S. Dandapat

S. Dandapat
Indian Institute of Technology Guwahati | IIT Guwahati · Department of Electronics and Electrical Engineering (EEE)

About

119
Publications
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1,974
Citations
Citations since 2017
22 Research Items
1241 Citations
2017201820192020202120222023050100150200250
2017201820192020202120222023050100150200250
2017201820192020202120222023050100150200250
2017201820192020202120222023050100150200250

Publications

Publications (119)
Conference Paper
In this work, spectrum of vowels /a/ and /i/ belonging to normal, mild and moderate-severe hypernasal cleft palate (CP) speech are analyzed to find the nature of magnitude of dominant harmonics and their frequencies in these three levels of hypernasality severity. The coupling of nasal tract with the oral tract during the production of hypernasal v...
Article
Hypernasality in the speech of children with cleft palate is a consequence of velopharyngeal insufficiency. The spectral analysis of hypernasal speech shows the presence of nasal formants and anti-formants in the spectrum which affects the harmonic-intensity. The nasal formants increases whereas the anti-formants decrease the magnitude of harmonics...
Conference Paper
Hypernasality is a speech disorder in cleft palate (CP) children. Hypernasality detection is done by analyzing the vowels present in the speech stimuli. The presence of nasal peak in the vicinity of first formant F 1 is an important acoustic cue for the hyper- nasality detection. Generally, a two-step process is followed for hypernasality detection...
Article
The presence of hypernasality in repaired cleft palate (CP) speech is a consequence of velopharyngeal insufficiency. The coupling of the nasal tract with the oral tract adds nasal formant and antiformant pairs in the hypernasal speech spectrum. This addition deviates the spectral and linear prediction (LP) residual characteristics of hypernasal spe...
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...
Conference Paper
Full-text available
Cleft lip and palate (CLP) is a congenital disorder of the orofacial region. Nasal air emission (NAE) in CLP speech occurs due to the presence of velopharyngeal dysfunction (VPD), and it mostly occurs in the production of fricative sounds. The objective of present work is to study the acoustic characteristics of voiceless sibilant fricatives in Kan...
Article
Full-text available
Assessment of intelligibility is required to characterize the overall speech production capability and to measure the speech outcome of different interventions for individuals with cleft lip and palate (CLP). Researchers have found that articulation error and hypernasality have a significant effect on the degradation of CLP speech intelligibility....
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...
Article
Intelligibility is considered as one of the primary measures for speech rehabilitation of individuals with a cleft lip and palate (CLP). Currently, speech processing and machine-learning-based objective methods are gaining more research interest as a way to quantify speech intelligibility. In this work, joint spectro-temporal features computed from...
Article
The present work explores the acoustic characteristics of articulatory deviations near g(lottis) landmarks to derive the correlates of cleft lip and palate speech intelligibility. The speech region around the g landmark is used to compute two different acoustic features, namely two-dimensional discrete cosine transform based joint spectro-temporal...
Conference Paper
Speech intelligibility is considered as the primary measure to evaluate the speech outcome of therapy and other rehabilitation for cleft lip and palate (CLP) individuals. It has been found that the CLP speech intelligibility primarily degrades due to several speech disorders, such as hypernasality, consonants production errors, and voice disorders....
Conference Paper
Full-text available
This work presents a comparison based framework by exploiting the self-similarity matrices matching technique to estimate the speech intelligibility of cleft lip and palate (CLP) children. Self-similarity matrix (SSM) of a feature sequence is a square matrix, which encodes the acoustic-phonetic composition of the underlying speech signal. Deviation...
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...
Article
This study proposes a method for differentiating hypernasal-speech from normal speech using the vowel space area (VSA). Hypernasality introduces extra formant and anti-formant pairs in vowel spectrum, which results in shifting of formants. This shifting affects the size of the VSA. The results show that VSA is reduced in hypernasal-speech compared...
Article
Detection of microvolt T-wave alternans (TWA) and finding its clinical significance remains a challenging task. In this work, we propose a new TWA detection method based on multiscale analysis-by-synthesis followed by higher-order singular value decomposition (MASHOSVD). The multilead ECG (MECG) data, after R-peak detection, was represented as a th...
Article
Full-text available
Myocardial infarction is a coronary artery ailment, and it is characterized by the changes in the morphological features such as the shape of T-wave, Q-wave and ST-segment of ECG signal. In clinical standard, it is a challenging problem to diagnose MI pathology using 12-lead ECG and vectorcardiogram (VCG). VCG has the advantage to record the heart...
Article
Cardiac arrhythmias, with each passing day, are becoming highly prevalent in modern society. The ever increasing number of patients added to the sheer amount of data that is recorded from a patient during monitoring limits the ability of a medical practitioner to diagnose these problems quickly. Therefore, an intelligent system is required which ca...
Article
This paper presents a new method of feature extraction using Fourier model for analysis of out-of-breath speech. The proposed feature is evaluated using mutual information (MI) on the difference and ratio values of the Fourier parameters, amplitude and frequency. The difference and ratio are calculated between two contiguous values of the Fourier p...
Article
Full-text available
In this paper, a novel subspace projection approach is proposed for analysis of speech signal under stressed condition. The subspace projection method is based on the assumption of orthogonality between speech subspace and stress subspace. Speech and stress subspaces contain speech and stress information, respectively. The projection of stressed sp...
Conference Paper
This work analyses the hypernasal cleft palate speech for 4-point severity rating (0-normal, 1-mild, 2-moderate, 3-severe). Hypernasality results nasalization of vowels and some of voiced consonants. Addition of extra nasal peak in vicinity of first formant occurs due to nasalization. To resolve the closely spaced extra nasal peak and first formant...
Article
This paper explores the analysis and classification of speech under stress using a new feature, harmonic peak to energy ratio (HPER). The HPER feature is computed from the Fourier spectra of speech signal. The harmonic amplitudes are closely related to breathiness levels of speech. These breathiness levels may be different for different stress cond...
Article
Computational complexity and power consumption are prominent issues in wireless telemonitoring applications involving physiological signals. Compressed sensing (CS) has emerged as a promising framework to address these challenges because of its energy-efficient data reduction procedure. In this work, a CS-based approach is studied for joint compres...
Article
Full-text available
The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features durin...
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
Computational complexity and power consumption are prominent issues in wireless telemonitoring applications involving physiological signals. Because of its energy-efficient data reduction procedure, compressed sensing (CS) emerged as a promising framework to address these challenges. In this work, a multi-channel CS framework is explored for multi-...
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...
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
Multichannel elctrocardiogram (MECG) signals are correlated both in spatial domain as well as in temporal domain and this correlation is stronger at multiscale levels (Fig. 1). To exploit this correlation in compressed sensing (CS) based ECG tele-monitoring systems, a joint multiscale compressed sensing (JMCS) technique is proposed in this work. CS...
Conference Paper
Full-text available
In this paper, a novel technique is proposed for detecting cardiac arrhythmias using signals obtained from a multi-lead electrocardiogram (ECG). The method employs the use of two non-linear features namely detrended fluctuation analysis and sample entropy. The features are calculated on signals obtained after performing discrete wavelet transform o...
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...
Conference Paper
This paper presents synthesis of 12-lead Electrocardiogram (ECG) from a reduced set of leads. A patient-specific 12-lead ECG is trained using the Singular Value Decomposition (SVD) for minimum of three beat periods. Then, in the testing stage, different reduced lead sets comprising of three leads are used to reconstruct all other leads. The singula...
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
Full-text available
In this Letter, a robust third-order tensor decomposition of multi-lead electrocardiogram (MECG) comprising of 12-leads is proposed to reduce the dimension of the storage data. An order-3 tensor structure is employed to represent the MECG data by rearranging the MECG information in three dimensions. The three-dimensions of the formed tensor represe...
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
In this paper, a novel distortion measure is presented for quantifying loss of clinical information in multichannel electrocardiogram (MECG) signals. The proposed measure (SCPRD) is defined as the sum of percentage root mean square difference between magnitudes of convolution response of original and processed MECG signals. The convolution operatio...
Article
Electrocardiogram signals acquired through different channels from the body surface are termed as Multichannel ECG (MECG) signals. They are obtained by projecting the same heart potential in different directions and hence share common information with each other. In this work a new two-dimensional (2-D) approach is proposed for MECG signal processi...
Conference Paper
Multichannel elctrocardiogram (MECG) signals are correlated both in spatial domain as well as in temporal domain and this correlation becomes even higher at multiscale levels. This work presents a MECG compression method in order to exploit the inherent inter-channel correlation more efficiently, using a multiscale compressive sensing (MSCS) based...
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...
Article
Diabetes has become a life threatening disease. The effect of diabetes on human retina is called Diabetic Retinopathy (DR). If DR involves macula, it is known as maculopathy. Under this condition, the visibility of the patient gets affected adversely. In this paper, we have proposed a method for grading the stages of maculopathy. In the first stage...
Conference Paper
Compressive sensing (CS) is well known for its robust sparse signal reconstruction ability from a smaller set of linear projections taken over an incoherent basis. For mutually correlated signals, a variant of CS called distributed compressive sensing (DCS) is employed. In this work, DCS is proposed to exploit the underlying correlation structure b...
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
Cardiovascular disease (CVD) is one of the most widespread health problems with unpredictable and life-threatening consequences. The electrocardiogram (ECG) is commonly recorded for computer-aided CVD diagnosis, human emotion recognition and person authentication systems. For effective detection and diagnosis of cardiac diseases, the ECG signals ar...
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...
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
This paper proposes a novel subspace projection based approach for analysis of stressed speech signal. The projection of stressed speech vectors onto the neutral speech subspace can separate speech specific information from stress information. Orthogonality between speech and stress is assumed to separate these two information. The orthogonal relat...
Conference Paper
Diabetic retinopathy causes blindness due to the physiological changes in the retina of human eye, which occurs due to the progression of diabetes. Diabetic retinopathy images differ from normal fundus images by lesions such as: microaneurysm, hemorrhages, exudates, cotton wool spots and variations in blood vessels etc. Appearance of these features...
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...
Conference Paper
Condition of the retina can be known from the color fundus image. Appearance and location of different features such as exudates, hemorrhages and drusen in color fundus image are used for the assessment of diabetic retinopathy (DR). DR affects the structure of blood vessels and optic disc (OD). In this paper we propose a novel method for detecting...
Article
In this paper, we present a quality driven PCG signal coding scheme for wireless cardiac patient monitoring applications. The proposed quality driven codec is designed based on the wavelet-based compression method and the wavelet energy based diagnostic distortion (WEDD) measurement criterion. The proposed WEDD measure is the weighted percentage ro...
Article
In this study, spectral slope based features are investigated for characterization and classification of stressed speech. The vocal tract spectrum is modulated with glottal flow spectra, resulting a tilt in the overall spectrum. In this study, spectral tilt is analyzed for different stress classes. Relative formant peak displacement (RFD) is propos...
Conference Paper
This study analyzes the effect of stress in human and automatic stressed speech processing tasks for speech collected from non-professional speakers. The database of 33 keywords is collected under five stress conditions, namely, neutral, angry, happy, sad and Lombard from fifteen speakers. The first study is to understand the ability to identify st...
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
Full-text available
Evaluating the quality of processed retinal images is an important issue in applications such as telemedicine. The traditional image quality measures are having limitation in emphasizing the loss of clinically significant information. We previously proposed a wavelet weighted blood vessel distortion measure (WBVDM) for retinal images. The WBVDM giv...
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
Full-text available
In this paper, a novel wavelet transform based blood vessel distortion measure (WBVDM) is proposed to assess the image quality of blood vessels in the processed retinal images. The wavelet analysis of retinal image shows that different wavelet subbands carry different information about the blood vessels. The WBVDM is defined as the sum of wavelet w...
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
Full-text available
This paper presents the feature analysis and design of compensators for speaker recognition under stressed speech conditions. Any condition that causes a speaker to vary his or her speech production from normal or neutral condition is called stressed speech condition. Stressed speech is induced by emotion, high workload, sleep deprivation, frustrat...
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
Full-text available
The analysis of diagnostic features such as the optic disc(OD) provides important clues for the diagnosis of various retinopathic diseases. In this paper, a wavelet based distortion measure for the optic disc (WODDM) in retinal image is proposed. The wavelet analysis shows that different subbands carry optic disc information to a different level. T...
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
Full-text available
The variations in speech production due to stress have an adverse affect on the performances of speech and speaker recognition algorithms. In this work, different speech features, such as Sinusoidal Frequency Features (SFF), Sinusoidal Amplitude Features (SAF), Cepstral Coefficients (CC) and Mel Frequency Cepstral Coefficients (MFCC), are evaluated...
Conference Paper
Noise degrades the rate-distortion performance of any electrocardiogram (ECG) compression algorithm. In distortion driven lossy coding approach, the bit stream is truncated at the bit rate that corresponds to a guaranteed user defined distortion level measured using the percentage root mean square difference (PRD). In many lossy compression methods...
Article
An effective quality-controlled set partitioning in hierarchical trees (SPIHT)-based ECG coding strategy under noise environments is proposed using a wavelet-energy based weighted percentage root mean square difference (WEWPRD<sub>s</sub>) criterion. This criterion is subjectively meaningful and leads to a better measure of rate-distortion (R-D) pe...
Article
In this letter, a novel objective distortion measure is proposed for compressed electrocardiogram (ECG) signals. The measure is a weighted percentage root-mean-square difference (WPRD) between the subband coefficients of the original and compressed signals with weights equal to the multiscale entropies of the corresponding subbands. The measure app...
Article
In this paper, two novel and simple, target distortion level (TDL) and target data rate (TDR), Wavelet threshold based ECG compression algorithms are proposed for real-time applications. The issues on the use of objective error measures, such as percentage root mean square difference (PRD) and root mean square error (RMSE) as a quality measures, in...
Conference Paper
This paper presents a novel phonocardiogram (PCG) signal compression method based on Wavelet transform. The proposed compression method uses energy based thresholding for retaining significant coefficients, uniform scalar zero zone quantizer (USZZQ) for quantizing the amplitudes of the significant coefficients and differencing coder for integer sig...
Conference Paper
Full-text available
This paper presents a simple method to assess the quality of compressed retinal images. It is based on the idea that the retinal image should possess some common features which helps to define the quality of the image. Retinal blood vessels are important diagnostic features in ophthalmological images. Changes in retinal vessel structure helps in de...
Conference Paper
One of the emerging issues in telehealth care system is how effectively the limited and well established mobile technologies that are now almost globally usable are exploited. The main challenge is to develop a mobile telemedicine system to transmit biosignals directly to a specialist in an emergency medical care unit for monitoring/diagnosis using...
Conference Paper
A novel and simple quality controlled ECG compression algorithm is proposed using Wavelet energy based diagnostic distortion (WEDD) measure, which localizes the error between the original and the reconstructed signals in the feature space. The compression algorithm is based on Wavelet transform, energy based thresholding and an adaptive quantizatio...
Article
Measurement of quality is of fundamental importance to electrocardiogram (ECG) signal processing applications. A number of distortion measures are used for ECG signal quality assessment. A simple and widely used distortion measure is the percentage root mean square difference (PRD). It is an attractive measure due to its simplicity and mathematical...
Article
Full-text available
Different types of speech features are used for speaker identification. Speeeh features sueh as Mel'frequency cepstral coefficients (MFGG), Jog area ratios (LAW, arcsin reflection coefficients (ARC), cepstralcoefficients (CO) and reflection coefficients (RE)are shown to produce promising results for speaker identification, The results produced are...
Article
In this paper, a novel Wavelet Energy based diagnostic distortion (WEDD) measure is proposed to assess the reconstructed signal quality for ECG compression algorithms. WEDD is evaluated from the Wavelet coefficients of the original and the reconstructed ECG signals. For each ECG segment, a Wavelet energy weight vector is computed via five-level bio...
Conference Paper
A new novel wavelet-threshold based ECG signal compression method is proposed using linear phase biorthogonal 9/7 discrete wavelet transform, uniform scalar zero zone quantizer (USZZQ) and Huffman coding of the difference between two consecutive index of the significant coefficients. The compression performance of the proposed method is better comp...
Conference Paper
Diabetic retinopathy is one of the major cause of blindness among the people. Many approaches are proposed by the authors to automate and detect the presence of diabetic retinopathy in fundus image. We propose a novel method of detection of the diabetic retinopathy using Gaussian intensity feature input to a VQ classifier. The underlying idea of us...
Conference Paper
In this work, we propose a constrained autoregressive (CAR) model based Burg method for parametric spectral estimation. CAR Burg method is based on constraining the Mth reflection coefficient of an M-order AR model. The value of this constrained reflection coefficient can be used for controlling the frequency bias and improving the spectral resolut...
Conference Paper
Emotional speech plays an important role for conveying the desired message. Emotions are manifested in speech signal at all the levels, in particular they are significant at suprasegmental level (i.e., prosodic level). In this paper four emotions are characterized (anger, compassion, happy and neutral) using the prosodic features such as duration,...
Article
In this paper, a new Wavelet threshold based ECG signal compression technique using uniform scalar zero zone quantizer (USZZQ) and Huffman coding on differencing significance map (DSM) is proposed. Wavelet coefficients are selected based on the energy packing efficiency of each sub-band. Significant Wavelet coefficients are quantized with uniform s...

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