Vandana Roy

Gyan Ganga Institute of Technology & Sciences · EC

This paper presents a boon and amend technique for eradicating the artifacts from the Electroencephalogram (EEG) signals. The abolition of artifacts from scalp EEGs is of considerable implication for both the computerized and visual investigation of fundamental brainwave activities. These noise sources increase the difficulty in analyzing the EEG a...

Present investigation reveals the quantum of work carried in the filtering methods for image de-noising. An image is often gets corrupted by various noises that are visible or invisible while being gathered, coded, acquired and transmitted. Noise influences various process parameters that may cause a quality problem for further image processing. De...

Biomedical applications coupled with IoT advancements help to bridge the gap between the physical and digital worlds, creating a hyper-connected society where objects are utilized not only to share data but are also becoming increasingly intelligent and aware of their context. This book takes a look into applications of the Internet of Things (IoT)...

The electroencephalography (EEG) signal is corrupted with some non-cerebral activities due to patient movement during signal measurement. These non-cerebral activities are termed as artifacts, which may diminish the superiority of acquired EEG signal statistics. The state of the art artifact elimination approaches applied canonical correlation anal...

Electroencephalogram (EEG) signals are progressively growing data widely known as biomedical big data, which is applied in biomedical and healthcare research. The measurement and processing of EEG signal result in the probability of signal contamination through artifacts which can obstruct the important features and information quality existing in...

Internet of Things in Biomedical Applications presents the current research areas in the Internet of Everything (IoE) applications for medical patient observation, monitoring, and symptomatic treatments. The book takes a broad area approach for both human-related parameters as well as the technical aspects of cloud, big data, security, networking a...

As the electroencephalography (EEG) biomedical signals are affected under the presence of the muscular motion artifacts. Presence of these artifacts leads to error in visual analysis of EEG signal, thus results in wrong diagnosis of human diseases. The variants of blind source separation (BSS) methods are available. This paper aims to design the ef...

Electroencephalogram (EEG) signal is usually suffered from motion artifacts, generated randomly during signal acquisition timings. These artifacts sturdily affect the investigation and therefore, diagnosis of neural diseases from EEG signal. The artifact removal may cause loss of important information from the signal. Therefore, it is required to r...

The sleep stages determination is important for the identification and diagnosis of different diseases. An efficient algorithm of wavelet decomposition is used for feature extraction of single channel EEG. The Chi-Square method is applied for the selection of the best attributes from the extracted features. The classification of different staged te...

The motion generated at the capturing time of electro-encephalography (EEG) signal leads to the artifacts, which may reduce the quality of obtained information. Existing artifact removal methods use canonical correlation analysis (CCA) for removing artifacts along with ensemble empirical mode decomposition (EEMD) and wavelet transform (WT). A new a...

The Big data as Electroencephalography (EEG) can induce by artifacts during acquisition process which will obstruct the features and quality of interest in the signal. The healthcare diagnostic procedures need strong and viable biomedical signals and elimination of artifacts from EEG is important. In this research paper, an improved ensemble approa...

Artifacts frequently corrupt biomedical signal recording and processing, therefore, removal of these artifacts from physiological signals is an essential step. The acuteness in the performance of healthcare technology has upgraded from the current hospital-centric environment towards portable ubiquitous approaches. The uncertainty in the subsequent...

Ferrite circulators are required to provide isolation between mismatched cavity and RF source. As a part of indigenous circulator development program, a 476 MHz strip line circulator has been designed and modeled using CST Microwave Studio, for RF system of Infra-Red Free-Electron Laser at RRCAT, Indore. Circulator subsystems viz. calcium vanadium...

Directional Coupler (DC) is a passive device which is primarily employed for monitoring purposes. Itis also used in wide range of applications such as antenna feeds, balanced mixers, modulators, phase shifters, as power combiners, as reflectometers. The paper discusses the designing issues of a coupled line-microstripline directional coupler and de...

Presence of artifacts in electroencephalographs (EEG) is major hurdles for the precise analysis of spectral behavior. For suppression of ocular artifact in EEG this paper proposes a component based Independent Component Analysis (ICA) model. It involves the generating a set of individual components of given signal followed by rejection of unwanted...

Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI), Computer tomography (CT), and Ultrasound imaging. This work synopsis proposes a medical image denoising algorithm using an adaptive filter structure for discrete wavelet transform. The presence of noise in biomedical images is a majo...

Presence of artifacts in electroencephalogram (EEG) signals is significant hurdles in analysis of spectral behavior. These artifacts are the low amplitude signals from unconscious ocular activity and muscles activity of human body. Since the source and noise in received signals originate from different sources, ICA method has been extensively revis...

The EEG signals are the prime sources to diagnose and manipulate Epilepsy, state of coma and numerous studies. The EEG signals in the active brains constitute various body activities controlled or out of human consciousness. There exist considerable researches that focus to minimize the artifact values in the EEG domain. This paper is the evaluatio...

Ultrasonic images are generally affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. Speckle filtering is thus a critical pre-processing step in medical ultrasound imagery provided that the features of interest for diagnosis are not lost. We present a novel speckle removal algorithm within the...

Independent Component Analysis is used for the automation and detection of brain artifacts. The Independent Component Analysis (ICA) here is used for the segmentation of artifact peaks in the signal. Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result. We have extended our...

This chapter proposes an automatic method for artifact removal and noise elimination from scalp electroencephalogram recordings (EEG). The method is based on transform domain method having combination of data adaptive and non-data adaptive transform domain image denoising method to improve artifact elimination (ocular, high frequency muscle, and el...

An image is inevitably corrupted by noise in its acquisition or transmission. Noises in an image can degrade severely the follow-up image processing tasks, such as image feature extraction, coding, segmentation, and target detection. Thus noise reduction becomes a very important image pre-processing for improving the quality of image and meeting th...