A Robust Method for Pulse Peak Determination in a Digital Volume Pulse Waveform With a Wandering Baseline

Jang, Dae-Geun; Farooq, Umar; Park, Seung-Hun; Hahn, Minsoo

doi:10.1109/tbcas.2013.2295102

Cited by 36 publications

(20 citation statements)

References 22 publications

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“…Since these measures quantize the error between manually annotated and automatically detected PTTs, the smaller the values of the ERnorm and the MAD, the better is the performance [15]. The results show that the measures of the proposed method are lower than those of the conventional maximum peak picking and pulse peak estimation methods.…”

Section: Discussionmentioning

confidence: 96%

“…R-waves were annotated with the criterion of the first upward deflection after the small upward wave (P-wave) in the ECG signals [28] and pulse peaks were annotated with the criterion of the first maximum peak of each cardiac cycle in the PPG signals [15], [16].…”

Section: Data Acquisition and Annotationmentioning

confidence: 99%

“…We investigated how closely the proposed approach detects true positions of pulse peaks and how accurately it estimates PTTs compared to the conventional maximum peak picking method [1], [5], the knowledge-based rules [17], the adaptive threshold method [18], and the template matching method [19] using three quantitative measures: the normalized error rate (ER norm ) [15], the mean absolute difference (MAD) of pulse peaks, and the MAD of PTTs. Each measure is defined as (4) and (5) …”

Section: B Performance Evaluationmentioning

confidence: 99%

“…Traditionally, the PTT has been estimated directly on the pulse waveforms by picking the maximum peak in a range of consecutive R-waves [1], [5]. However, this approach can yield unreliable results in noisy and corrupted PPG signals [15]. In order to cope with this problem, Solà et al introduced a parametric approach [5].…”

Section: Introductionmentioning

confidence: 99%

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A Gaussian Model-Based Probabilistic Approach for Pulse Transit Time Estimation

Jang

Park²,

Hahn

2016

IEEE J. Biomed. Health Inform.

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In this paper, we propose a new probabilistic approach to pulse transit time (PTT) estimation using a Gaussian distribution model. It is motivated basically by the hypothesis that PTTs normalized by RR intervals follow the Gaussian distribution. To verify the hypothesis, we demonstrate the effects of arterial compliance on the normalized PTTs using the Moens-Korteweg equation. Furthermore, we observe a Gaussian distribution of the normalized PTTs on real data. In order to estimate the PTT using the hypothesis, we first assumed that R-waves in the electrocardiogram (ECG) can be correctly identified. The R-waves limit searching ranges to detect pulse peaks in the photoplethysmogram (PPG) and to synchronize the results with cardiac beats--i.e., the peaks of the PPG are extracted within the corresponding RR interval of the ECG as pulse peak candidates. Their probabilities of being the actual pulse peak are then calculated using a Gaussian probability function. The parameters of the Gaussian function are automatically updated when a new pulse peak is identified. This update makes the probability function adaptive to variations of cardiac cycles. Finally, the pulse peak is identified as the candidate with the highest probability. The proposed approach is tested on a database where ECG and PPG waveforms are collected simultaneously during the submaximal bicycle ergometer exercise test. The results are promising, suggesting that the method provides a simple but more accurate PTT estimation in real applications.

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Section: Discussionmentioning

confidence: 96%

Section: Data Acquisition and Annotationmentioning

confidence: 99%

Section: B Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Gaussian Model-Based Probabilistic Approach for Pulse Transit Time Estimation

Jang

Park²,

Hahn

2016

IEEE J. Biomed. Health Inform.

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“…Event detection represents an essential step in many biomedical signal processing applications, such as QRS complex detection [21], electrogram event detection [22], detection of rapid-eye movements in sleep studies [23], heartbeat and respiration detection [24], pulse peak determination in digital volume pulse waveforms [25]. Accordingly, many different methods have been developed, which most often rely on some peculiar feature of the application at hand.…”

mentioning

confidence: 99%

A Simple and Robust Event-Detection Algorithm for Single-Cell Impedance Cytometry

Caselli

Bisegna

2016

IEEE Trans. Biomed. Eng.

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Abstract-Microfluidic impedance cytometry is emerging as a powerful label-free technique for the characterization of single biological cells. In order to increase the sensitivity and the specificity of the technique, suited digital signal processing methods are required to extract meaningful information from measured impedance data.In this work, a simple and robust event-detection algorithm for impedance cytometry is presented. Since a differential measuring scheme is generally adopted, the signal recorded when a cell passes through the sensing region of the device exhibits a typical odd-symmetric pattern. This feature is exploited twice by the proposed algorithm: first, a preliminary segmentation, based on the correlation of the data stream with the simplest oddsymmetric template, is performed; then, the quality of detected events is established by evaluating their E2O index, that is, a measure of the ratio between their even and odd parts.A thorough performance analysis is reported, showing the robustness of the algorithm with respect to parameter choice and noise level. In terms of sensitivity and positive predictive value, an overall performance of 94.9% and 98.5%, respectively, was achieved on two datasets relevant to microfluidic chips with very different characteristics, considering three noise levels.The present algorithm can foster the role of impedance cytometry in single-cell analysis, which is the new frontier in "Omics".

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High‐Performing Acid‐Free PEDOT:PSS‐Based Organic Photodiodes for Cardiovascular Disease Diagnosis

Yang,

Kim,

Jang

et al. 2023

Adv Funct Materials

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Photodetectors made from low‐toxicity organic materials are considered a promising alternative to conventional inorganic photodetectors. However, the performance of current organic photodetectors (OPD) needs to be further enhanced. This study aims to introduce acid‐free poly(3,4‐ethylenedioxythiophene)‐(polystyrene sulfonate) (PEDOT‐(PSS)) films in order to improve the performance of OPDs in practical applications. Utilization of heterocyclic 1,3‐diazole (HDZ) in PEDOT‐(PSS) improves the polymerization degree, carrier mobility, and other physicochemical properties. These enhanced properties also improve the comprehensive performance of OPD. In this flow, the enhanced noise suppression is also confirmed by elucidating the device's performance limitations. Consequently, the presented OPD‐based photoplethysmography sensor has the ability to diagnose blood circulation status and cardiovascular diseases. This accomplishment marks the first in single pixel‐based organic photodiode research.

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A Robust Method for Pulse Peak Determination in a Digital Volume Pulse Waveform With a Wandering Baseline

Cited by 36 publications

References 22 publications

A Gaussian Model-Based Probabilistic Approach for Pulse Transit Time Estimation

A Gaussian Model-Based Probabilistic Approach for Pulse Transit Time Estimation

A Simple and Robust Event-Detection Algorithm for Single-Cell Impedance Cytometry

High‐Performing Acid‐Free PEDOT:PSS‐Based Organic Photodiodes for Cardiovascular Disease Diagnosis

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