A spatial coherence-based vision-free brain-computer interface using auditory selective attention / Interface cérebro-computador baseada em coerência espacial usando atenção auditiva seletiva

INTRODUCTION: The development of Brain Computer Interfaces based on Auditory Selective Attention allows patients unable to voluntarily control eye movement to interact with the interface, because such systems are independent of vision. An alternative technique suitable for Brain Computer Interface applications is Spatial Coherence, an objective method to detect the side where a subject is focusing attention. This method takes into consideration the Coherence Function and the topographic distribution of responses between EEG electrodes. In this work, we further study the Information Transfer Rate and the effects of overlapping windows in the calculations. The idea behind the overlapping is to decrease the duration of the test in order to augment the Information Transfer Rate. METHOD: EEG signals were collected from fourteen adult men aged between 19 and 28 years. Amplitude-modulated tones were used for stimulation, with 32 and 38 Hz modulation and 500 and 2000 Hz carrier frequencies, on the left and right ears, respectively. Spatial coherence was used in an online Brain Computer Interface system using auditory steady-state responses modulated by Auditory Selective Attention. RESULTS: The obtained hit rates and the Information Transfer Rate may be considered appropriate, with a maximum value of 82% and 1.89 bits/min. The better detector regarding sensitivity versus specificity can be obtained by using a 50% overlap between consecutive data windows. CONCLUSION: We conclude that the Spatial Coherence successfully detected the focus of attention, and it seemed useful as a classifier of the attention condition for vision-free Brain Computer Interface.

O desenvolvimento de interfaces cérebro computador (BCI), com base em atenção seletiva auditiva (ASA), auxilia pacientes que não conseguem controlar voluntariamente o movimento do olho para interagir com interfaces visuais, uma vez que tais sistemas são independentes de visão. A Coerência Espacial é técnica alternativa adequada para aplicações BCI, tal técnica é usada em eletroencefalograma (EEG) para detectar o lado, ou hemisfério, em que o sujeito está focalizando atenção. Este método leva em consideração a função de coerência e a distribuição topográfica das respostas entre os eletrodos de EEG. Neste estudo foram coletados sinais EEG de 14 homens adultos com idade entre 19 e 28 anos com aplicação de estímulos sonoros, tons em amplitude modulada (AM) com frequência de modulação e portadora 32/500 Hz na orelha esquerda e 38/2000 Hz na orelha direita. A coerência espacial foi usada em um sistema BCI on-line com ASSR modulada pela atenção seletiva auditiva. Neste trabalho, foi abordado a taxa de transferência de informação (ITR) e os efeitos de sobreposição de janelas nas estimativas da coerência com objetivo de reduzir a duração do ensaio e aumentar a ITR. Conclui-se que a coerência espacial pode útil para detecção do foco de atenção, aplicado a BCI. As taxas de sensibilidade e ITR máximas são de 82% e 1,89 bits/min. Neste caso a melhor sensibilidade e especificidade foram obtidas com 50% de sobreposição entre as janelas nas estimativas da coerência.

Investigating cardiolocomotor synchronization during running in trained and untrained males

Introduction This study aims at investigating the coupling of the cardiac and locomotor systems during running in trained and untrained males. Methods Sixteen healthy young males subjects were submitted to an anthropometric evaluation, followed by a treadmill test at 70% to 75% of heart rate reserve. Based on the average velocity, they were divided into two groups of eight, trained group (TG) and untrained group (UT). The electrocardiogram and the electromyogram of the vastus lateralis muscle of the right thigh were digitized at a sampling rate of 1000 Hz, and processed off-line. Each cardiac and electromyographic cycle was detected to further investigate the coupling between cardiac and running rates in time domain, using the cross-correlation, and in the frequency domain, using a phase synchronization measure based on the Hilbert transform. A Shannon entropy index and magnitude squared coherence were also applied to improve analysis. Results Both groups presented low cross-correlation (0.18 ± 0.07 TG and 0.15 ± 0.08 UG) values between these signals, and only four from 16 subjects presented short epochs of phase synchronization (4.1 ± 8.6% TG and 3.2±7.3% UG) between signals, occurring at a low frequency band and random phase differences. The low to moderate coherence (0.67 ± 0.16 TG and 0.64 ± 0.16 UG) observed at 0.1 Hz appears to be an effect of the simultaneous action of sympathetic system over both cardiac and muscular rhythms. Conclusion The combined results suggest that the chosen exercise protocol was not able to cause cardiolocomotor synchronization.

Rice detector: proposal of a novel objective response detection technique

INTRODUCTION: The detection of the somatosensory response (SR) is an important tool for the neurophysiological evaluation in the intra and post-operative period of some vascular and spine surgeries. Particularly, the SR identification with a maximum false positive ratio by means of Objective Response Detection (ORD) techniques could lead to a less subjective procedure. In this work a novel ORD, the Rice Detector (RD), is presented and its theoretical critical value is obtained. METHODS: The probability of detection (PD) of RD is assessed for different numbers of eletroencephalographic (EEG) signal epochs (M = 30, 60, 120, 240) and signal-to-noise ratios (-20 to 10 dB, in steps of 1 dB) by means of simulation. The simulated PD curves (PDc) are compared with the theoretical ones and with the PDc of the Magnitude-Squared Coherence (MSC), a well-known ORD technique. The performance of RD and MSC are also compared for real EEG data. The comparison is based on the DP for estimates calculated with M = 30, 60, 120 and 240 epochs. RESULTS: The results showed that the simulated PDc follow the theoretical ones and both the MSC and RD present similar performance, with slight advantage for this latter at low M-values. However, for real data, no statistical significant difference (proportion test with alpha=0.05) was found between MSC and RD. CONCLUSION: Both techniques presented mean detection rates varying from 70% to 90%, even for intermediate M-value (120 epochs), and can be useful for evoked response detection applications.