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    Heart Rate monitoring during physical exercise using wrist-type photoplethysmographic (PPG) signals

    , Article Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 25 August 2015 through 29 August 2015 ; Volume 2015-November , 2015 , Pages 6166-6169 ; 1557170X (ISSN) ; 9781424492718 (ISBN) Khas Ahmadi, A ; Moradi, P ; Malihi, M ; Karimi, S ; Shamsollahi, M. B ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Heart rate monitoring using wrist-type using photoplethysmographic (PPG) signals during subjects' intensive exercises is a challenging problem, since signals are strongly affected by motion artifacts caused by unexpected movements. This paper presents a method that uses both time and frequency characteristics of signals; using sparse signal reconstruction for high-resolution spectrum estimation. Experimental results on type data sets recorded from 12 subjects during fast running at peak speed of 15 km/hour. The results have a performance with the average absolute error being 1.80 beat per minute  

    Low complexity heart rate measurement from wearable wrist-type photoplethysmographic sensors robust to motion artifacts

    , Article ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 15 April 2018 through 20 April 2018 ; Volume 2018-April , 2018 , Pages 921-924 ; 15206149 (ISSN) ; 9781538646588 (ISBN) Boloursaz Mashhadi, M ; Farhadi, M ; Essalat, M ; Marvasti, F ; Sharif University of Technology
    This paper presents a low complexity while accurate Heart Rate (HR) estimation technique from signals captured by Photoplethysmographic (PPG) sensors worn on the wrist during intensive physical exercise. Wrist-type PPG signals experience severe Motion Artifacts (MA) that hinder efficient HR estimation especially during intensive physical exercises. To suppress the motion artifacts efficiently, simultaneous 3 dimensional acceleration signals are used as reference MAs. The proposed method achieves an Average Absolute Error (AAE) of 1.19 Beats Per Minute (BPM) on the 12 benchmark PPG recordings in which subjects run at speeds of up to 15 km/h. This method also achieves an AAE of 2.17 BPM on the... 

    Evaluating valence level of pictures stimuli in heart rate variability response

    , Article 42nd Computing in Cardiology Conference, CinC 2015, 6 September 2015 through 9 September 2015 ; Volume 42 , 2015 , Pages 1057-1060 ; 23258861 (ISSN); 9781509006854 (ISBN) Rezaei, S ; Moharreri, S ; Jafarnia Dabanloo, N ; Parvaneh, S ; Sharif University of Technology
    IEEE Computer Society  2015
    Low and high valence were induced in 20 male volunteers using two groups of pictures stimuli. Heart response was compared between two groups from RR series extracted from recorded ECG measurements. Mean heart rate and heart rate variability measures including time, frequency and Poincare domain were extracted. The results revealed that HRV triangular index, SDNN and SD2 were the only statistically significant parameters between groups (p<0.05). Mean heart rate and power in LF and HF bands were also different between low and high valence groups however level of significance was not reached. © 2015 CCAL  

    A hybrid algorithm for prediction of varying heart rate motion in computer-assisted beating heart surgery

    , Article Journal of Medical Systems ; Volume 42, Issue 10 , 2018 ; 01485598 (ISSN) Mansouri, S ; Farahmand, F ; Vossoughi, G ; Alizadeh Ghavidel, A ; Sharif University of Technology
    Springer New York LLC  2018
    An essential requirement for performing robotic assisted surgery on a freely beating heart is a prediction algorithm which can estimate the future trajectory of the heart in the varying heart rate (HR) conditions of real surgery with a high accuracy. In this study, a hybrid amplitude modulation- (AM) and autoregressive- (AR) based algorithm was developed to enable estimating the global and local oscillations of the beating heart, raised from its major and minor physiological activities. The AM model was equipped with an estimator of the heartbeat frequency to compensate for the HR variations. The RMS of the prediction errors of the hybrid algorithm was in the range of 165–361 μm for the... 

    Supervised heart rate tracking using wrist-type photoplethysmographic (PPG) signals during physical exercise without simultaneous acceleration signals

    , Article 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, 7 December 2016 through 9 December 2016 ; 2017 , Pages 1166-1170 ; 9781509045457 (ISBN) Essalat, M ; Boloursaz Mashhadi, M ; Marvasti, F ; IEEE Signal Processing Society; The Institute of Electrical and Electronics Engineers ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2017
    PPG based heart rate (HR) monitoring has recently attracted much attention with the advent of wearable devices such as smart watches and smart bands. However, due to severe motion artifacts (MA) caused by wristband stumbles, PPG based HR monitoring is a challenging problem in scenarios where the subject performs intensive physical exercises. This work proposes a novel approach to the problem based on supervised learning by Neural Network (NN). By simulations on the benchmark datasets [1], we achieve acceptable estimation accuracy and improved run time in comparison with the literature. A major contribution of this work is that it alleviates the need to use simultaneous acceleration signals.... 

    Time-varying assessment of heart rate variability parameters using respiratory information

    , Article Computers in Biology and Medicine ; Volume 89 , 2017 , Pages 355-367 ; 00104825 (ISSN) Goldoozian, L. S ; Zahedi, E ; Zarzoso, V ; Sharif University of Technology
    Analysis of heart rate variability (HRV) is commonly used for characterization of autonomic nervous system. As high frequency (HF, known as the respiratory-related) component of HR, overlaps with the typical low frequency (LF) band when the respiratory rate is low, a reference signal for HF variations would help in better discriminating the LF and HF components of HR. The present study proposes a model for time-varying separation of HRV components as well as estimation of HRV parameters using respiration information. An autoregressive moving average with exogenous input (ARMAX) model of HRV is considered with a parametrically modeled respiration signal as the input. The model parameters are... 

    Computerized interpretation of cardiotocographs using kubli score

    , Article 4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008, Antwerp, 23 November 2008 through 27 November 2008 ; Volume 22 , 2008 , Pages 962-965 ; 16800737 (ISSN); 9783540892076 (ISBN) Krupa, N ; Hasan, F. M ; Mohd Ali, M. A ; Zahedi, E ; Sharif University of Technology
    The purpose of this work is to interpret cardiotocograph recordings by estimating kubli score in order to find out the presence of antepartum morbidity in cardiotocograph (CTG) recordings. The Kubli score is a tool used to evaluate a non-stress test (NST). It works very much like an Apgar Score in that there are 5 criteria to be assessed, baseline rate, amplitude of fluctuations, frequency of fluctuations, deceleration and acceleration pattern, and each will be assigned a score of 0, 1, or 2, for a maximum total of 10. The advantage of the Kubli score is that it is systematic and specific. This communication tool helps clinicians to have a visual image of the immediate fetal status. Using... 

    Two statistical methods for resolving healthy individuals and those with congestive heart failure based on extended self-similarity and a recursive method

    , Article Journal of Biological Physics ; Volume 32, Issue 6 , 2006 , Pages 489-495 ; 00920606 (ISSN) Atyabi, F ; Livari, M. A ; Kaviani, K ; Rahimi Tabar , M. R ; Sharif University of Technology
    In this paper we introduce two methods for measuring irregularities in human heartbeat time series (HHTS). First we consider the multi-fractal structure of HHTS to distinguish healthy individuals and from those with congestive heart failure. In this way we modify the Extended Self-Similarity (ESS) method and apply it to HHTS. Our second approach is based on the recursive method, which we use to predict the duration of the next heartbeat by considering a few previous ones. We use standard physiological data and show that these approaches lead to very satisfactory methods to resolve the healthy and CHF individuals. These methods can be used potentially in portable electronic heart alarm... 

    Regeneration of stochastic processes: An inverse method

    , Article European Physical Journal B ; Volume 47, Issue 3 , 2005 , Pages 411-415 ; 14346028 (ISSN) Ghasemi, F ; Peinke, J ; Sahimi, M ; Rahimi Tabar, M. R ; Sharif University of Technology
    We propose a novel inverse method that utilizes a set of data to construct a simple equation that governs the stochastic process for which the data have been measured, hence enabling us to reconstruct the stochastic process. As an example, we analyze the stochasticity in the beat-to-beat fluctuations in the heart rates of healthy subjects as well as those with congestive heart failure. The inverse method provides a novel technique for distinguishing the two classes of subjects in terms of a drift and a diffusion coefficients which behave completely differently for the two classes of subjects, hence potentially providing a novel diagnostic tool for distinguishing healthy subjects from those... 

    Transabdominal fetal heart rate detection using NIR photopleythysmography: instrumentation and clinical results

    , Article IEEE Transactions on Biomedical Engineering ; Volume 56, Issue 8 , 2009 , Pages 2075-2082 ; 00189294 (ISSN) Gan, K. B ; Zahedi, E ; Mohd Ali, M. A ; Sharif University of Technology
    In obstetrics, fetal heart rate (FHR) detection remains the standard for intrapartum assessment of fetal well-being. In this paper, a low-power (<55 mW) optical technique is proposed for transabdominal FHR detection using near-infrared photoplesthys-mography (PPG). A beam of IR-LED (890 nm) propagates through to the maternal abdomen and fetal tissues, resulting in a mixed signal detected by a low-noise detector situated at a distance of 4 cm. Low-noise amplification and 24-bit analog-to-digital converter resolution ensure minimum effect of quantization noise. After synchronous detection, the mixed signal is processed by an adaptive filter to extract the fetal signal, whereas the PPG from the... 

    The application of empirical mode decomposition for the enhancement of cardiotocograph signals

    , Article Physiological Measurement ; Volume 30, Issue 8 , 2009 , Pages 729-743 ; 09673334 (ISSN) Krupa, B. N ; Mohd Ali, M. A ; Zahedi, E ; Sharif University of Technology
    Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is... 

    Applicability of adaptive noise cancellation to fetal heart rate detection using photoplethysmography

    , Article Computers in Biology and Medicine ; Volume 38, Issue 1 , 2008 , Pages 31-41 ; 00104825 (ISSN) Zahedi, E ; Beng, G. K ; Sharif University of Technology
    In this paper, an approach based on adaptive noise cancellation (ANC) is evaluated for extraction of the fetal heart rate using photoplethysmographic signals from the maternal abdomen. A simple optical model is proposed in which the maternal and fetal blood pulsations result in emulated signals where the lower SNR limit (fetal to maternal) is - 25 dB. It is shown that a recursive least-squares algorithm is capable of extracting the peaks of the fetal PPG from these signals, for typical values of maternal and fetal tissues. © 2007 Elsevier Ltd. All rights reserved  

    Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

    , Article BioMedical Engineering Online ; Volume 10 , 2011 ; 1475925X (ISSN) Krupa, N ; MA, M. A ; Zahedi, E ; Ahmed, S ; Hassan, F. M ; Sharif University of Technology
    Background: Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'.Methods: The FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from... 

    Heart Arrhythmia Classification based on Nonlinear Analysis and Dynamic Behavior of Heart Rate Variability (HRV)Signal

    , M.Sc. Thesis Sharif University of Technology Rezaei, Shahab (Author) ; Bagheri Shouraki, Saeed (Supervisor) ; Ghorshi, Mohammad Ali (Co-Advisor)
    Detection and classification of arrhythmia is important especially for patients in Emergency care units. Early diagnosis of cardiac arrhythmia makes it possible to choose appropriate anti arrhythmic drugs, and is thus very important for improving arrhythmia therapy. Computer-Assisted Diagnostic (CAD) Systems are used in recent decades in which extracted features and classifiers are the most important factor. In this project, we try to focus on both of these two major factors in heart arrhythmia classification using HRV signal. Therefore, in this project, we try to classify different groups of arrhythmia using HRV signal processing especially the nonlinear processing. Our main aim is to... 

    Enhancing physionet electrocardiogram records for fetal heart rate detection algorithm

    , Article Proceedings - 2015 2nd International Conference on Biomedical Engineering, ICoBE 2015 ; 2015 ; 9781479917495 (ISBN) Yusuf, W. Y. W ; Ali, M. A. M ; Zahedi, E ; Sharif University of Technology
    The noninvasive fetal electrocardiogram (ECG) data available from Physionet data bank are suitable for developing fetal heart rate (FHR) detection algorithms. The data have been collected from single subject with a broad range of gestation weeks, and have a total data length of more than 9 hours arranged in 55 data sets. However, there are three additional data features which are currently not directly available from Physionet to facilitate the easy usage of these data: (1) the fetal peak visibility evaluation, (2) the gestation week, and (3) the data length. This article presents an improvement to the data bank by providing the additional features. The required pre-processing of the data is... 

    Two channel abdominal PPG instrumentation

    , Article IFMBE Proceedings ; Volume 21 IFMBE, Issue 1 , 2008 , Pages 691-693 ; 16800737 (ISSN); 9783540691389 (ISBN) Gan, K. B ; Mohd Ali, M. A ; Zahedi, E ; Sharif University of Technology
    Springer Verlag  2008
    In this paper, a two channel abdominal PPG instrumentation is developed. The proposed instrument consists of IR-LED and its driver, photo-detector and data acquisition card. The modulation frequency generation, demodulation and digital signal processing is done completely in the digital domain using LabView. The results show that the developed instrument is able to acquire signal from the abdomen even at 4 cm source to detector separation. This instrument is intended for future application in trans-abdominal fetal heart rate detection. © 2008 Springer-Verlag  

    Designing the FPGA-based system for Triangle Phase space Mapping (TPSM) of heart rate variability (HRV) signal

    , Article 2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015, 9 July 2015 through 11 July 2015 ; July , 2015 , Page(s): 1 - 4 ; 9781479984985 (ISBN) Rezaei, S ; Moharreri, S ; Ghorshi, A ; Molnar K ; Herencsar N ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    There has been an increasing interest in telemonitoring thanks to the availability of new technologies for data transmission and processing with better performances and lower costs. In this paper, we try to develop and implement the HRV signal processing into a Field Programmable Gate Array (FPGA). The hardware implementing algorithm was developed in Verilog Hardware Description Language (HDL). In designed hardware, after defining the number of samples in the input, we extract and analyses the Triangular Phase Space Mapping (TPSM), a novel method for representation of heart rate. The performance of the system was tested using MATLAB and validated based on the input signals  

    An improved algorithm for heart Rate tracking during physical exercise using simultaneous wrist-type photoplethysmographic (PPG) and acceleration signals

    , Article 2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st International Iranian Conference on Biomedical Engineering, ICBME 2016, 23 November 2016 through 25 November 2016 ; 2017 , Pages 146-149 ; 9781509034529 (ISBN) Boloursaz Mashhadi, M ; Essalat, M ; Ahmadi, M ; Marvasti, F ; Sharif University of Technology
    Causal Heart Rate (HR) monitoring using photoplethysmographic (PPG) signals recorded from wrist during physical exercise is a challenging task because the PPG signals in this scenario are highly contaminated by artifacts caused by hand movements of the subject. This paper proposes a novel algorithm for this problem, which consists of two main blocks of Noise Suppression and Peak Selection. The Noise Suppression block removes Motion Artifacts (MAs) from the PPG signals utilizing simultaneously recorded 3D acceleration data. The Peak Selection block applies some decision mechanisms to correctly select the spectral peak corresponding to HR in PPG spectra. Experimental results on benchmark... 

    An artificial multi-channel model for generating abnormal electrocardiographic rhythms

    , Article Computers in Cardiology 2008, CAR, Bologna, 14 September 2008 through 17 September 2008 ; Volume 35 , 2008 , Pages 773-776 ; 02766574 (ISSN); 1424437067 (ISBN); 9781424437061 (ISBN) Clifford, G. D ; Nemati, S ; Sameni, R ; Sharif University of Technology
    We present generalizations of our previously published artificial models for generating multi-channel ECG so that the simulation of abnormal rhythms is possible. 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 are then specified either as new dipoles, or as perturbations of the existing dipole. Switching between normal and abnormal beat types is achieved using a hidden Markov model (HMM). Probability transitions can be learned from real data or modeled by coupling to heart rate and sympathovagal balance. Natural morphology changes form beat-to-beat... 

    Prediction of Heart Arrhythmias Related to Pramature Beats

    , M.Sc. Thesis Sharif University of Technology Sabeti, Elyas (Author) ; Shamsollahi, Mohammad Bagher (Supervisor)
    About 42 percent of annual mortality in all around the world is originated from cardiovascular arrhythmias and diseases. One of these arrhythmias is atrial fibrillation whose onset and persistence can produce clot and consequently cause stroke. The basis of our research are upon this idea that dangerous heart arrhythmias do not happen abruptly and there always are some background signs before occurrence of them. In our approach to predict the onset of atrial fibrillation, by analyzing ECG signal in order to extract distinguishing features, we want to classify signals which will terminate Paroxysmal Atrial Fibrillation (PAF) from signals which won’t end with PAF. In this thesis, we propose...