between EEG spectral power dynamics and event related potential amplitude on a P300 speller

Association between EEG spectral power dynamics and event related potential amplitude on a P300 speller

Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review

Recurrence quantification analysis during a mental calculation task

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