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Browsing Conference proceedings by Author "Geethalakshmi, S N"

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    Artifact Removal from EEG using Spatially Constrained Independent Component Analysis and Wavelet Denoising with Otsu’s Thresholding Technique
    (2012) Geethalakshmi, S N
    This paper presents a novel technique for removing the artifacts from the ElectroEncephaloGram (EEG) signals. EEG signals are influenced by different characteristics, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). The elimination of artifact from scalp EEGs is of substantial significance for both the automated and visual examination of underlying brainwave actions. These noise sources increase the difficulty in analyzing the EEG and obtaining clinical information related to pathology. Hence it is crucial to design a procedure to decrease such artifacts in EEG records. This paper uses Spatially-Constrained Independent Component Analysis (SCICA) to separate the Independent Components (ICs) from the initial EEG signal. As the next step. Wavelet Denoising (WD) is applied to extract the brain activity from purged artifacts, and finally the artifacts are projected back and subtracted from EEG signals to get clean EEG data. Here, thresholding plays an important role in delineating the artifacts and hence a better thresholding technique called Otsu’, thresholding is applied. Experimental results show that the proposed technique results in better removal of artifacts.
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    Brewing Heterogeneous Devices for Monitoring Cerebrovascular Oxygenation
    (2016) Geethalakshmi, S N
    Technologies encumbering Wireless Sensor Network with its effulgence and ubiquity in Sensing plays a dominant role in Health care industry and Health monitoring System. Impeccable blending of Actuators and networking them for a viable communication across varied platforms paves gateway for triumphant loT solution. loT plays a predominant role in revitalizing the healthcare sector with appendages of several smart devices deliberated to facilitate medicos, surgeons and subjects to monitor each and every aspect of their health. Customary health checkups allow patients to distinguish health issues sooner and get treatment accordingly. loT offers a cost effective solution adjunct with a timely intervention.
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    Detecting Epileptic Seizures Using Electroencephalogram: A Novel Frequency Domain Feature Extraction Technique for Seizure Classification using Fast ANFIS
    (2012) Geethalakshmi, S N
    Epileptic seizures usually results in a mixture of temporal alterations in perception and behavior. Epilepsy is considered to be one of the highly frequent neurological disorders. A considerable manner for detecting and examining epileptic seizure behavior in humans is Electroencephalogram (EEC) signal examination. EEC classification is a significant process in Brain Computer Interface (BCl) that offers a new dimension in human computer interface, directly linking a computer with human thinking. Identification of the epileptic EEC signal has been performed manually. Recently, automated epileptic seizure identification with the help of EEC signals has become an active of research. This paper presents an implementation of automated epileptic EEG detection system. In this paper, frequency domain feature extraction is carried out through Fast Fourier Transform to the process of classifying EEG signals. For classification this paper uses Fast Adaptive Ncuro-Fuzzy Inference System (ANFIS) which utilize the modified Levenberg-Marquardt algorithm for learning. Experimental results show that the proposed system results in higher accuracy of classification at lesser time.
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    Digital Image Processing: Methods and Applications
    (2010) Geethalakshmi, S N
    In electrical engineering and computer science, image processing is any form of signal processing that converts the raw form of an input image into a usable and often meaningful output image. There are several standard techniques available for image processing and these techniques are broadly classified as image ^enhancement and image analyzing techniques. This paper discusses some of the most frequently used methods under this category.
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    Influence of Non-Technical Components on Software Development
    (2010) Geethalakshmi, S N
    The success or failure of Software Project management consists of two components, namely the technical and non-technical components of software development. Non-technical related components of software development process tend to be under managed. Further research on success and failure of software projects developed in-house are sparse. Therefore a study was conducted in India among the industries that are into in-house software development, to investigate the influence of the nontechnical components of the software development process, on success and failure of software development from the practitioners’ perspective. The Study reveals that practitioners’ consider the level of customer/user involvement, software process management, and estimation & schedule contribute most to project success and failure.