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The feasibility of utilizing concurrent electroencephalography (EEG) and functional Near infrared spectroscopy (fNIRS) recording to characterize the difference in cortical activities between stroke patients (n=3) and healthy controls (n=3) was evaluated with a motor execution task. The asymmetry indicators, including inter-hemispheric sample entropy (IHI_En) derived from EEG signal and inter-hemispheric...
Alteration of neuron structure can induce abnormalities in signal propagation for nervous systems, as seen in traumatic brain injuries, damage and tumours. Here, effects of geometrical changes and damage of neuron structure are investigated in two scaled nerve bundle models, made of myelinated and unmyelinated nerve fibres. We propose a 3D finite element model of a nerve bundle as a unique framework...
Visual-evoked potential (VEP)-based BCIs have been shown to provide the highest information transfer rates and reliability among BCI approaches. However, to date, no flexible software platform exists that allows investigators and end-users to easily evaluate and optimize VEP stimulus parameters such as size, position, flashing rate, color, etc., with seamless integration to an application environment...
Restoring normal walking abilities following the loss of them is a challenge. Importantly, there is a growing need for a better understanding of brain plasticity and the neural involvements for the initiation and control of these abilities so as to develop better rehabilitation programmes and external support devices. In this paper, we attempt to identify gait-related neural activities by decoding...
This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Related Cortical Potential (MRCP) detection. The algorithm was compared with the Locality Preserving Projection (LPP) algorithm in the context of detecting foot dorsiflexion within a group of thirteen subjects. It has been shown that CSPPC achieved a significantly reduced delay latency compared to LPP (−25...
Surgical removal of seizure-generating brain tissue can cure epilepsy in patients who do not respond to medications. However, identifying seizure-generating regions is difficult and fails in many cases. In this paper, we report a fully unsupervised and automated approach to seizure focus localization using a Bayesian filter. This method uses a spectral domain feature, Power in Bands (PIB). PIB is...
Across neuroscience research, clinical diagnostics, and engineering applications in pain evaluation and treatment, there is a need for an objective measure of pain experience and detection when it occurs. This detector should be reliable in real-world settings using easily accessible, non-invasive data sources. We present a simple yet robust paradigm for decoding pain using neural and physiological...
Target image detection based on rapid serial visual presentation (RSVP) paradigm is a typical brain-computer interface with various applications, such as image retrieval. In an RSVP paradigm, the P300 component is detected to determine the target image, which requires high-precision single-trial P300 detection methods. However, compared to multi-trial P300 detection methods, the performance of single-trial...
Dual tasking refers to the simultaneous execution of two tasks with different demands. In this study, we aimed to investigate the effect of a second task on a main task of motor execution and on the ability to detect the cortical potential related to the main task from non-invasive electroencephalographic (EEG). Participants were asked to perform a series of cue-based ankle dorsiflexions as the primary...
Electroencephalography has been studied to understand various brain functions. These functions can be related to their frequency and spatial patterns. These properties are relatively unknown in infants. The first year of life includes stages of significant growth neurologically and behaviorally. The present study is aimed to investigate infant brain development using high-density EEG(124 channel)...
It is known that signs of early auditory selective attention are reflected in the N1-wave of auditory late potentials. In recent years, we used instantaneous phase synchronization measures related to this N1-effect to assess the attentional effort in listening. In particular, we showed that listening effort induced by task difficulty can be quantified by using this method. Subsequently, in order to...
Verbal communication makes human unique from other species. People use different modalities of speech while communicating with others. Widely practised modalities are speak loudly (utter), whispering and mumbling with closed lips. Apart from speaking, people also speak in their mind. Due to different ailments or injury, some people have lost their ability to speak and are forced to take other means...
In Brain Computer Interfaces (BCIs), with multiple recordings from different subjects in hand, a question arises regarding whether the knowledge of previously recorded subjects can be transferred to a new subject. In this study, we explore the possibility of transferring knowledge by using a convolutional network model trained on multiple subjects and fine-tuning the model on a small amount of data...
Electroencephalography (EEG) processing methods mostly focus on extracting its spectral or spatial features, which are proven to discriminate bilateral hand movement, hand movement directions and speed. The focus of current study is to explore EEG time-domain features that represent neural correlates of hand movement execution speed. In this paper, we propose autocorrelation analysis of EEG and features...
Parkinson's disease (PD) is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. Deep brain stimulation (DBS) has been used to treat advanced PD successfully. Previous studies have found that the DBS also has an effect on the electrophysiological activity of the deep brain nucleus while alleviate the PD symptoms. Here, in an attempt to gain a greater understanding of...
P300-based brain-computer interface (BCI) is one of the most common BCIs. Due to the characteristics of P300 responses vary from person to person, it leads to the necessity of collecting much labeled data from each user and the problem of time-consuming in many applications. In this work, a transfer learning method which dynamically adjusts the weights of instances is applied to improve the P300-based...
Epidural spinal cord stimulation (SCS) is a promising therapy for spinal cord injury (SCI). This paper combines experimental data from epidurally-stimulated human paraplegic patients with computational models of SCS to identify the electric field features correlated with the patients' ability to stand. We locate the spinal cord regions most critical to stimulated standing and find that the most informative...
This paper presents an original framework based on deep learning and preference learning to retrieve and characterize biomedical images for assisting physicians in diagnosing complex diseases with potentially only small differences between them. In particular, we use deep learning to extract the high-level and compact features for biomedical images. In contrast to the traditional biomedical algorithms...
In this paper, the thickness change of biceps brachii during the fatigue process is continuously monitored using one micro-size single-element ultrasound transducer and analyzed by the echo tracking algorithm. We focus on isometric, 50 % maximum voluntary contraction (MVC) of the elbow. Four subjects participates in the experiment and the result shows that the muscle thickness of biceps brachii continues...
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