AI Medical Compendium Topic:
Heart Rate

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An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

Bio-medical materials and engineering
In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid t...

Detection of mental stress due to oral academic examination via ultra-short-term HRV analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. Mental stress detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minu...

Monitoring and detecting atrial fibrillation using wearable technology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial fibrillation (AFib) is diagnosed by analysis of the morphological and rhythmic properties of the electrocardiogram. It was recently shown that accurate detection of AFib is possible using beat-to-beat interval variations. This raises the quest...

Sensor data quality processing for vital signs with opportunistic ambient sensing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Opportunistic ambient sensing involves placement of sensors appropriately so that intermittent contact can be made unobtrusively for gathering physiological signals for vital signs. In this paper, we discuss the results of our quality processing syst...

Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat "concept" fo...

An unsupervised learning for robust cardiac feature derivation from PPG signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We propose here derivation algorithms for physiological parameters like beat start point, systolic peak, pulse duration, peak-to-peak distance related to heart rate, dicrotic minima, diastolic peak from Photoplethysmogram (PPG) signals robustly. Our ...

Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

Critical care medicine
OBJECTIVE: The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability.

[Study on Sleep Staging Methods Based on Heart Rate Variability Analysis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In order to realize sleep staging automatically and conveniently,we used support vector machine(SVM)to analyze the correlation between heart rate variability and sleep stage experimentally.R-R intervals(RRIs)from 33 cases of sleep clinical data of Ti...

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

Pakistan journal of pharmaceutical sciences
Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each elect...