Blood pressure estimation from appropriate and inappropriate PPG signals using A whole-based method

Biomedical Signal Processing and Control, Journal Year: 2018, Volume and Issue: 47, P. 196 - 206

Published: Aug. 29, 2018

Language: Английский

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Photoplethysmogram Analysis and Applications: An Integrative Review

Frontiers in Physiology, Journal Year: 2022, Volume and Issue: 12

Published: March 1, 2022

Beyond its use in a clinical environment, photoplethysmogram (PPG) is increasingly used for measuring the physiological state of an individual daily life. This review aims to examine existing research on concerning generation mechanisms, measurement principles, applications, noise definition, pre-processing techniques, feature detection and post-processing techniques processing, especially from engineering point view. We performed extensive search with PubMed, Google Scholar, Institute Electrical Electronics Engineers (IEEE), ScienceDirect, Web Science databases. Exclusion conditions did not include year publication, but articles published English were excluded. Based 118 articles, we identified four main topics enabling PPG: (A) PPG waveform, (B) features applications including basic based original combined PPG, derivative (C) motion artifact baseline wandering hypoperfusion, (D) signal processing preprocessing, peak detection, quality index. The application field has been extending mobile environment. Although there no standardized pipeline as data are acquired accumulated various ways, recently proposed machine learning-based method expected offer promising solution.

Language: Английский

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Wearable Photoplethysmography for Cardiovascular Monitoring

Proceedings of the IEEE, Journal Year: 2022, Volume and Issue: 110(3), P. 355 - 381

Published: March 1, 2022

Smart wearables provide an opportunity to monitor health in daily life and are emerging as potential tools for detecting cardiovascular disease (CVD). Wearables such fitness bands smartwatches routinely the photoplethysmogram signal, optical measure of arterial pulse wave that is strongly influenced by heart blood vessels. In this survey, we summarize fundamentals wearable photoplethysmography its analysis, identify clinical applications, outline pressing directions future research order realize full tackling CVD.

Language: Английский

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Synchronized wearables for the detection of haemodynamic states via electrocardiography and multispectral photoplethysmography

Nature Biomedical Engineering, Journal Year: 2023, Volume and Issue: 7(10), P. 1229 - 1241

Published: Oct. 2, 2023

Language: Английский

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Clinical assessment of a non-invasive wearable MEMS pressure sensor array for monitoring of arterial pulse waveform, heart rate and detection of atrial fibrillation

npj Digital Medicine, Journal Year: 2019, Volume and Issue: 2(1)

Published: May 14, 2019

There is an unmet clinical need for a low cost and easy to use wearable devices continuous cardiovascular health monitoring. A flexible wristband, based on microelectromechanical sensor (MEMS) elements array was developed support this need. The performance of the device in monitoring investigated by (i) comparing arterial pressure waveform recordings gold standard, invasive catheter recording (n = 18), (ii) analyzing ability detect irregularities rhythm 7), (iii) measuring heartrate accuracy 31). Arterial waveforms carry important physiological information comparison study revealed that made with standard resulted almost identical (r 0.9-0.99) pulse waveforms. can measure heart possible it. clustering analysis demonstrates perfect classification between atrial fibrillation (AF) sinus rhythm. showed near beat-to-beat (sensitivity 99.1%, precision 100%) healthy subjects. In contrast, detection from coronary artery disease patients challenging, but averaged extracted successfully (95% CI: -1.2 1.1 bpm). conclusion, results indicate could be useful remote diseases personalized medicine.

Language: Английский

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Blood Pressure Estimation Using Photoplethysmogram Signal and Its Morphological Features

IEEE Sensors Journal, Journal Year: 2019, Volume and Issue: 20(8), P. 4300 - 4310

Published: Dec. 24, 2019

In this paper, we present a machine learning model to estimate the blood pressure (BP) of person using only his photoplethysmogram (PPG) signal. We propose algorithms better detect some critical points PPG signal, such as systolic and diastolic peaks, dicrotic notch inflection point. These are applicable different signal morphologies improve precision feature extraction. show that logarithm reflection index, ratio low- high-frequency components heart rate (HR) variability product HR multiplied by modified Normalized Pulse Volume (mNPV) key features in accurately estimating BP Our proposed method has achieved higher accuracies compared previously reported methods use For BP, correlation coefficient between estimated values real is 0.78, mean absolute error 8.22 mmHg, their standard deviation 10.38 mmHg. 0.72, 4.17 4.22 The results fall within Grade A for diastolic, C B based on BHS standard.

Language: Английский

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Geometric leaf classification

Computer Vision and Image Understanding, Journal Year: 2014, Volume and Issue: 133, P. 102 - 109

Published: Nov. 20, 2014

Language: Английский

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RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection

Proceedings of the 2022 International Conference on Management of Data, Journal Year: 2021, Volume and Issue: unknown, P. 2328 - 2337

Published: June 9, 2021

Periodicity detection is a crucial step in time series tasks, including monitoring and forecasting of metrics many areas, such as IoT applications self-driving database management system. In these applications, multiple periodic components exist are often interlaced with each other. Such dynamic complicated patterns make the accurate periodicity difficult. addition, other series, trend, outliers noises, also pose additional challenges for detection. this paper, we propose robust general framework Our algorithm applies maximal overlap discrete wavelet transform to into temporal-frequency scales that different can be isolated. We rank them by variance, then at scale detect single our proposed Huber-periodogram Huber-ACF robustly. rigorously prove theoretical properties justify use Fisher's test on To further refine detected periods, compute unbiased autocorrelation function based Wiener-Khinchin theorem from improved robustness efficiency. Experiments synthetic real-world datasets show outperforms popular ones both

Language: Английский

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Detecting beats in the photoplethysmogram: benchmarking open-source algorithms

Physiological Measurement, Journal Year: 2022, Volume and Issue: 43(8), P. 085007 - 085007

Published: July 19, 2022

Abstract The photoplethysmogram (PPG) signal is widely used in pulse oximeters and smartwatches. A fundamental step analysing the PPG detection of heartbeats. Several beat algorithms have been proposed, although it not clear which performs best. Objective: This study aimed to: (i) develop a framework with to design test detectors; (ii) assess performance detectors different use cases; (iii) investigate how their affected by patient demographics physiology. Approach: Fifteen were assessed against electrocardiogram-derived heartbeats using data from eight datasets. Performance was F 1 score, combines sensitivity positive predictive value. Main results: Eight performed well absence movement scores ≥90% on hospital wearable collected at rest. Their poorer during exercise 55%–91%; neonates than adults 84%–96% compared 98%–99% adults; atrial fibrillation (AF) 92%–97% AF 99%–100% normal sinus rhythm. Significance: Two denoted ‘MSPTD’ ‘qppg’ best, complementary characteristics. evidence can be inform choice detector algorithm. algorithms, datasets, assessment are freely available.

Language: Английский

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Overhead Power Line Tension Estimation Method Using Accelerometers

Energies, Journal Year: 2025, Volume and Issue: 18(1), P. 181 - 181

Published: Jan. 3, 2025

Overhead power lines are important components of grids, and the status transmission line equipment directly affects safe reliable operation grids. In order to guarantee efficient usage grid, tension overhead is an parameter be measured. The can calculated from modal frequency, but measured acceleration data obtained accelerometer severely contaminated with noises. this paper, a multiscale-based peak detection (M-AMPD) algorithm used find possible frequencies in spectral density data. To obtain noise-free signal, median absolute deviations baseline correction (MAD-BS) applied. An accurate estimation for by iteration MAD-BS reduction frequency range technique. iterative technique improves accuracy estimated lines. contribute improving reliability efficiency grid. proposed implemented MATLAB R2020a verified comparison tensiometer.

Language: Английский

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