AIMC Topic: Photoplethysmography
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Variability of morphology in photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment.
Physiological measurement
Sep 16, 2024
We investigated fluctuations of the photoplethysmography (PPG) waveform in patients undergoing surgery. There is an association between the morphologic variation extracted from arterial blood pressure (ABP) signals and short-term surgical outcomes. T...
Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.
Journal of clinical monitoring and computing
Aug 19, 2024
PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive...
Databases, Factual
Female
Reproducibility of Results
Aged
Humans
Artificial Intelligence
Algorithms
Deep Learning
Monitoring, Intraoperative
ROC Curve
Photoplethysmography
Adult
Male
Middle Aged
Blood Pressure Monitors
Capnography
Area Under Curve
Hypotension
Electrocardiography
Intraoperative Complications
Blood Pressure Determination
Consciousness Monitors
Blood Pressure
ST-Phys: Unsupervised Spatio-Temporal Contrastive Remote Physiological Measurement.
IEEE journal of biomedical and health informatics
Aug 6, 2024
Remote photoplethysmography (rPPG) is a non-contact method that employs facial videos for measuring physiological parameters. Existing rPPG methods have achieved remarkable performance. However, the success mainly profits from supervised learning ove...
Compressed Deep Learning Models for Wearable Atrial Fibrillation Detection through Attention.
Sensors (Basel, Switzerland)
Jul 24, 2024
Deep learning (DL) models have shown promise for the accurate detection of atrial fibrillation (AF) from electrocardiogram/photoplethysmography (ECG/PPG) data, yet deploying these on resource-constrained wearable devices remains challenging. This stu...
Improved sleep stage predictions by deep learning of photoplethysmogram and respiration patterns.
Computers in biology and medicine
Jul 20, 2024
Sleep staging is a crucial tool for diagnosing and monitoring sleep disorders, but the standard clinical approach using polysomnography (PSG) in a sleep lab is time-consuming, expensive, uncomfortable, and limited to a single night. Advancements in s...
Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities.
Scientific reports
Jul 12, 2024
The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and bio...
DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model.
Medical & biological engineering & computing
Jul 4, 2024
Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introd...
Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise.
Sensors (Basel, Switzerland)
Jun 28, 2024
(1) Background: The objective of this study was to predict the vascular health status of elderly women during exercise using pulse wave data and Temporal Convolutional Neural Networks (TCN); (2) Methods: A total of 492 healthy elderly women aged 60-7...
High-accuracy heart rate detection using multispectral IPPG technology combined with a deep learning algorithm.
Journal of biophotonics
Jun 27, 2024
Image Photoplethysmography (IPPG) technology is a noncontact physiological parameter detection technology, which has been widely used in heart rate (HR) detection. However, traditional imaging devices still have issues such as narrower receiving spec...
Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks.
Sensors (Basel, Switzerland)
Jun 19, 2024
Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pres...
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