AIMC Topic: Photoplethysmography
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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...
Estimation of invasive coronary perfusion pressure using electrocardiogram and Photoplethysmography in a porcine model of cardiac arrest.
Computer methods and programs in biomedicine
Jun 13, 2024
BACKGROUND: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is recommended for high-quality cardiopulmonary resuscitation (CPR). This study aimed to investigate a method for non-invasive estimation of CPP using elect...
Development of a Personalized Multiclass Classification Model to Detect Blood Pressure Variations Associated with Physical or Cognitive Workload.
Sensors (Basel, Switzerland)
Jun 6, 2024
Comprehending the regulatory mechanisms influencing blood pressure control is pivotal for continuous monitoring of this parameter. Implementing a personalized machine learning model, utilizing data-driven features, presents an opportunity to facilita...
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