Reza Sameni

Reza Sameni
Emory University | EU · Department of Biomedical Informatics

PhD, SMIEEE

About

115
Publications
43,680
Reads
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3,062
Citations
Additional affiliations
July 2020 - April 2021
Emory University
Position
  • -
September 2018 - July 2020
Grenoble Institute of Technology
Position
  • Researcher
September 2008 - August 2018
Shiraz University
Position
  • Faculty Member

Publications

Publications (115)
Article
Full-text available
Chest sound— as the first and most commonly available vital signal for newborns— contains affluent information about their cardiac and respiratory health. However, neonatal lung sound auscultation is currently challenging and often unreliable due to the noise and interference, particularly for preterm infants. The noise often overlaps with the hear...
Preprint
Full-text available
Stethoscope-recorded chest sounds provide the opportunity for remote cardio-respiratory health monitoring of neonates. However, reliable monitoring requires high-quality heart and lung sounds. This paper presents novel Non-negative Matrix Factorisation (NMF) and Non-negative Matrix Co-Factorisation (NMCF) methods for neonatal chest sound separation...
Article
In this study, a new method is proposed to assess heart and lung signal quality objectively and automatically on a 5-level scale in real-time, and to assess the effect of signal quality on vital sign estimation. A total of 207 10 s long chest sounds were taken from 119 preterm and full-term babies. Thirty of the recordings from ten subjects were ob...
Preprint
Full-text available
Objective: To determine if a realistic, but computationally efficient model of the electrocardiogram can be used to pre-train a deep neural network (DNN) with a wide range of morphologies and abnormalities specific to a given condition - T-wave Alternans (TWA) as a result of Post-Traumatic Stress Disorder, or PTSD - and significantly boost performa...
Preprint
The fetal electrocardiogram (fECG) was first recorded from the maternal abdominal surface in the early 1900s. During the past fifty years, the most advanced electronics technologies and signal processing algorithms have been used to convert noninvasive fetal electrocardiography into a reliable technology for fetal cardiac monitoring. In this chapte...
Article
Full-text available
Cardiac auscultation is one of the most cost effective techniques used to detect and identify many heart conditions. Computer-assisted decision systems based on auscultation can support physicians in their decisions. Unfortunately, the application of such systems in clinical trials is still minimal since most of them only aim to detect the presence...
Article
Full-text available
Background Atrial fibrillation (AFib) is the most common cardiac arrhythmia associated with stroke, blood clots, heart failure, coronary artery disease, and/or death. Multiple methods have been proposed for AFib detection, with varying performances, but no single approach appears to be optimal. We hypothesized that each state-of-the-art algorithm i...
Preprint
div>Objective: Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation performed by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, depending on the selected data-model, the adopted estimation scheme (least-squares...
Conference Paper
Deep learning methods, and in particular Convolutional Neural Networks (CNNs), have shown breakthrough performance in a wide variety of classification applications, including electroencephalogram-based Brain Computer Interfaces (BCIs). Despite the advances in the field, BCIs are still far from the subject-independent decoding of brain activities, p...
Conference Paper
Common Spatial Pattern (CSP) is a popular feature extraction algorithm used for electroencephalogram (EEG) data classification in brain-computer interfaces. One of the critical operations used in CSP is taking the average of trial covariance matrices for each class. In this regard, the arithmetic mean, which minimizes the sum of squared Euclidean d...
Preprint
Full-text available
Digital stethoscopes in combination with telehealth allow chest sounds to be easily collected and transmitted for remote monitoring and diagnosis. Chest sounds contain important information about a newborn's cardio-respiratory health. However, low-quality recordings complicate the remote monitoring and diagnosis. In this study, a new method is prop...
Preprint
div>Objective: Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation performed by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, depending on the selected data-model, the adopted estimation scheme (least-squares...
Preprint
Full-text available
Objective: Mixtures of temporally nonstationary signals are very common in biomedical applications. The nonstationarity of the source signals can be used as a discriminative property for signal separation. Herein, a semi-blind source separation algorithm is proposed for the extraction of temporally nonstationary components from linear multichannel...
Preprint
div>Objective: Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation performed by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, depending on the selected data-model, the adopted estimation scheme (least-squares...
Preprint
div>Objective: Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation performed by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, depending on the selected data-model, the adopted estimation scheme (least-squares...
Preprint
Cardiac auscultation is one of the most cost-effective techniques used to detect and identify many heart conditions. Computer-assisted decision systems based on auscultation can support physicians in their decisions. Unfortunately, the application of such systems in clinical trials is still minimal since most of them only aim to detect the presence...
Preprint
Full-text available
The electro-phono-cardiogram (EPHNOGRAM) project focused on the development of low-cost and low-power devices for recording simultaneous electrocardiogram (ECG) and phonocardiogram (PCG) data, with auxiliary channels for capturing environmental audio noise, which could be used for PCG quality enhancement through signal processing. The current datab...
Preprint
Nowadays, shallow and deep Neural Networks (NNs) have vast applications including biomedical engineering, image processing, computer vision, and speech recognition. Many researchers have developed hardware accelerators including field-programmable gate arrays (FPGAs) for implementing high-performance and energy efficient NNs. Apparently, the hardwa...
Preprint
Full-text available
The extraction of nonstationary signals from blind and semi-blind multivariate observations is a recurrent problem. Numerous algorithms have been developed for this problem, which are based on the exact or approximate joint diagonalization of second or higher order cumulant matrices/tensors of multichannel data. While a great body of research has b...
Preprint
The models and algorithms developed by the Alphanumerics Team during the XPRIZE Pandemic Response Challenge are presented. The algorithms are based on profound theories from \textit{optimal state estimation} and \textit{finite horizon optimal control}. The major contribution of the team is to develop a predictor and prescriptor over an \textit{ad h...
Article
Full-text available
Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a gr...
Preprint
Full-text available
Assessing fetal development is usually carried out by techniques such as ultrasound imaging, which is generally unavailable in rural areas due to the high cost, maintenance, skills and training needed to operate the devices effectively. In this work, we propose a low-cost one-dimensional Doppler-based method for estimating gestational age (GA). Dop...
Chapter
The fetal electrocardiogram (fECG) was first recorded from the maternal abdominal surface in the early 1900s. During the past 50 years, the most advanced electronics technologies and signal processing algorithms have been used to convert noninvasive fetal electrocardiography into a reliable technology for fetal cardiac monitoring. In this chapter,...
Article
Fetal phonocardiogram (FPCG) consists in the recording of fetal heart sounds by means of a sensor placed on the mother's abdominal surface. Usually, FPCG includes two major sounds for each fetal cardiac cycle: S1, produced by the sudden closure of mitral and tricuspid valves, and S2 produced by the closure of aortic and pulmonary valves. The aim of...
Preprint
Full-text available
Background The study of cerebral activity during sleep using the electroencephalograph (EEG) is a major research field in neuroscience. Despite the rich literature in this field, the automatic and accurate categorization of wake-sleep stages remains an open problem. New Method A robust model-based Kalman filtering scheme is proposed for tracking t...
Article
Full-text available
In this work, we analytically study the peaking phenomenon in the context of linear discriminant analysis in the multivariate Gaussian model under the assumption of a common known covariance matrix. The focus is finite sample setting where the sample size and observation dimension are comparable. Therefore, in order to study the phenomenon in such...
Preprint
Full-text available
The outbreak of the Coronavirus COVID-19 has taken the lives of several thousands worldwide and locked-out many countries and regions, with yet unpredictable global consequences. In this research we study the epidemic patterns of this virus, from a mathematical modeling perspective. The study is based on endemic extensions of the well-known suscept...
Article
Full-text available
Objective: Mixtures of temporally nonstationary signals are very common in biomedical applications. The nonstationarity of the source signals can be used as a discriminative property for signal separation. Herein, a semi-blind source separation algorithm is proposed for the extraction of temporally nonstationary components from linear multichannel...
Article
Full-text available
Objective: Noninvasive fetal electrocardiography is emerging as a low-cost and high-accuracy technology for fetal cardiac monitoring. Signal processing techniques have been used over the past fifty years in this domain. The current major challenges of this domain, addressed in this study are (1) fetal electrocardiogram (fECG) extraction from few n...
Presentation
Full-text available
R. Sameni, “Digital Systems Design Course Lecture Notes”, School of Electrical & Computer Engineering, Shiraz University, Shiraz, Iran, revision 2018.
Article
Full-text available
During the past decades, a great body of research has been devoted to automatic sleep stage scoring using the electroencephalogram (EEG). However, the results are not yet satisfactory to be used as a standard procedure in clinical studies. In this study, using recent developments in robust EEG phase extraction, a novel set of EEG-based features con...
Article
Full-text available
Objective: The instantaneous phase (IP) and instantaneous frequency (IF) of the electroencephalogram (EEG) are considered as notable complements for the EEG spectrum. The calculation of these parameters commonly includes narrow-band filtering, followed by the calculation of the signal's analytical form. The calculation of the IP and IF is highly s...
Article
Full-text available
Noninvasive extraction of the fetal electrocardiogram (fECG) from multichannel maternal abdomen recordings is an emerging technology used for fetal cardiac monitoring and diagnosis. The strongest interference for the fECG is the maternal ECG (mECG), which is not always removed through conventional methods, including blind source separation, especia...
Article
Full-text available
Background Time-Frequency (TF) analysis has been extensively used for the analysis of non-stationary numeric signals in the past decade. At the same time, recent studies have statistically confirmed the non-stationarity of genomic non-numeric sequences and suggested the use of non-stationary analysis for these sequences. The conventional approach t...
Article
Full-text available
Objective: In this study, a robust method is developed for frequency-specific electroencephalogram (EEG) phase extraction using the analytic representation of the EEG. Based on recent theoretical findings in this area, it is shown that some of the phase variations-previously associated to the brain response-are systematic side-effects of the metho...
Article
Full-text available
In the past few decades, analysis of heart sound signals (i.e. the phonocardiogram or PCG), especially for automated heart sound segmentation and classification, has been widely studied and has been reported to have the potential value to detect pathology accurately in clinical applications. However, comparative analyses of algorithms in the litera...
Article
Fetal motility is a widely accepted indicator of the well-being of a fetus. In previous research, it has be shown that fetal motion (FM) is coherent with fetal heart rate accelerations and an indicator for active/rest cycles of the fetus. The most common approach for FM and fetal heart rate (FHR) assessment is by Doppler ultrasound (DUS). While DUS...
Conference Paper
Full-text available
Time-Frequency (TF) analysis has been extensively used for the analysis of numeric signals in the past decade. In this paper, using the notion of interpretive signal processing (ISP) and by redefining correlation functions for non-numeric sequences, a general class of TF transforms are extended and applied to non-numerical genomic sequences. The te...
Article
Full-text available
In this work, a block-wise extension of Tikhonov regularization is proposed for denoising smooth signals contaminated by wide-band noise. The proposed method is derived from a constrained least squares problem in two forms: 1) a block-wise fixed-lag smoother with smooth inter-block transitions applied in matrix form, and 2) a fixed-interval smoothe...
Article
Full-text available
Non-invasive fetal electrocardiography (NI-FECG) is a promising alternative continuous fetal monitoring method that has the potential to allow morphological analysis of the FECG. However, there are a number of challenges associated with the evaluation of morphological parameters from the NI-FECG, including low signal to noise ratio of the NI-FECG a...
Article
Nonlinear digital filters play an important role in digital signal processing applications. In this brief, a novel architecture is proposed for the hardware implementation of fixed and runtime variable window length one-dimensional median filters. In the proposed architecture, the maximum working clock frequency is almost independent of the median...
Article
Event related potentials (ERP) are time-locked electrical activities of the brain in direct response to a specific sensory, cognitive, or motor stimulus. ERP components, such as the P300 wave, which are involved in the process of decision-making, help scientists diagnose specific cognitive disabilities. New Method: In this study, we utilize the ang...
Patent
Full-text available
A method for processing cardiac signals includes accepting, from a sensor system, a set of one or more signals, the signals including components of a desired cardiac signal and components of a substantially periodic interfering signal. The method is applicable for extraction of desired fetal cardiac signals from signals with interference from the m...
Article
Full-text available
Development of ECG delineation algorithms has been an area of intense research in the field of computational cardiology for the past few decades. However, devising evaluation techniques for scoring and/or merging the results of such algorithms, both in the presence or absence of gold standards, still remains as a challenge. This is mainly due to ex...
Conference Paper
Full-text available
The problem of blind source separation (BSS) and tracking from time-varying mixtures is an open-problem of biomedical signal processing research. In this study we present a framework for decomposing and tracking instantaneous separation matrices of independent component analysis (ICA) solutions of BSS. The decomposition is based on the tracking of...
Article
Full-text available
In this paper a general framework is presented for morphological modeling of cardiac signals from a signal decomposition perspective. General properties of a desired morphological model are presented and special cases of the model are studied in detail. The presented approach is studied for modeling the morphology of electrocardiogram (ECG) signals...
Conference Paper
Full-text available
The PhysioNet/CinC 2013 Challenge aimed to stimulate rapid development and improvement of software for estimating fetal heart rate (FHR), fetal interbeat intervals (FRR), and fetal QT intervals (FQT), from multichannel recordings made using electrodes placed on the mother's abdomen. For the challenge, five data collections from a variety of sources...
Conference Paper
Full-text available
In this paper, a robust framework is presented for fECG extraction from maternal abdomen recordings. The idea is based on extracting the fECG from contaminated signals using a multistage interference and noise cancelation method, designed specifically according to the time, space and frequency characteristics of the fECG and its interferences. The...
Conference Paper
Full-text available
Fetal heart rate variability (FHRV) is one of the valuable features of fetal electrocardiography that could be useful to obtain reliable information about the fetal heart activity. In noninvasive systems, the major obstacle for the accurate detection of the fetal QRS (fQRS) complex is the presence of abdominal noise and the maternal ECG (mECG). In...
Article
The analysis of auditory evoked cortical responses in fetal Magnetoencephalography (fMEG) can be used as an early marker of functional cerebral development. A major obstacle for this objective is the very low signal-to-noise ratio of the fMEG recordings in presence of other biological contaminants (mainly maternal and fetal cardiac activities). Due...
Conference Paper
Full-text available
In this paper a novel method based on Matched Filters is proposed for the analysis of non-numeric sequences. Conventional techniques of non-numeric data analysis consist of assigning numeric values to non-numeric symbols and using numeric techniques for processing the resultant sequences. However, in the proposed technique, using the notion of simi...
Conference Paper
Full-text available
A discrete-time linear Kalman filter is presented for removing power-line interference from biomedical recordings. The theoretical aspects of this filter, the relationship with conventional digital IIR and adaptive IIR notch filters, and its steady state behavior are studied in detail. As compared to previous studies, the filter is linear and does...
Conference Paper
Full-text available
In this paper the cardiac phase is calculated using different methods based on time warping theory. The estimated phase is used for calculation of the heart rate (HR) signal. The results show that the estimated HR is similar to the HR calculated by using the RR-interval sequence. Unlike the RR-interval signal which is non-uniformly sampled, the pro...
Article
The maturation of fetal auditory evoked cortical responses (fAECRs) is an important aspect of developmental medicine, but their reliable identification is limited due to the technical restrictions in prenatal diagnosis. The signal-to-noise ratio of the fAECRs extracted exclusively from fetal magnetoencephalography is a known issue which limits thei...
Article
We sought to evaluate the accuracy of a novel system for measuring fetal heart rate (FHR) and ST-segment changes using noninvasive electrodes on the maternal abdomen. Fetal electrocardiograms were recorded using abdominal sensors from 32 term laboring women who had a fetal scalp electrode (FSE) placed for a clinical indication. Good-quality data fo...
Article
Full-text available
Identification of social relationships in social networks, especially cell phone networks, has attracted a lot of attention recently. Mobile phones continue to be one of the main methods of communication. Their voice and SMS logs are accessible in network switches and/or telecommunication centers. However, relationships like friendship have been mi...
Article
Full-text available
A general deflation framework is described for the separation of a desired signal subspace of arbitrary dimensions from noisy multichannel observations. The method simultaneously uses single and multichannel priors to split the desired and undesired subspaces, even for coplanar (intersecting) subspaces. By appropriate use of signal priors, it can e...
Article
Full-text available
We present generalizations of our previously published artificial models for generating multi-channel ECG to provide simulations of abnormal cardiac rhythms. Using a three-dimensional vectorcardiogram (VCG) formulation, we generate the normal cardiac dipole for a patient using a sum of Gaussian kernels, fitted to real VCG recordings. Abnormal beats...
Article
Full-text available
A general deflation framework is described for the separation of a desired signal subspace of arbitrary dimensions from noisy multichannel observations. The method simultaneously uses single and multichannel priors to split the desired and unde-sired subspaces, even for coplanar (intersecting) subspaces. By appropriate use of signal priors, it can...
Code
Full-text available
The Open-Source Electrophysiological Toolbox (OSET), online available at www.oset.ir, is a collection of electrophysiological data and open source codes for biological signal generation, modeling, processing, and filtering, originally released in June 2006. The toolbox is distributed under the GNU General Public License and may be freely used or mo...
Article
Full-text available
The field of electrocardiography has been in existence for over a century, yet despite significant advances in adult clinical electrocardiography, signal processing techniques and fast digital processors, the analysis of fetal ECGs is still in its infancy. This is, partly due to a lack of availability of gold standard databases, partly due to the r...
Conference Paper
Full-text available
Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work w...
Article
Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work w...
Article
Full-text available
A novel second-order-statistics-based sequential blind extraction algorithm for blind extraction of quasi-periodic signals, with time-varying period, is introduced in this paper. Source extraction is performed by sequentially converging to a solution that effectively diagonalizes autocorrelation matrices at lags corresponding to the time-varying pe...