AIMC Topic: Photoplethysmography

Clear Filters Showing 141 to 150 of 196 articles

A Supervised Approach to Robust Photoplethysmography Quality Assessment.

IEEE journal of biomedical and health informatics
Early detection of Atrial Fibrillation (AFib) is crucial to prevent stroke recurrence. New tools for monitoring cardiac rhythm are important for risk stratification and stroke prevention. As many of new approaches to long-term AFib detection are now ...

A Deep Neural Network-Based Pain Classifier Using a Photoplethysmography Signal.

Sensors (Basel, Switzerland)
Side effects occur when excessive or low doses of analgesics are administered compared to the required amount to mediate the pain induced during surgery. It is important to accurately assess the pain level of the patient during surgery. We proposed a...

CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment.

IEEE transactions on biomedical circuits and systems
Advancements in wireless sensor network technologies have enabled the proliferation of miniaturized body-worn sensors, capable of long-term pervasive biomedical signal monitoring. Remote cardiovascular monitoring has been one of the beneficiaries of ...

Bidirectional Recurrent Auto-Encoder for Photoplethysmogram Denoising.

IEEE journal of biomedical and health informatics
Photoplethysmography (PPG) has become ubiquitous with the development of smart watches and the mobile healthcare market. However, PPG is vulnerable to various types of noises that are ever present in uncontrolled environments, and the key to obtainin...

Arterial stiffness in normal pregnancy as assessed by digital pulse wave analysis by photoplethysmography - A longitudinal study.

Pregnancy hypertension
INTRODUCTION: It might in the future be valuable to screen for increased maternal arterial stiffness, i.e. low compliance, since it is associated with development of hypertensive complications in pregnancy. Digital pulse wave analysis (DPA) is an eas...

Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification.

Biosensors
Blood pressure is a basic physiological parameter in the cardiovascular circulatory system. Long-term abnormal blood pressure will lead to various cardiovascular diseases, making the early detection and assessment of hypertension profoundly significa...

Blood Pressure Estimation Using Photoplethysmography Only: Comparison between Different Machine Learning Approaches.

Journal of healthcare engineering
INTRODUCTION: Blood pressure (BP) has been a potential risk factor for cardiovascular diseases. BP measurement is one of the most useful parameters for early diagnosis, prevention, and treatment of cardiovascular diseases. At present, BP measurement ...

A Wearable Multi-Modal Bio-Sensing System Towards Real-World Applications.

IEEE transactions on bio-medical engineering
Multi-modal bio-sensing has recently been used as effective research tools in affective computing, autism, clinical disorders, and virtual reality among other areas. However, none of the existing bio-sensing systems support multi-modality in a wearab...

Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor.

Sensors (Basel, Switzerland)
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for ...