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Steady-state visual evoked potential (SSVEP) has become one of the most widely employed modalities in online brain computer interface (BCI) because of its high signal-to-noise ratio. However, due to the limitations of brain physiology and the refresh rate of the display devices, the available stimulation frequencies that evoke strong SSVEPs are generally limited for practical applications. In this...
Actigraphy is effective at monitoring circadian rhythms, but often misidentifies periods of restless sleep (defined here as sleep periods with movement) as wake, and periods of quiet wake as sleep. This limitation restricts the effectiveness of actigraphy for investigating sleep disorders. Our objective in this study was to investigate a time-frequency representation of movement during sleep and wake...
Successful brain-computer interfaces (BCIs) swiftly and accurately communicate the user's intention to a computer. Typically, information transfer rate (ITR) is used to measure the performance of a BCI. We propose a multi-step process to speed up detection and classification of the user's intent and maximize ITR. Users randomly looked at 4 frequency options on the interface in two sessions, one without...
Steady-state visual evoked potentials (SSVEPs) are widely used in the design of brain-computer interfaces (BCIs). A lot of effort has therefore been devoted to find a fast and reliable way to detect SSVEPs. We study the link between transient and steady-state VEPs and show that it is possible to predict the spectral content of a subject's SSVEPs by simulating trains of transient VEPs. This could lead...
The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests...
Current EEG based brain computer interface (BCI) systems have achieved successful control in up to 3 dimensions; however the current paradigm may be unnatural for many rehabilitative and recreational applications. Therefore there is a great need to find motor imagination (MI) tasks that are realistic for output device control. In this paper we present our results on classifying hand gesture MI tasks,...
While motor imagery has been known as a powerful tool for neuro-rehabilitation in stroke patients, whether this technique is also effective for other brain disorders is unclear. For instance, patients with Parkinson's disease or attention-deficit hyperactivity disorder who are impaired at real motor switching may benefit therapeutically from training that consists of switching their imagined motor...
Resting-state fMRI (rs-fMRI) studies of the human brain have demonstrated that low-frequency fluctuations can define functionally relevant resting state networks (RSNs). The majority of these methods rely on Pearson's correlation for quantifying the functional connectivity between the time series from different regions. However, it is well-known that correlation is limited to quantifying only linear...
We propose a novel approach for measuring the stationarity level of multichannel time-series. This measure is based on stationarity definition over time-varying spectra and aims to quantify the relationship between local (single-channel dynamics) and global (multichannel dynamics) stationarity. With the purpose of separate among several motor/imagery tasks, we asssume that movement imagination implies...
Radiofrequency catheter ablation of atrial fibrillation (AF) guided by complex fractionated atrial electrograms (CFAE) is associated with a high AF termination rate in paroxysmal AF, but not in persistent. CFAE does not always identify favorable sites for persistent AF ablation. Studies suggest that only high fractionation level should be used as a target site for ablation. Nonetheless, there are...
An effective mechanism in neuronal communication is oscillatory neuronal synchronization. The neuronal gamma-band (30–100 Hz) synchronization is associated with attention which is induced by a certain visual stimuli. Numerous studies have shown that the gamma-band activity is observed in the visual cortex. However, impact of different head modeling techniques and sensor types to localize gamma-band...
The non-invasive monitoring of the frequency of intestinal pacemaker activity (slow wave, SW) has an important diagnostic value. However the presence of noise, physiological interferences and spurious peaks of the spectral estimators can yield to misidentification of SW frequency when using conventional dominant frequency detection method. In this paper, two methods of ridge extraction from the time-frequency...
Owing to the recent advances in multi-modal data analysis, the aim of the present study was to analyze the functional network of the brain which remained the same during the eyes-open (EO) and eyes-closed (EC) resting task. The simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) were used for this study, recorded from five distinct cortical regions of the brain. We focused...
In this paper we examined the robustness of a feature-set based on time-frequency distributions (TFDs) for neonatal EEG seizure detection. This feature-set was originally proposed in literature for neonatal seizure detection using a support vector machine (SVM). We tested the performance of this feature-set with a smoothed Wigner-Ville distribution and modified B distribution as the underlying TFDs...
Brain activities are often investigated through Electroencephalographic (EEG) data analysis using timedomain Independent Component Analysis (ICA). Nevertheless, the instantaneous mixing model of ICA cannot properly describe spatio-temporal dynamics, such as those related to traveling waves of neural activity. In this work, we exploit the application of the Complex ICA (cICA) to describe the underlying...
Electric cell-substrate impedance sensing (ECIS) is a powerful instrument for quantifying cell behavior in tissue culture. As cells attach and spread on the sensing electrode, they restrict the current flow and hence cause the increase of electrical impedance. Furthermore, cell motion may reveal itself as electrical fluctuations, which are always associated with living cells and continue even when...
We present an accurate seizure detection algorithm, and make a detailed comparison of two frequency analysis methods: a widely used stationary method — Fast Fourier Transform (FFT) and a relatively new nonstationary method — Hilbert-Huang Transform (HHT). Two public databases and one our own database were tested. The results show that our algorithm has very high accuracy compared with the state-of-the-art...
Muscle fatigue is a neuromuscular condition where muscle performance decreases due to sustained or intense contraction. It is experienced by both normal and abnormal subjects. In this work, an attempt has been made to analyze the progression of muscle fatigue in biceps brachii muscles using surface electromyography (sEMG) signals. The sEMG signals are recorded from fifty healthy volunteers during...
In this paper, we have focused on the issue of regulating the human heart rate (HR) to a predefined reference trajectory, especially for cycle-ergometer exercise used for training or rehabilitation. As measuring HR is relatively easy compared to exercise intensity, it has been used in the wide range of training programs. The aim of this paper is to develop a non-model-based control strategy using...
It is known that standing induces orthostatic stress on the cardiovascular system. Our previous works have presented that the postural control during standing and cardiovascular changes are related to each other in the health young individuals. However, it remains to be checked if such a relationship is present in the elderly individuals as well. The present study conducted experiments similar to...
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