Nikesh Bajaj

Queen Mary, University of London | QMUL · School of Electronic Engineering and Computer Science

Understanding the mechanism sustaining cardiac fibrillation can facilitate the personalization of treatment. Granger causality analysis can be used to determine the existence of a hierarchical fibrillation mechanism that is more amenable to ablation treatment in cardiac time-series data. Conventional Granger causality based on linear predictability...

Modern deep neural networks (DNNs) have shown promising results in brain studies involving multi-channel electroencephalogram (EEG) signals. The representations produced by the layers of a DNN trained on EEG signals remain, however, poorly understood. In this paper, we propose an approach to interpret deep representations of EEG signals. Our approa...

Mixed reality (MR) blends the physical and digital environments using natural interactions. In MR, users experience computer-generated content in the physical world by wearing a head-mounted display unit. MR domain is still in its infancy with several open questions on immersion, comfort, user interactions, and user experience. Specifically, game u...

Background Subtle prognostically-important ECG features may not be apparent to physicians. In the course of supervised machine learning (ML), many thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. Hypothesis Novel neural network (NN)-derived ECG features can predict future cardiovascular...

Background Subtle, prognostically-meaningful ECG features may not be apparent to physicians. In the course of supervised machine learning training, many thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. These novel neural network (NN)-derived ECG features may have clinical, phenotypic, an...

Background Subtle, prognostically-meaningful ECG features may not be apparent to physicians. In the course of supervised machine learning ML training, many thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. These novel neural network (NN)-derived ECG features may have clinical, phenotypic,...

Lower body tracking and user experience analysis are ongoing challenges in immersive technologies and biomechanics research, respectively. Particularly, in immersive technologies like mixed reality, there are limited research applications in user comfort and experience, and locomotion. In this paper, we aimed to conduct a cross-disciplinary researc...

This paper explores the important factors of job interviews that can be gamified and incorporated into a virtual reality interview training application. Virtual reality and gamification have demonstrated benefits in training, simulation, and education. Specifically, virtual reality can be helpful in creating simulations of realistic job interview s...

There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable...

Background Obesity is a growing global health problem that confers higher risks of atrial arrhythmias and sudden cardiac death. Despite this, the proarrhythmic substrate in obesity and its reversibility with weight loss has not been studied in-depth. Purpose To characterise the proarrhythmic substrate in obese patients, and its reversibility with...

Unlike conventional data such as natural images, audio and speech, raw multi-channel Electroencephalogram (EEG) data are difficult to interpret. Modern deep neural networks have shown promising results in EEG studies, however finding robust invariant representations of EEG data across subjects remains a challenge, due to differences in brain foldin...

Background Obesity confers higher risks of atrial arrhythmias and sudden cardiac death. Despite this, the proarrhythmic substrate in obesity and its reversibility with weight loss has not been studied in-depth. To address this, the proarrhythmic substrate in obese patients, and its reversibility with bariatric surgery, was characterised using elect...

Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): National Institute for Health Research (NIHR) British Heart Foundation Background Obesity confers higher risks of atrial arrhythmias and is associated with abnormal ventricular repolarisation. Despite this, the proarrhythmic substrate in obesity and it...

Atrial fibrillation (AF) is the most common arrhythmia and causes significant morbidity and mortality. Early identification of AF may lead to early treatment of AF and may thus prevent AF-related strokes and complications. However, there is no current formal, cost-effective strategy for population screening for AF. In this review, we give a brief o...

One of the most striking characteristics of e-Learning audiences is their diversity. Native and non-native learners can be expected among such audiences and therefore, when developing e-Learning courses it is important to consider the impact of the language level on learning. Specifically, non-native learners are expected to have a diminished audit...

This chapter introduces the applications of wavelet for Electroencephalogram (EEG) signal analysis. First, the overview of EEG signal is discussed to the recording of raw EEG and widely used frequency bands in EEG studies. The chapter then progresses to discuss the common artefacts that contaminate EEG signal while recording. With a short overview...

Auditory attention to natural speech is a complex brain process. Its quantification from physiological signals can be valuable to improving and widening the range of applications of current brain-computer-interface systems, however it remains a challenging task. In this article, we present a dataset of physiological signals collected from an experi...

Brain–computer interface (BCI) systems are becoming increasingly popular nowadays. Electroencephalogram (EEG) signals recorded by BCI systems are however frequently contaminated by artifacts and while applying any artifact removal algorithm, precautions should be taken not to remove useful information. Widely and most popular approaches to remove a...

Auditory attention is fundamental also in serious games. This paper synthetizes the results of a recent statistical analysis of auditory attention of non-native learners and proposes indications for serious game design. We propose a 3-dimensional difficulty level model that can be applied both for designing game levels and adaptivity to keep a play...

In recent years designing a game for education has become very popular. Neuroscience has developed many theories of learning, based on how brain learns. We discuss a design approach for conventional teaching methods. The proposed approach illustrates the opportunities to exploit the concept of neuroscience and combine it with game for educational p...

Since decades, in the field of face expression recognition, many researchers have been developing numerous new techniques. These developments are being fueled by numerous advances in computer vision. Such advancement in the field of computer vision holds a promise of reducing error rate in face expression recognition system. This paper proposes an...

Fractals have always been associated with the term chaos. To many chaologists, the study of chaos and fractals is more than just a new field in science which fascinates the researchers to work on a theory that unifies mathematics, physics, art, and computer science - it is a revolution in science. Nature has used fractal designs for at least hundre...

Understanding human motions can be posed as a pattern recognition problem. Applications of pattern recognition in information processing problems are diverse ranging from Speech, Handwritten character recognition to medical research and astronomy. Humans express time-varying motion patterns (gestures), such as a wave, in order to convey a message t...

In signal processing, wavelet transform is used mainly for compression purposes and fractional fourier transform has find its applications in the field of filtering operations, optics and various other fields. This paper designs new family of wavelets combining both the transformation techniques. The new wavelets are unique to a respective fraction...

In recent years, image encryption has grown much to provide information security to end user. There are various algorithms for encrypting the image. RC5 is a block cipher and can be used for image encryption. In this paper, weaknesses of RC5 for image encryption are discussed and analysed. Further, improvement in RC5 algorithm is done. Improvement...

The Global System for Mobile communication, GSM is the most widely used cellular system in the world, with over a billion customers around the world. GSM was the first cellular system which seriously considered security threats. Previous cellular systems had practically no security, and they were increasingly the subject of criminal activity such a...

The Global System for Mobile communication, GSM voice calls are encrypted using a family of algorithms collectively called A5. A5/1 is the stream cipher which encrypts the information transmitted from mobile user. Initially A5 algorithm was kept secret to ensure the security but as algorithm was disclosed many cryptanalytic attacks were proposed an...

Fractional Fourier Transform (FRFT) is the generalization of the classic Fourier Transform (FT). When we dealing with time-varying signals, FRFT is an important tool to analysis these signals. This paper contain the results for variation of basic signals like Rectangular pulse, sine wave and Gaussian signal in the Fractional Fourier Domain (FRFD)....