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M. J. Vidya

Bio: M. J. Vidya is an academic researcher from R.V. College of Engineering. The author has contributed to research in topics: Encryption & Digital watermarking. The author has an hindex of 3, co-authored 14 publications receiving 41 citations.

Papers
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Journal Article
TL;DR: This biomedical paper is about 10:20 Electrode System is used to achieve the electroencephalograph (EEG) in neurology, where the main diagnostic application is in the case of epilepsy.
Abstract: This biomedical paper is about 10:20 Electrode System is used to achieve the electroencephalograph (EEG). In neurology, the main diagnostic application of EEG is in the case of epilepsy, as epileptic activity can create clear abnormalities on a standard EEG study. A secondary clinical use of EEG is in the diagnosis of coma, encephalopathy, and brain death. A third clinical use of EEG is for studies of sleep and sleep disorders where recordings are typically done for one full night. This is a technical review paper about the different devices/equipment using 10:20 electrode system method to achieve accurate analysis of EEG with ease.

27 citations

Proceedings ArticleDOI
22 Jun 2013
TL;DR: In this article, the fiber Bragg grating (FBG) was fabricated by etching the fiber BRG to a region where the total internal reflection is affected, which acts as high sensitive, fast response fluid optical switch in liquid level sensing, petroleum leakage detection etc.
Abstract: Detection of petroleum leakages in pipelines and storage tanks is a very important as it may lead to significant pollution of the environment, accidental hazards, and also it is a very important fuel resource. Petroleum leakage detection sensor based on fiber optics was fabricated by etching the fiber Bragg grating (FBG) to a region where the total internal reflection is affected. The experiment shows that the reflected Bragg’s wavelength and intensity goes to zero when etched FBG is in air and recovers Bragg’s wavelength and intensity when it is comes in contact with petroleum or any external fluid. This acts as high sensitive, fast response fluid optical switch in liquid level sensing, petroleum leakage detection etc. In this paper we present our results on using this technique in petroleum leakage detection.

5 citations

Journal Article
TL;DR: An overview of all filters which remove noise from ECG signal is taken, like FIR, smoothing, Golay, Gaussian etc, in this paper.
Abstract: The ECG an instrument, which records the electrical activity of heart. Electrical signals from the heart characteristically precede the normal mechanical function and monitoring of these signal has great clinical significance. ECG are used in catherization laboratories, coronary care units and for routine diagnostic applications in cardiology. Noise is an unwanted problem to achieve spike free ECG signal. To remove this problem we use various filter. In this paper we take an overview of all filters which remove noise from ECG signal. Filter used like FIR, smoothing, Golay , Gaussian etc. in this paper we survey on all type of filter which is used in to achieve noise free signal. Removing motion artifacts from an electrocardiogram (ECG) is one of the important issues to be considered during real-time heart rate measurements in telemetric health care. However, motion artifacts are part of the transient baseline change caused by the electrode motions that are the results of a subject's movement.

5 citations

01 Jan 2012
TL;DR: A brief review about home dialysis machines is given about homeDialysis machines to describe a situation when the kidneys fail to work.
Abstract: 3 ABSTRACT: Renal failure is a term to describe a situation when the kidneys fail to work. This may be a permanent or temporary failure. When the kidneys fail, Wastes begin to accumulate in the blood (uremia)As homeostasis is upset within the body, other organs can also begin to shut down - heart, liver, etc. The end result of renal failure is usually death unless the blood is filtered by some other means. The ideal intervention is to replace the failed kidneys with a donor kidney (STSE).While a person waits for a donor kidney, they usually have to undergo dialysis, a method where their blood is filtered and cleaned on a regular basis using machines. This paper gives a brief review about home dialysis machines.

3 citations

Journal ArticleDOI
TL;DR: Results illustrate that the uniqueness if augmentation index of 95% and dewatermarking of 98% are really reliable after retrieving the embedded information of a patient.

3 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a new application of optical frequency domain reflectometry (OFDR) technique is introduced to monitor both corrosion and leakage, and simulation tests are conducted to verify this method, where several optical fiber sensors were bonded to the pipe surface with the same interval, forming a sensor array.

167 citations

Journal ArticleDOI
TL;DR: This paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019, focusing on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach.
Abstract: Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions between humans and computers, the need for reliable and deployable solutions for the identification of human emotional states is required. Recent developments in using electroencephalography (EEG) for emotion recognition have garnered strong interest from the research community as the latest developments in consumer-grade wearable EEG solutions can provide a cheap, portable, and simple solution for identifying emotions. Since the last comprehensive review was conducted back from the years 2009 to 2016, this paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019. The focus on this state-of-the-art review focuses on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach. From this state-of-the-art review, we suggest several future research opportunities including proposing a different approach in presenting the stimuli in the form of virtual reality (VR). To this end, an additional section devoted specifically to reviewing only VR studies within this research domain is presented as the motivation for this proposed new approach using VR as the stimuli presentation device. This review paper is intended to be useful for the research community working on emotion recognition using EEG signals as well as for those who are venturing into this field of research.

129 citations

Journal ArticleDOI
TL;DR: In this article, a multichannel fiber Bragg grating (FBG) sensor array was used for dynamic strain-response measurements of cylindrical specimen subjected to uniaxial compression.

36 citations

Journal ArticleDOI
TL;DR: It was uncovered that incorporating reading- and writing-related tasks to experiments used in data collection may help improve existing EEG-based pattern classification frameworks for dyslexia, and those unwanted artefacts caused by body movements in the EEG signals during reading and writing activities could be minimised using artefact subspace reconstruction.
Abstract: Dyslexia is a disability that causes difficulties in reading and writing despite average intelligence. This hidden disability often goes undetected since dyslexics are normal and healthy in every other way. Electroencephalography (EEG) is one of the upcoming methods being researched for identifying unique brain activation patterns in dyslexics. The aims of this paper are to examine pros and cons of existing EEG-based pattern classification frameworks for dyslexia and recommend optimisations through the findings to assist future research. A critical analysis of the literature is conducted focusing on each framework’s (1) data collection, (2) pre-processing, (3) analysis and (4) classification methods. A wide range of inputs as well as classification approaches has been experimented for the improvement in EEG-based pattern classification frameworks. It was uncovered that incorporating reading- and writing-related tasks to experiments used in data collection may help improve these frameworks instead of using only simple tasks, and those unwanted artefacts caused by body movements in the EEG signals during reading and writing activities could be minimised using artefact subspace reconstruction. Further, support vector machine is identified as a promising classifier to be used in EEG-based pattern classification frameworks for dyslexia.

32 citations

Proceedings ArticleDOI
11 Mar 2016
TL;DR: An algorithm, developed for denoising high frequency noise from ECG signal which is based on moving average filter is presented, which need not requires redundant pre-processing steps, thus allowing a simple architecture for its implementation as well as low computational cost.
Abstract: The electro-cardiogram (ECG) is graphical representation of electro-mechanical activities of the heart. It reflects the state of heart and is very much useful in disease diagnosis. Since, ECG signal contains high frequency noise which is well known as power line interference hence, it must be removed for the further processing This paper presents an algorithm, developed for denoising high frequency noise from ECG signal which is based on moving average filter. The filtering process is followed by an algorithm for smoothing the ECG signal using polynomial curve fitting. Its denoising performance is implemented, smoothened and compared in C++ environment. The proposed algorithm need not requires redundant pre-processing steps, thus allowing a simple architecture for its implementation as well as low computational cost.

22 citations