AIMC Topic: Photoplethysmography

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Analysis of short-term heart rate and diastolic period variability using a refined fuzzy entropy method.

Biomedical engineering online Jul 1, 2015
BACKGROUND: Heart rate variability (HRV) has been widely used in the non-invasive evaluation of cardiovascular function. Recent studies have also attached great importance to the cardiac diastolic period variability (DPV) examination. Short-term vari...
Heart Rate Nonlinear Dynamics Signal-To-Noise Ratio Statistics, Nonparametric Stochastic Processes Normal Distribution Entropy Diastole Middle Aged Photoplethysmography Electrocardiography Humans Fuzzy Logic Aged Algorithms Adult Computer Simulation Male Female Models, Cardiovascular Coronary Stenosis Periodicity
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Deep generative models for physiological signals: A systematic literature review.

Artificial intelligence in medicine Jul 1, 2025
In this paper, we present a systematic literature review on deep generative models for physiological signals, particularly electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG) and electromyogram (EMG). Compared to the existin...
Electrocardiography Electroencephalography Signal Processing, Computer-Assisted Electromyography Humans Deep Learning Photoplethysmography
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Predicting blood pressure without a cuff using a unique multi-modal wearable device and machine learning algorithm.

Computers in biology and medicine Jun 1, 2025
Blood pressure is a critical risk factor for cardiovascular diseases (CVDs), yet most adults do not monitor it frequently enough to prevent serious complications. This is in part because the traditional cuff-based method is inconvenient, uncomfortabl...
Humans Machine Learning Algorithms Female Blood Pressure Determination Blood Pressure Pulse Wave Analysis Signal Processing, Computer-Assisted Adult Male Wearable Electronic Devices Photoplethysmography
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A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG.

Computer methods and programs in biomedicine Jun 1, 2025
BACKGROUND AND OBJECTIVE: The aim of this study is to extract a patient-specific viscosity equation from photoplethysmography (PPG) data. An aging society has increased the need for remote, non-invasive health monitoring systems. However, the circula...
Algorithms Deep Learning Wearable Electronic Devices Photoplethysmography Signal Processing, Computer-Assisted Blood Viscosity Humans Neural Networks, Computer
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Investigating the correlation between smoking and blood pressure via photoplethysmography.

Biomedical engineering online May 12, 2025
Smoking has been widely identified for its detrimental effects on human health, particularly on the cardiovascular health. The prediction of these effects can be anticipated by monitoring the dynamic changes in vital signs and other physiological sig...
Electrocardiography Blood Pressure Young Adult Signal Processing, Computer-Assisted Humans Adult Smoking Heart Rate Male Machine Learning Photoplethysmography Female
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Validation of a fingertip home sleep apnea testing system using deep learning AI and a temporal event localization analysis.

Sleep May 12, 2025
STUDY OBJECTIVES: This paper validates TipTraQ, a compact home sleep apnea testing (HSAT) system. TipTraQ comprises a fingertip-worn device, a mobile application, and a cloud-based deep learning artificial intelligence (AI) system. The device utilize...
Middle Aged Deep Learning Mobile Applications Photoplethysmography Sleep Apnea Syndromes Humans Reproducibility of Results Sleep Apnea, Obstructive Prospective Studies Adult Accelerometry Female Male Polysomnography
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A Neural Network for Atrial Fibrillation Detection via PPG.

Studies in health technology and informatics Apr 24, 2025
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with severe complications such as ischemic stroke and heart failure. Early detection is essential for timely intervention; however, traditional diagnostic methods often lack scalab...
Smartphone Mobile Applications Photoplethysmography Atrial Fibrillation Humans Neural Networks, Computer Sensitivity and Specificity Male
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External validation of a machine learning-based classification algorithm for ambulatory heart rhythm diagnostics in pericardioversion atrial fibrillation patients using smartphone photoplethysmography: the SMARTBEATS-ALGO study.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Mar 28, 2025
AIMS: The aim of this study was to perform an external validation of an automatic machine learning (ML) algorithm for heart rhythm diagnostics using smartphone photoplethysmography (PPG) recorded by patients with atrial fibrillation (AF) and atrial f...
Aged Male Middle Aged Smartphone Algorithms Female Reproducibility of Results Predictive Value of Tests Signal Processing, Computer-Assisted Electrocardiography, Ambulatory Atrial Fibrillation Mobile Applications Photoplethysmography Electrocardiography Support Vector Machine Humans Classification Algorithms Machine Learning Heart Rate Electric Countershock Atrial Flutter
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[A review of deep learning methods for non-contact heart rate measurement based on facial videos].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2025
Heart rate is a crucial indicator of human health with significant physiological importance. Traditional contact methods for measuring heart rate, such as electrocardiograph or wristbands, may not always meet the need for convenient health monitoring...
Video Recording Face Monitoring, Physiologic Signal Processing, Computer-Assisted Heart Rate Humans Deep Learning Photoplethysmography
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[Application of Photoplethysmography Combined with Deep Learning in Postoperative Monitoring of Flaps].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Jul 30, 2024
OBJECTIVE: Photoelectric volumetric tracing (PPG) exhibits high sensitivity and specificity in flap monitoring. Deep learning (DL) is capable of automatically and robustly extracting features from raw data. In this study, we propose combining PPG wit...
Neural Networks, Computer Monitoring, Physiologic Embolism Animals Rabbits Deep Learning Postoperative Period Photoplethysmography Surgical Flaps
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