We presented a comparative study on the training methodologies of convolutional neural network (CNN) for detection steady-state visually evoked potentials (SSVEP). Two scenarios were also compared: user-independent (UI) and user-dependent (UD) training.The CNN was trained in both UD UI two types features SSVEP classification: magnitude spectrum (M-CNN) complex (C-CNN). The canonical correlation analysis (CCA), widely used processing, as baseline. Additional comparisons performed with...

This study evaluated the effect of change in background on steady state visually evoked potentials (SSVEP) and motion (SSMVEP) based brain computer interfaces (BCI) a small-profile augmented reality (AR) headset. A four target SSVEP SSMVEP BCI was implemented using Cognixion AR headset prototype. An active (AB) non-active (NB) were evaluated. The signal characteristics classification performance two paradigms studied. Offline analysis performed canonical correlation (CCA) complex-spectrum...

A key issue in brain-computer interface (BCI) is the detection of intentional control (IC) states and non-intentional (NC) an asynchronous manner. Furthermore, for steady-state visual evoked potential (SSVEP) BCI systems, multiple (sub-states) exist within IC state. Existing recognition methods rely on a threshold technique, which difficult to realize high accuracy, i.e., simultaneously true positive rate low false rate. To address this issue, we proposed novel convolutional neural network...

Motor imagery (MI)-based Brain-Computer Interfaces (BCIs) have shown promise in engaging the motor cortex for recovery. However, individual responses to MI-based BCIs are highly variable and relatively weak. Conversely, combined action observation (AO) (MI) paradigms demonstrated stronger compared AO or MI alone, along with enhanced cortical excitability. In this study, a novel BCI called Combined AO, MI, Steady-State Motion Visual Evoked Potential (SSMVEP) (CAMS) was proposed. CAMS designed...

In recent years, there has been increased interest in video summarization and automatic sports highlights generation. this work, we introduce a new dataset, called SNOW, for umpire pose detection the game of cricket. The proposed dataset is evaluated as preliminary aid developing systems to automatically generate cricket highlights. cricket, authority make important decisions about events on field. signals using unique hand gestures. We identify four such classification namely SIX, NO BALL,...

Objective. Different visual stimuli might have different effects on the brain, e.g. change of brightness, non-biological movement and biological movement.Approach. In this study, flicker, checkerboard gaiting were chosen as to investigate whether steady-state motion evoked potential (SSMVEP) effect sensorimotor area for rehabilitation. The stimulus was designed sequence a human. hypothesis is that only observing would simultaneously induce: (1) SSMVEP in occipital area, similarly an SSVEP...

User-independent Brain Computer Interfaces (BCIs) have gained increased attention in recent years for their attractive feature of having minimal or zero calibration. BCIs based on steady state visual evoked potentials (SSVEP) the most favorable characteristics developing user-independent BCIs. In this study, we proposed use complex Fast Fourier Transform (FFT) features as input to a Convolutional Neural Network (CNN) classifying SSVEP responses without user specific training. Our method...

Steady-state visual evoked potentials (SSVEP) are responses elicited when a user is presented with repetitive stimulus. Change in stimuli proximity has been shown to have an influence on the performance of SSVEP-based BCI, where inter-stimulus distance positive correlation overall performance. This limits flexibility stimulus design by imposing constraint acceptable distance, consequently limiting range applicability for BCIs real-world applications. Another limitation that needs be...

Facial expression recognition has been an active area in computer vision with application areas including animation, social robots, personalized banking, etc. In this study, we explore the problem of image classification for detecting facial expressions based on features extracted from pre-trained convolutional neural networks trained ImageNet database. Features are and transferred to a Linear Support Vector Machine classification. All experiments performed two publicly available datasets...

Stimulus proximity has been shown to have an influence on the classification performance of a steady-state visual evoked potential based brain-computer interface (SSVEP-BCI). Multiple stimuli placed close each other compete for neural representations leading effect competing stimuli. In this study, we propose convolutional network (CNN) method enhance detection accuracy SSVEP in presence A seven-class dataset from ten healthy participants was used evaluating proposed method. The results were...

Flicker is the most widely used steady-state visual evoked potential (SSVEP) stimulus. In addition, checkerboard can induce motion (SSMVEP) in occipital area. More recently, action video proposed to simultaneously elicit SSMVEP and sensorimotor area activations via mirror neuron systems through Action Observation (AO). Integration of AO with brain-computer interface (BCI) appealing for neural rehabilitation applications. order make such a BCI paradigm more feasible rehabilitation, it...

Designing a self-paced brain computer interface (BCI) that works reliably across human subjects has been challenge. Of particular interest are simple BCIs enable detection of an Intentional Control (IC) state against background No (NC) state. Such known as switches or BCI switches. One the possible methods to build switch is based on consistent increase in alpha component EEG spectrum when close their eyes. The present work proposes approach achieve automatic user customization with just one...

In the era of digital marketing, it is imperative for brands to reach target segment precisely maximize their marketing ROI. most cases, segments are created based on broad demographic and psychographic traits without any knowledge consumer brand preferences. this paper, we propose a methodology predict individual level preference historical visitation patterns. We believe that first attempt successful deployment at large scale. general, very hard accumulate longitudinal location data...

Democratization of information access brought about by digital distribution has resulted in two contradictory phenomena: the ability to personalize consumer experience, and greater anonymity users. These intensify when is consumed on mobile devices, particularly because techniques profile users desktop web do not work smart-devices. Yet, already large still fast-growing field advertising require activation audience segments against campaigns. Of particular importance are age gender users, as...

Identifying valuable customers as well retaining them has become key component for any business to succeed in this competitive market. Businesses have also realized that relying solely on its own transactional data, might not be sufficient longer, meet the required objectives. There is a need partner and leverage power of big data available from external sources add more value. In paper, we are detailing methodology mashing up Mobilewalla's high scale mobile consumer with one world's largest...

Brain-computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEP) are considered as one of the most successful noninvasive BCI paradigms. Recently, an evolution SSVEP was introduced with repetitive motion visual stimuli instead conventional flickering stimuli. This novel paradigm is potential (SSMVEP), and it has been proposed to address some inherent limitations stimulus. One important factor that affects decoding performance BCIs stimulus change in inter-stimulus...

This study presents automated sleep staging on a large number of electroencephalography (EEG) recordings collected using the Muse S headband. Two recent deep learning models; single-channel Deep Sleep Net (DSN) and multi-channel (MNet) were evaluated 5-class stage classification task 200 expert-labelled overnight EEG recordings. The learned representations models visualized uniform manifold approximation projection (UMAP). Moreover, scale analysis relationship between distribution non-rapid...

This paper introduces a hands-on laboratory exercise focused on assembling and testing hybrid soft-rigid active finger prosthetic for biomechanical biomedical engineering (BME) education. activity focuses the design of myoelectric prosthesis, integrating mechanical, electrical, sensor (i.e., inertial measurement units (IMUs), electromyography (EMG)), pneumatics, embedded software concepts. We expose students to robotic system, offering flexible, modifiable lab that can be tailored...

In the rapidly evolving retail landscape, optimizing operations has become critical to maintaining competitive advantage and enhancing customer satisfaction. This paper explores transformative impact of machine learning (ML) big data analytics on operations. By leveraging advanced science techniques, retailers can gain actionable insights into inventory management, behavior, supply chain efficiencies. Machine algorithms facilitate predictive analytics, enabling accurate demand forecasting...

Steady state visually evoked potentials (SSVEP) are periodic responses elicited when a participant looks at visual stimulus flickering particular frequency. Brain computer interfaces (BCI) based on SSVEP have been shown to consistent across most human subjects. We use this property for designing two-state BCI switch. Canonical correlation analysis (CCA) is used distinguish between the intentional control and no states of The traditional approach using CCA detection uses target frequencies...

Changes in stimuli proximity have been shown to affect the performance of brain computer interfaces (BCI) based on steady-state visual evoked potentials (SSVEP). Specifically, closely placed compete for neural representations, which is called effect competing stimuli. Recently, motion potential (SSMVEP) has proposed alleviate some inherent limitations SSVEP. In this study, SSVEP and SSMVEP paradigms were systematically compared under three different inter-stimulus distances modulate Offline...