A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China

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Blockwise PPG Enhancement Based on Time-Variant Zero-Phase Harmonic Notch Filtering

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A comb filter based signal processing method to effectively reduce motion artifacts from photoplethysmographic signals

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PPG-BP Database

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Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques

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An optimal filter for short photoplethysmogram signals

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Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification

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Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: a review from VascAgeNet

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A review of machine learning in hypertension detection and blood pressure estimation based on clinical and physiological data

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Hypertension Assessment via ECG and PPG Signals: An Evaluation Using MIMIC Database

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Wearable Photoplethysmography for Cardiovascular Monitoring.

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Toward Generating More Diagnostic Features from Photoplethysmogram Waveforms

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Hypertension Assessment Using Photoplethysmography: A Risk Stratification Approach

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A benchmark for machine-learning based non-invasive blood pressure estimation using photoplethysmogram

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An Unobtrusive and Calibration-free Blood Pressure Estimation Method using Photoplethysmography and Biometrics

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How Effective Is Pulse Arrival Time for Evaluating Blood Pressure? Challenges and Recommendations from a Study Using the MIMIC Database

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Continuous Non-Invasive Blood Pressure Monitoring: A Methodological Review on Measurement Techniques

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A Benchmark Study of Machine Learning for Analysis of Signal Feature Extraction Techniques for Blood Pressure Estimation Using Photoplethysmography (PPG)

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PlethAugment: GAN-Based PPG Augmentation for Medical Diagnosis in Low-Resource Settings

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A survey: From shallow to deep machine learning approaches for blood pressure estimation using biosensors

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Noninvasive Classification of Blood Pressure Based on Photoplethysmography Signals Using Bidirectional Long Short-Term Memory and Time-Frequency Analysis

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Performer: A Novel PPG-to-ECG Reconstruction Transformer for a Digital Biomarker of Cardiovascular Disease Detection

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Detection of Cardiovascular Disease Based on PPG Signals Using Machine Learning with Cloud Computing

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Synthetic photoplethysmogram generation using two Gaussian functions

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Noninvasive Blood Pressure Classification Based on Photoplethysmography Using K-Nearest Neighbors Algorithm: A Feasibility Study

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A machine learning approach for hypertension detection based on photoplethysmography and clinical data

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pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis

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Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

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ExHyptNet: An explainable diagnosis of hypertension using EfficientNet with PPG signals

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Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation

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Blood Pressure Measurement: From Cuff-Based to Contactless Monitoring

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Non-Invasive Classification of Blood Glucose Level Based on Photoplethysmography Using Time–Frequency Analysis

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PPGSynth: An Innovative Toolbox for Synthesizing Regular and Irregular Photoplethysmography Waveforms

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A Machine Learning Approach to Predict Diabetes Using Short Recorded Photoplethysmography and Physiological Characteristics

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PPG-based blood pressure estimation can benefit from scalable multi-scale fusion neural networks and multi-task learning

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Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher

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Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals

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Development of a novel light-sensitive PPG model using PPG scalograms and PPG-NET learning for non-invasive hypertension monitoring

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Research on a Non-Invasive Hemoglobin Measurement System Based on Four-Wavelength Photoplethysmography

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Beat-Based PPG-ABP Cleaning Technique for Blood Pressure Estimation

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Hypertension Detection Based on Photoplethysmography Signal Morphology and Machine Learning Techniques

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Your smartphone could act as a pulse-oximeter and as a single-lead ECG

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Classification of cardiac disorders using 1D local ternary patterns based on pulse plethysmograph signals

Aziz, S., Awais, M., Khan, M. U., Iqtidar, K., & Qamar, U. (2021) · Expert Systems · doi:10.1111/exsy.12664 · Cited by 24 · see citing works

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring

Wang, C.-F., Wang, T.-Y., Kuo, P.-H., Wang, H., Li, S.-Z., Lin, C., Chan, S.-C., Liu, T., Lo, Y., Lin, S.-H., et al. (2023) · Biosensors · doi:10.3390/bios13030321 · Cited by 24 · see citing works

Comparison of Different Machine Learning Techniques for the Cuffless Estimation of Blood Pressure using PPG Signals

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A novel method for continuous blood pressure estimation based on a single-channel photoplethysmogram signal

Hu, Q., Deng, X., Wang, A., & Yang, C. (2020) · Physiological Measurement · doi:10.1088/1361-6579/abc8dd · Cited by 23 · see citing works

Video Based Cocktail Causal Container for Blood Pressure Classification and Blood Glucose Prediction

Zhang, C., Jovanov, E., Liao, H., Zhang, Y., Lo, B. P. L., Zhang, Y., & Guan, C. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3220967 · Cited by 22 · see citing works

A novel interpretable feature set optimization method in blood pressure estimation using photoplethysmography signals

Liu, J., Hu, S., Xiao, Z., Hu, Q., Wang, D., & Yang, C. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105184 · Cited by 23 · see citing works

A Survey of PPG's Application in Authentication

Li, L., Chen, C., Pan, L., Zhang, L. Y., Wang, Z., Zhang, J., & Xiang, Y. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103488 · Cited by 24 · see citing works

An FPGA Implementation of Multiclass Disease Detection From PPG

Chowdhury, A., Das, D., Hasan, K., Cheung, R. C. C., & Chowdhury, M. H. (2023) · IEEE Sensors Letters · doi:10.1109/lsens.2023.3322288 · Cited by 22 · see citing works

Photoplethysmography signal quality assessment using attractor reconstruction analysis

Schmith, J., Kelsch, C., Cunha, B., Prade, L. R., Martins, E. A., Keller, A. L., & de Figueiredo, R. M. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105142 · Cited by 21 · see citing works

Research on Estimation of Blood Glucose Based on PPG and Deep Neural Networks

Deng, H., Zhang, L., Xie, Y., & Mo, S. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/693/1/012046 · Cited by 20 · see citing works

A Data-Driven Model with Feedback Calibration Embedded Blood Pressure Estimator Using Reflective Photoplethysmography

Chen, J., Huang, H.-K., Fang, Y.-T., Lin, Y.-T., Li, S.-Z., Chen, B., Lo, Y., Chen, P.-C., Wang, C.-F., & Chen, Y. (2022) · Sensors · doi:10.3390/s22051873 · Cited by 18 · see citing works

Joint Regression Network and Window Function-Based Piecewise Neural Network for Cuffless Continuous Blood Pressure Estimation Only Using Single Photoplethesmogram

Qiu, Z., Chen, D., Ling, B. W., Liu, Q., & Li, W. (2022) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2022.3174689 · Cited by 19 · see citing works

Beat-to-Beat Blood Pressure Estimation by Photoplethysmography and Its Interpretation

Fleischhauer, V., Feldheiser, A., & Zaunseder, S. (2022) · Sensors · doi:10.3390/s22187037 · Cited by 18 · see citing works

An experimental investigation on pulse transit time and pulse arrival time using ecg, pressure and ppg sensors

Sukesh Rao, M., C, N. K., Adithi, K., & Bangera, S. C. (2023) · Medicine in Novel Technology and Devices · doi:10.1016/j.medntd.2023.100214 · Cited by 18 · see citing works

Deep Learning based non-invasive diabetes predictor using Photoplethysmography signals

Srinivasan, V. B., & Foroozan, F. (2021) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco54536.2021.9616351 · Cited by 17 · see citing works

PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points

Abdullah, S., Hafid, A., Folke, M., Lindén, M., & Kristoffersson, A. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2023.1199604 · Cited by 18 · see citing works

Estimation of Organizational Competitiveness by a Hybrid of One-Dimensional Convolutional Neural Networks and Self-Organizing Maps Using Physiological Signals for Emotional Analysis of Employees

Alanazi, S., Alruwaili, M., Ahmad, F., Alaerjan, A., & Alshammari, N. O. (2021) · Sensors · doi:10.3390/s21113760 · Cited by 16 · see citing works

Ethnic disparities in publicly-available pulse oximetry databases

Sinaki, F. Y., Ward, R. K., Abbott, D., Allen, J., Fletcher, R., Menon, C., & Elgendi, M. (2022) · Communications Medicine · doi:10.1038/s43856-022-00121-8 · Cited by 16 · see citing works

Type 2 Diabetes Detection With Light CNN From Single Raw PPG Wave

Zanelli, S., El‐Yacoubi, M. A., Hallab, M., & Ammi, M. (2023) · IEEE Access · doi:10.1109/access.2023.3274484 · Cited by 16 · see citing works

Photoplethysmogram-based heart rate and blood pressure estimation with hypertension classification

Chowdhury, A., Das, D., Eldaly, A. B. M., Cheung, R. C. C., & Chowdhury, M. H. (2024) · IPEM-Translation · doi:10.1016/j.ipemt.2024.100024 · Cited by 16 · see citing works

CardioNet: Deep Learning Framework for Prediction of CVD Risk Factors

Panwar, M., Gautam, A., Dutt, R., & Acharyya, A. (2020) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas45731.2020.9180636 · Cited by 16 · see citing works

Intensive care photoplethysmogram datasets and machine-learning for blood pressure estimation: Generalization not guarantied

Weber-boisvert, G., Gosselin, B. J., & Sandberg, F. (2023) · Frontiers in Physiology · doi:10.3389/fphys.2023.1126957 · Cited by 16 · see citing works

Wearable Blood Pressure Monitoring Devices: Understanding Heterogeneity in Design and Evaluation

Cheung, M. Y., Sabharwal, A., Coté, G. L., & Veeraraghavan, A. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3434344 · Cited by 16 · see citing works

Estimating Reliability of Signal Quality of Physiological Data from Data Statistics Itself for Real-time Wearables

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Non-invasive cuff-less blood pressure machine learning algorithm using photoplethysmography and prior physiological data

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Diagnosis of Community-Acquired pneumonia in children using photoplethysmography and Machine learning-based classifier

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Noninvasive Blood Glucose Detection System With Infrared Pulse Sensor and Hybrid Feature Neural Network

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Calibration-free Blood Pressure Assessment Using An Integrated Deep Learning Method

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An improved deep regression model with state space reconstruction for continuous blood pressure estimation

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GRU-Based Fusion Models for Enhanced Blood Pressure Estimation From PPG Signals

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FPGA Implementation of PPG-Based Cardiovascular Diseases and Diabetes Classification Algorithm

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Optimal Preprocessing of Raw Signals from Reflective Mode Photoplethysmography in Wearable Devices

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CATransformer: A Cycle-Aware Transformer for High-Fidelity ECG Generation From PPG

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Novel Flexible Organic Photoplethysmogram Sensor for Continuous Cardiovascular Monitoring

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Hap-pulse: A Wearable Vibrotactile Glove for Medical Pulse Wave Rendering

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The Striking Need for Age Diverse Pulse Oximeter Databases

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The quest for raw signals: a quality review of publicly available photoplethysmography datasets

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Few-Shot PPG Signal Generation via Guided Diffusion Models

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Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors

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Photoplethysmography Bio-Signal Extraction for Classifying Diabetes Mellitus Diseases Using Pretrained Deep Learning Networks

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Classification of Photoplethysmography Signals using Ensemble Machine Learning

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Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables

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Deep Learning Model for Blood Pressure Estimation from PPG Signal

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IoT and cloud-based non-invasive diabetes detection system from photoplethysmogram

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A multiwavelength photoplethysmography dataset with blood pressure and heart rate reference measurements

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MIMIC-III-Ext-PPG, a PPG-based Benchmark Dataset for Cardiovascular and Respiratory Signal Analysis

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Available PPG Databases

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A Multi-posture Asymmetry-aware Intelligent Bilateral Observation Dataset for Cardiovascular Monitoring

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