L.N. Sharma

L.N. Sharma
Indian Institute of Technology Guwahati | IIT Guwahati · Department of Electronics and Electrical Engineering (EEE)

PhD (Biomedical Signal Processing)

About

78
Publications
10,836
Reads
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964
Citations
Citations since 2016
40 Research Items
759 Citations
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
Introduction
L.N. Sharma currently works at the Department of Electronics and Electrical Engineering (EEE), Indian Institute of Technology Guwahati. Their current project is 'Cardiac Pathology and Signal Processing.'
Additional affiliations
December 1996 - May 2016
Indian Institute of Technology Guwahati
Position
  • Senior TO

Publications

Publications (78)
Article
Full-text available
Non-contact human body vital parameter measurements are getting more attention and have been extensively studied in a short span of time. One of such techniques is the heart rate (HR) estimation based on video recording of human face known as remote photoplethysmogram (rPPG). Usually, the recorded video gets contaminated due to illumination variati...
Conference Paper
Accurate detection of fiducial points is a challenging task for an electrocardiogram (ECG) signal and failing to achieve the desired features can degrade the performance of the ECGbased biometrics. This paper presents a robust ECG-based biometric framework for user authentication, which does not require the detection of fiducial points. In the prop...
Article
Pulse transit time (PTT) has been widely used for cuffless blood pressure (BP) measurement. But, it requires more than one cardiovascular signals involving more than one sensing device. In this paper, we propose a method for cuffless continuous blood pressure measurement with the help of left ventricular ejection time (LVET). A MEMS-based accelerom...
Article
Full-text available
In this paper, aortic ejected blood-flow and aortic pressure is investigated as an independent tool for diagnosing cardiovascular risk. This study presents vibrocarotidography (ViCG), a novel noninvasive and nonintrusive way to measure aortic blood-flow variations in each heartbeat through carotid arteries. Most of the existing state-of-the-art wor...
Article
Full-text available
As a vital risk stratification tool, heart rate variability (HRV) has the ability to provide early warning signs for many life-threatening diseases. This paper presents a study on reliable cardiac cycle extraction and HRV measurement with a seismocardiographic (SCG) method. Like R-peaks in an ECG, the proposed method relies on peaks corresponding t...
Article
In this work, a seismocardiogram (SCG) based breathing-state measuring method is proposed for m-health applications. The aim of the proposed framework is to assess the human respiratory system by identifying degree-of-breathings, such as breathlessness, normal breathing, and long and labored breathing. For this, it is needed to measure cardiac-indu...
Preprint
Full-text available
Pulse transit time (PTT) has been widely used for cuffless blood pressure (BP) measurement. But, it requires more than one cardiovascular signals involving more than one sensing device. In this paper, we propose a method for continuous cuffless blood pressure measurement with the help of left ventricular ejection time (LVET). The LVET is estimated...
Chapter
Full-text available
Brain state classification using electroencephalography (EEG) finds applications in both clinical and non-clinical contexts, such as detecting sleep states or perceiving illusory effects during multisensory McGurk paradigm, respectively. Existing literature mostly considers recordings of EEG electrodes that cover the entire head. However, for real...
Preprint
Full-text available
Precise estimation of fiducial points of a seismocardiogram (SCG) signal is a challenging problem for its clinical usage. Delineation techniques proposed in the existing literature do not estimate all the clinically significant points of an SCG signal, simultaneously. The aim of this research work is to propose a delineation framework to identify I...
Preprint
Full-text available
In this work, a seismocardiogram (SCG) based breathing-state measuring method is proposed for m-health applications. The aim of the proposed framework is to assess human respiratory system by identifying degree-of-breathings, such as breathlessness, normal breathing, and long and labored breathing. For this, it is needed to measure cardiac-induced...
Conference Paper
Brain state classification using electroencephalography (EEG) finds applications in both clinical and non-clinical contexts, such as detecting sleep states or perceiving illusory effects during multisensory McGurk paradigm, respectively. Existing literature considers recordings of EEG electrodes that cover the entire head. However, for real world a...
Article
This paper presents a new method to extract the envelope of the fundamental heart sound (S1 and S2) using the logistic function. The sigmoid characteristic of the logistic function is incorporated to segregate S1, and S2 signal intensities from silent or noise interfered systolic and diastolic intervals in a heart sound cycle. This signal intensity...
Data
https://jbhi.embs.org/2019/05/06/sensor-informatics-may-2019/
Article
Full-text available
A framework to detect aortic valve opening (AO) phase with the help of seismocardiogram (SCG) signal is proposed. A small electronic circuit board is designed, which consists of 3-D MEMS based accelerometer, pre-amplifier, and filter. It is interfaced with standard data acquisition system to record SCG signals. The signal is decomposed using a prop...
Conference Paper
Full-text available
In this paper, an analysis of thoracic vibrations induced by cardiac activities is presented under two different breathing levels. These levels are associated to respiratory efforts in normal and stopped manner. Usually, the vibrations on the thoracic cavity are captured by the means of seismocardiogram (SCG) signal. Some morphological features are...
Article
Early diagnosis and prediction of heart diseases are essential to reduce the cardiac risks. Change in heart cycle morphologies is a vital diagnostic feature for cardiac clinical systems. A seismocardiogram (SCG) signal provides more detailed information of different cardiac phases in a heart cycle compared to othercardiac signals. Hence, heart cycl...
Article
This paper presents a multi-centroid diastolic duration model for the hidden semi-Markov model (HSMM) based heart sound segmentation. The centroids are calculated by hierarchical agglomerative clustering of the neighboring diastolic duration values using Ward’s method until center of clusters are found at least a systolic duration apart. The multip...
Conference Paper
Full-text available
In this paper, we propose a spectracentrogram model for time-frequency analysis of major signal-power concentration. The proposed model is derived from a traditional time-frequency representation (TFR) scheme, spectrogram. The algorithm consists of two major operations: performing short time Fourier transform (STFT) for spectrogram, and computation...
Conference Paper
In this paper, a unified denoising framework is proposed to suppress the noises and artifacts from a seismocardiogram (SCG) signal. The proposed method consists of a unique set of two Kalman filter models in a cascaded fashion. Each of the Kalman filters is modelled separately to serve two different purposes. First stage Kalman filter (KF1) is mode...
Conference Paper
In this paper, we have proposed a new morphological feature to improve the detection of S1 and S2 sounds from noisy or pathological phonocardiogram (PCG) signals. This feature is based on logistic function amplitude moderator (LFAM) and Teager-Kaiser energy operator (TKEO). The LFAM is used to enhance the intensity of weak heart sounds so that the...
Patent
This invention is a disclosure of an automated method for Jigsaw Puzzle reconstruction. The problem of Jigsaw puzzle reconstruction is extensively analyzed and we proposed a novel algorithm for solving this problem. In our method, we restrained ourselves to use only the texture information. Colour information is totally ignored for puzzle reconstru...
Article
Full-text available
Accurate detection of fiducial points in a seismocardiogram (SCG) is a challenging research problem for its clinical application. In this paper, an automated method for detecting aortic valve opening (AO) instants using the dorsoventral component of SCG signal is proposed. This method does not require electrocardiogram (ECG) as a reference signal....
Conference Paper
Full-text available
In this paper, a variational mode decomposition (VMD) based heartbeat extraction framework is proposed for seismocardiogram (SCG) signal. A reference cardiac signal such as ECG is not needed in our proposed method. The proposed method consists of four major steps: signal decomposition using VMD algorithm, heart rate (HR) envelope construction, low...
Patent
This invention is related to a method and technology that can produce human speech signal from 3-dimensional glottal vibration signals. Due to vibration of vocal folds during phonation, there is acceleration of the intrinsic laryngeal muscles in the 3-dimesional space. The acceleration interrelating to the vibration signals are non-invasively acqui...
Article
Full-text available
The phonocardiogram (PCG) signal indicates closing instants of atrio-ventricular and semilunar valves, and this information can also be extracted from two major profiles of a seismocardiographic (SCG) cycle. This letter presents a method to extract fundamental heart sounds (HSs) from a SCG signal. The proposed method employs discrete wavelet transf...
Conference Paper
The wavelet transform based decomposition of heart sound signal segments its clinical components at different wavelet scales. Thus the energy of the first and second heart sounds (S1 and S2) appears at different scales. In this paper, multiscale squared energy envelope is computed at different wavelet scales to locate boundaries of heart sounds. Th...
Patent
This invention is a disclosure of three dimensional recording technology of glottal folds vibration using 3-axis MEMS based accelerometer or any other device in a non-invasive manner. The invented technology is named as “Three Dimensional Seismoglottogram (3-D SEISMOGLOTTOGRAM)” or “3-D SGG”. In addition to this, the invention is integrated with sp...
Conference Paper
In this paper an automatic heart sound segmentation scheme is proposed using Teager-Kaiser energy operator (TKEO) in Hilbert space. After pre-processing the heart sound signal, Hilbert envelope is computed and filtering is performed to obtain smooth envelope. TKEO is applied to this envelope signal to find more accurate boundaries of heart sounds....
Article
In recent years, compressed sensing (CS) has emerged as a potential alternative to traditional data compression techniques for resource-constrained telemonitoring applications. In the present work, a CS framework of data reduction is proposed for multi-channel electrocardiogram (MECG) signals in eigenspace. The sparsity of dimension-reduced eigensp...
Article
Full-text available
In this letter, a novel principal component (PC) based diagnostic measure (PCDM) is proposed to quantify loss of clinical components in the multilead electrocardiogram (MECG) signals. The analysis of MECG shows that, the clinical components are captured in few PCs. The proposed diagnostic measure is defined as the sum of weighted percentage root me...
Article
Full-text available
Ventricular tachycardia (VT) and ventricular fibrillation (VF) are shockable ventricular cardiac ailments. Detection of VT/VF is one of the important step in both automated external defibrillator (AED) and implantable cardioverter defibrillator (ICD) therapy. In this paper, we propose a new method for detection and classification of shockable ventr...
Article
Background and objective: In this paper an information theory based multiscale singular value decomposition (SVD) is proposed for multilead electrocardiogram (ECG) signal processing. The shrinkage of singular values for different multivariate multiscale matrices at wavelet scales is based on information content. It aims to capture and preserve the...
Chapter
In this work, multiscale covariance analysis is proposed for multilead electrocardiogram signals to detect myocardial infarction (MI). Due to multiresolution decomposition, diagnostically important clinical components are grossly segmented at different scales. If multiscale multivariate matrices are formed using all ECG leads and subjected to covar...
Conference Paper
In this paper a heart sound segmentation algorithm in multiresolution domain is proposed. Wavelet decomposition of heart sound signal grossly segments its components into different subbands. If multiscale Hilbert envelope is computed on reconstructed signals at different scales, it provides suitable markers for first and second heart sound boundari...
Conference Paper
Accurate detection of life-threatening cardiac ailments is one of the important task in monitoring patient’s health. In this paper, a new method for detection and classification of cardiac ailments from multilead electrocardiogram (MECG) is presented. The singular value decomposition (SVD) is used to convert the MECG data matrix into two unitary ma...
Conference Paper
In this work, multiscale covariance analysis is proposed for multi-lead electrocardiogram signals to detect myocardial infarction (MI). Due to multiresolution decomposition, diagnostically important clinical components are grossly segmented at different scales. If multiscale multivariate matrices are formed using all ECG leads and subjected to cova...
Article
Electrocardiogram (ECG) contains the information about the contraction and relaxation of heart chambers. This diagnostic information will change due to various cardiovascular diseases. This information is used by a cardiologist for accurate detection of various life-threatening cardiac disorders. ECG signals are subjected to number of processing, f...
Article
In this paper, multilead electrocardiogram (MECG) data compression using singular value decomposition in multiresolution domain is proposed. It ensures a high compression ratio by exploiting both intra-beat and inter-lead correlations. A new thresholding technique based on multiscale root fractional energy contribution is proposed. It selects the s...
Article
Full-text available
In this paper, a novel technique on multiscale energy and eigenspace (MEES) approach is proposed for detection and localization of myocardial infarction from multilead electrocardiogram (ECG). Wavelet decomposition of multilead ECG signals grossly segments the clinical components at different subbands. In myocardial infarction, pathological charact...
Conference Paper
In this paper, denoising of multilead electrocardiograms (ECG) using multiscale singular value decomposition is proposed. If signal of each ECG leads are wavelet transformed with same mother wavelet and decomposition levels, it helps formation of multivariate multiscale matrices at wavelet scales. Singular value decomposition is applies in these sc...
Article
Full-text available
A new measure for quantifying diagnostic information from a multilead electrocardiogram (MECG) is proposed. This diagnostic measure is based on principal component (PC) multivariate multiscale sample entropy (PMMSE). The PC analysis is used to reduce the dimension of the MECG data matrix. The multivariate multiscale sample entropy is evaluated over...
Article
Compressed sensing recovers a sparse signal from a small set of linear, nonadaptive measurements. A sparse signal can be represented by compressed measurements with a reduced number of projections on a set of random vectors. In this paper, a multiscale compressed sensing based processing is investigated for an electrocardiogram signal which yields...
Conference Paper
Electrical activity of the heart recorded by a 12-lead Electrocardiogram is important in detecting cardiac abnormalities. The 12-leads can be seen as the components of heart vector which originates from the center of the heart. These components spread over the frontal and transverse plane and have information about various parts of the heart. Incre...
Conference Paper
Classically, signal information is believed to be retrieved, if it is sampled at Nyquist rate. Since last decade compressive sensing is evolving which shows the signal reconstruction ability from insufficient data points. It reconstructs the signal from a set of reduced number of sparse samples that is lesser than Nyquist rate. It is required that...
Conference Paper
Compressive sensing is well known for its robust signal reconstruction ability from a smaller set of samples than required according to Nyquist criterion. In this paper compressive sensing (CS) has been proposed in eigenspace for Multichannel Electrocardiogram (MECG) signals. Principal component analysis (PCA) is used to give eigenspace signals. PC...
Article
Conventionally it is believed that the successful reconstruction of a signal is possible if it is sampled at Nyquist rate. Compressed sensing method shows reconstruction ability from the insufficient data point. It reconstructs the signal from a set of reduced number of sparse samples. In wavelet domain, multi-lead electrocardiogram signals show sp...
Conference Paper
Compressed sensing is widely used due to its ability to reconstruct the signal accurately from a set of samples which is smaller than the set of samples produced using Nyquist rate. Multi-lead electrocardiogram signals show sparseness in wavelet domain. In this work, compressive sensing is applied for electrocardiogram signals in transform domain u...
Conference Paper
— In this work, an information theoretic approach is proposed for principal component analysis (PCA) of multi-lead electrocardiogram signals. Clinical information is evaluated from the inverse of the diagonal eigenvalue matrix. It is termed as Clinical Entropy (Centropy). Clinical entropy (Centropy) based PCA method shows improved performance compa...
Article
In this paper, multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression. In wavelet domain, principal components analysis (PCA) of multiscale multivariate matrices of multichannel signals helps reduce dimension and remove redundant information present in signals. The selection of princip...
Article
This work describes the development of an Assamese handwritten numeral recognizer. Online handwritten numeral recognition system is developed using x, y coordinates as the feature and Hidden Markov Model (HMM) as the modelling technique. Offline handwritten numeral recognition system is developed using vertical projection profile and horizontal pro...
Article
In this article, it is suggested to apply Multiscale PCA to multichannel ECG signals, for quality controlled denoising. PCA is applied at wavelet scales after forming multivariate data matrices. The quality controlled denoising is a two steps process, (a) selection of multivariate matrices at wavelet scale for PCA based dimension reduction and (b)...
Article
In this work, a novel wavelet-based denoising method for electrocardiogram signal is proposed. A threshold is derived by considering energy contribution of a wavelet subband, noise variance which is based on a novel Gaussian measure, Kurtosis, and number of samples. The robust noise estimator, median absolute deviation, is scaled by a normalized wa...
Article
In this work, multiscale principal component analysis (MSPCA) is introduced for denoising of multichannel electrocardiogram (MECG) signals. Wavelet decomposition of MECG signals segments the clinical information content at different Wavelet subbands or scales. At subband levels or scales multivariate data matrix are formed using Wavelet coefficient...
Article
In this work, multiscale principal component analysis (MSPCA) is applied to multichannel ECG signals. Multiresolution analysis of multichannel ECG data using L level Wavelet decomposition gives L + 1 subbands. Considering jth subbands of all the channels of a standard 12 lead ECG signals, subband matrices are formed at multiscale levels. At Wavelet...
Article
In this work, a novel denoising algorithm based on relative energies of Wavelet subbands and estimated noise variance is proposed for Electrocardiogram (ECG) signal. The proposed algorithm is based on Relative Energy Denoising (RED) factor which is a function of Energy Contribution Efficiency (ECE), Details Energy Contribution Efficiency (DECK) and...
Article
In this work, we propose a novel denoising method based on evaluation of higher-order statistics at different Wavelet bands for an electrocardiogram (ECG) signal. Higher-order statistics at different Wavelet bands provides significant information about the statistical nature of the data in time and frequency. The fourth order cumulant, Kurtosis, an...
Article
Multichannel electrocardiogram (MECG) signal de-noising can be described as a process of removing the clinically unimportant contents present from the signal. Higher order statistics (HOS) can help to retain finer details of an electrocardiogram (ECG) signal which can effectively reduce the noise levels in MECG signal. In this work, it is proposed...
Article
In order to realize an Internet based on-line laboratory, where actual experiments are performed remotely, the bandwidth of the network plays a very crucial role. In a low bit rate link streaming video is not possible. This work focuses a practical remote laboratory module for low bit rate link. The work has been tested from quite a few CIC (Commun...
Article
Full-text available
In technical education, laboratory components comprise an essential and integral part without which engineering education remains incomplete. Experiments conducted on laboratory equipments lend a practical touch to the theoretical knowledge acquired by the students. However, setting up a specialized laboratory consisting of sophisticated and expens...
Conference Paper
In recent past researchers have given much attention on the miniature compact antenna on PCB Substrate. To meet the antenna requirement in portable communication equipment variety of microstrip patch antenna structures with different PCB substrate materials have been suggested. In this work, a triangular microstrip patch antenna on FR4 material wit...

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