The Experts below are selected from a list of 1962 Experts worldwide ranked by ideXlab platform
M. Fernández-chimeno - One of the best experts on this subject based on the ideXlab platform.
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EMBC - Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and Fiducial Point selection
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and, 2015Co-Authors: V. Ferrer-mileo, F. Guede-fernandez, M. Fernández-chimeno, J. Ramos-castro, M. A. García-gonzálezAbstract:This work compares several Fiducial Points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and Fiducial Point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these Points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.
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Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and Fiducial Point selection
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015Co-Authors: V. Ferrer-mileo, F. Guede-fernandez, M. Fernández-chimeno, J. Ramos-castro, M. A. García-gonzálezAbstract:This work compares several Fiducial Points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and Fiducial Point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these Points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.
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EMBC - The effect of electrocardiographic lead choice on RR time series
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and, 2011Co-Authors: M. A. García-gonzález, J. Ramos-castro, M. Fernández-chimenoAbstract:Results of heart rate variability analysis depend on the quality of the initial RR time series that is measured only in one lead of the ECG. This work shows that RR time series can subtly change from lead to lead so the choice of the analyzed lead is another source of uncertainty. The standard deviation of the differences of two RR time series obtained from different leads can change from 0.5 ms to more than 20 ms depending on the amount of noise, the morphological changes of the QRS complexes, the strategies of Fiducial Point determination and the measured subject. This source of uncertainty is in healthy subjects greater than that associated to the sampling frequency of the ECG for sampling frequencies greater than 400 Hz.
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The effect of electrocardiographic lead choice on RR time series
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011Co-Authors: M. A. García-gonzález, J. Ramos-castro, M. Fernández-chimenoAbstract:Results of heart rate variability analysis depend on the quality of the initial RR time series that is measured only in one lead of the ECG. This work shows that RR time series can subtly change from lead to lead so the choice of the analyzed lead is another source of uncertainty. The standard deviation of the differences of two RR time series obtained from different leads can change from 0.5 ms to more than 20 ms depending on the amount of noise, the morphological changes of the QRS complexes, the strategies of Fiducial Point determination and the measured subject. This source of uncertainty is in healthy subjects greater than that associated to the sampling frequency of the ECG for sampling frequencies greater than 400 Hz.
M. A. García-gonzález - One of the best experts on this subject based on the ideXlab platform.
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EMBC - Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and Fiducial Point selection
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and, 2015Co-Authors: V. Ferrer-mileo, F. Guede-fernandez, M. Fernández-chimeno, J. Ramos-castro, M. A. García-gonzálezAbstract:This work compares several Fiducial Points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and Fiducial Point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these Points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.
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Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and Fiducial Point selection
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015Co-Authors: V. Ferrer-mileo, F. Guede-fernandez, M. Fernández-chimeno, J. Ramos-castro, M. A. García-gonzálezAbstract:This work compares several Fiducial Points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and Fiducial Point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these Points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.
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EMBC - The effect of electrocardiographic lead choice on RR time series
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and, 2011Co-Authors: M. A. García-gonzález, J. Ramos-castro, M. Fernández-chimenoAbstract:Results of heart rate variability analysis depend on the quality of the initial RR time series that is measured only in one lead of the ECG. This work shows that RR time series can subtly change from lead to lead so the choice of the analyzed lead is another source of uncertainty. The standard deviation of the differences of two RR time series obtained from different leads can change from 0.5 ms to more than 20 ms depending on the amount of noise, the morphological changes of the QRS complexes, the strategies of Fiducial Point determination and the measured subject. This source of uncertainty is in healthy subjects greater than that associated to the sampling frequency of the ECG for sampling frequencies greater than 400 Hz.
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The effect of electrocardiographic lead choice on RR time series
2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011Co-Authors: M. A. García-gonzález, J. Ramos-castro, M. Fernández-chimenoAbstract:Results of heart rate variability analysis depend on the quality of the initial RR time series that is measured only in one lead of the ECG. This work shows that RR time series can subtly change from lead to lead so the choice of the analyzed lead is another source of uncertainty. The standard deviation of the differences of two RR time series obtained from different leads can change from 0.5 ms to more than 20 ms depending on the amount of noise, the morphological changes of the QRS complexes, the strategies of Fiducial Point determination and the measured subject. This source of uncertainty is in healthy subjects greater than that associated to the sampling frequency of the ECG for sampling frequencies greater than 400 Hz.
Jean Rouat - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - Non-negative sparse image coder via simulated annealing and pseudo-inversion
2008 IEEE International Conference on Acoustics Speech and Signal Processing, 2008Co-Authors: Ramin Pichevar, Jean RouatAbstract:We propose a sparse non-negative image coding based on simulated annealing and matrix pseudo-inversion. We show that sparsity and non-negativity are both important to obtain part-based coding and we also show the impact of each of them on the coding. In contrast with other approaches in the literature, our method can constrain both weights and basis vectors to generate part-based bases suitable for image recognition and Fiducial Point extraction. We also propose a speed-up of the algorithm by implementing a hybrid system that mixes simulated annealing and pseudo-inverse computation of matrices.
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Non-negative sparse image coder via simulated annealing and pseudo-inversion
2008 IEEE International Conference on Acoustics Speech and Signal Processing, 2008Co-Authors: Ramin Pichevar, Jean RouatAbstract:We propose a sparse non-negative image coding based on simulated annealing and matrix pseudo-inversion. We show that sparsity and non-negativity are both important to obtain part-based coding and we also show the impact of each of them on the coding. In contrast with other approaches in the literature, our method can constrain both weights and basis vectors to generate part-based bases suitable for image recognition and Fiducial Point extraction. We also propose a speed-up of the algorithm by implementing a hybrid system that mixes simulated annealing and pseudo-inverse computation of matrices.
Prasad Sistla - One of the best experts on this subject based on the ideXlab platform.
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Accurate Fiducial Point Detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation.
IEEE Journal of Translational Engineering in Health and Medicine, 2020Co-Authors: Muskan Singla, Syed Azeemuddin, Prasad SistlaAbstract:Pulse Arrival Time (PAT) derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) for cuff-less Blood Pressure (BP) measurement has been a contemporary and widely accepted technique. However, the features extracted for it are conventionally from an isolated pulse of ECG and PPG signals. As a result, the estimated BP is intermittent. OBJECTIVE This paper presents feature extraction from each beat of ECG and PPG signals to make BP measurements uninterrupted. These features are extracted by employing Haar transformation to adaptively attenuate measurement noise and improve the Fiducial Point detection precision. METHOD the use of only PAT feature as an independent variable leads to an inaccurate estimation of either Systolic Blood Pressure (SBP) or Diastolic Blood Pressure (DBP) or both. We propose the extraction of supplementary features that are highly correlated to physiological parameters. Concurrent data was collected as per the Association for the Advancement of Medical Instrumentation (AAMI) guidelines from 171 human subjects belonging to diverse age groups. An Adaptive Window Wavelet Transformation (AWWT) technique based on Haar wavelet transformation has been introduced to segregate pulses. Further, an algorithm based on log-linear regression analysis is developed to process extracted features from each beat to calculate BP. RESULTS The mean error of 0.43 and 0.20 mmHg, mean absolute error of 4.6 and 2.3 mmHg, and Standard deviation of 6.13 and 3.06 mmHg is achieved for SBP and DBP respectively. CONCLUSIONS The features extracted are highly precise and evaluated BP values are as per the AAMI standards. Clinical Impact: This continuous real-time BP monitoring technique can be useful in the treatment of hypertensive and potential-hypertensive subjects.
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Accurate Fiducial Point Detection Using Haar Wavelet for Beat-by-Beat Blood Pressure Estimation
IEEE Journal of Translational Engineering in Health and Medicine, 2020Co-Authors: Muskan Singla, Syed Azeemuddin, Prasad SistlaAbstract:Pulse Arrival Time (PAT) derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) for cuff-less Blood Pressure (BP) measurement has been a contemporary and widely accepted technique. However, the features extracted for it are conventionally from an isolated pulse of ECG and PPG signals. As a result, the estimated BP is intermittent. Objective: This paper presents feature extraction from each beat of ECG and PPG signals to make BP measurements uninterrupted. These features are extracted by employing Haar transformation to adaptively attenuate measurement noise and improve the Fiducial Point detection precision. Method: the use of only PAT feature as an independent variable leads to an inaccurate estimation of either Systolic Blood Pressure (SBP) or Diastolic Blood Pressure (DBP) or both. We propose the extraction of supplementary features that are highly correlated to physiological parameters. Concurrent data was collected as per the Association for the Advancement of Medical Instrumentation (AAMI) guidelines from 171 human subjects belonging to diverse age groups. An Adaptive Window Wavelet Transformation (AWWT) technique based on Haar wavelet transformation has been introduced to segregate pulses. Further, an algorithm based on log-linear regression analysis is developed to process extracted features from each beat to calculate BP. Results: The mean error of 0.43 and 0.20 mmHg, mean absolute error of 4.6 and 2.3 mmHg, and Standard deviation of 6.13 and 3.06 mmHg is achieved for SBP and DBP respectively. Conclusions: The features extracted are highly precise and evaluated BP values are as per the AAMI standards. Clinical Impact: This continuous real-time BP monitoring technique can be useful in the treatment of hypertensive and potential-hypertensive subjects.
Kilhoum Park - One of the best experts on this subject based on the ideXlab platform.
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Advanced Real-Time Dynamic Programming in the Polygonal Approximation of ECG Signals for a Lightweight Embedded Device
IEEE Access, 2019Co-Authors: Yoosoo Jeong, Daejin Park, Junho Kwak, Kilhoum ParkAbstract:Arrhythmia is less frequent than a normal heartbeat in an electrocardiogram signal, and the analysis of an electrocardiogram measurement can require more than 24 hours. Therefore, the efficient storage and transmission of electrocardiogram signals have been studied, and their importance has increased recently due to the miniaturization and weight reduction of measurement equipment. The polygonal approximation method based on dynamic programming can effectively achieve signal compression and Fiducial Point detection by expressing signals with a small number of vertices. However, the execution time and memory area rapidly increase depending on the length of the signal and number of vertices, which are not suitable for lightweight and miniaturized equipment. In this paper, we propose a method that can be applied in embedded environments by optimizing the processing time and memory usage of dynamic programming applied to the polygonal approximation of an ECG signal. The proposed method is divided into three steps to optimize the processing time and memory usage of dynamic programming. The first optimization step is based on the characteristics of electrocardiogram signals in the polygonal approximation. Second, the size of a data bit is used as the threshold for the time difference of each vertex. Finally, a type conversion and memory optimization are applied, which allow real-time processing in embedded environments. After analyzing the performance of the proposed algorithm for a signal length L and number of vertices N, the execution time is reduced from O(L2N) to O(L), and the memory usage is reduced from O(L2N) to O(LN). In addition, the proposed method preserve a performance of Fiducial Point detection. In a QT-DB experiment provided by Physionet, achieving values of -4.01 ± 7.99 ms and -5.46 ± 8.03 ms.
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efficient Fiducial Point detection of ecg qrs complex based on polygonal approximation
Sensors, 2018Co-Authors: Yoosoo Jeong, Daejin Park, Kilhoum ParkAbstract:Electrocardiogram signal analysis is based on detecting a Fiducial Point consisting of the onset, offset, and peak of each waveform. The accurate diagnosis of arrhythmias depends on the accuracy of Fiducial Point detection. Detecting the onset and offset Fiducial Points is ambiguous because the feature values are similar to those of the surrounding sample. To improve the accuracy of this paper’s Fiducial Point detection, the signal is represented by a small number of vertices through a curvature-based vertex selection technique using polygonal approximation. The proposed method minimizes the number of candidate samples for Fiducial Point detection and emphasizes these sample’s feature values to enable reliable detection. It is also sensitive to the morphological changes of various QRS complexes by generating an accumulated signal of the amplitude change rate between vertices as an auxiliary signal. To verify the superiority of the proposed algorithm, error distribution is measured through comparison with the QT-DB annotation provided by Physionet. The mean and standard deviation of the onset and the offset were stable as −4.02±7.99 ms and −5.45±8.04 ms, respectively. The results show that proposed method using small number of vertices is acceptable in practical applications. We also confirmed that the proposed method is effective through the clustering of the QRS complex. Experiments on the arrhythmia data of MIT-BIH ADB confirmed reliable Fiducial Point detection results for various types of QRS complexes.