ECG databases for biometric systems: A systematic review
Computer-based biometric systems (CBBSs) individual recognition are expert and intelligent
systems that are gaining increasing interest in many areas, such as securing financial …
systems that are gaining increasing interest in many areas, such as securing financial …
Arrhythmia detection and classification using ECG and PPG techniques: A review
Electrocardiogram (ECG) and photoplethysmograph (PPG) are non-invasive techniques that
provide electrical and hemodynamic information of the heart, respectively. This information …
provide electrical and hemodynamic information of the heart, respectively. This information …
A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation
Background Cardiologs® has developed the first electrocardiogram (ECG) algorithm that
uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and …
uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and …
Signal quality and data fusion for false alarm reduction in the intensive care unit
Q Li, GD Clifford - Journal of electrocardiology, 2012 - Elsevier
Due to a lack of integration between different sensors, false alarms (FA) in the intensive care
unit (ICU) are frequent and can lead to reduced standard of care. We present a novel …
unit (ICU) are frequent and can lead to reduced standard of care. We present a novel …
Length of stay prediction for ICU patients using individualized single classification algorithm
Abstract Background and Objective: In intensive care units (ICUs), length of stay (LOS)
prediction is critical to help doctors and nurses select appropriate treatment options and …
prediction is critical to help doctors and nurses select appropriate treatment options and …
Reduction of false arrhythmia alarms using signal selection and machine learning
LM Eerikäinen, J Vanschoren… - Physiological …, 2016 - iopscience.iop.org
In this paper, we propose an algorithm that classifies whether a generated cardiac
arrhythmia alarm is true or false. The large number of false alarms in intensive care is a …
arrhythmia alarm is true or false. The large number of false alarms in intensive care is a …
Electrocardiogram pattern recognition and analysis based on artificial neural networks and support vector machines: a review
Computer systems for Electrocardiogram (ECG) analysis support the clinician in tedious
tasks (eg, Holter ECG monitored in Intensive Care Units) or in prompt detection of …
tasks (eg, Holter ECG monitored in Intensive Care Units) or in prompt detection of …
Real‐time arrhythmia detection using hybrid convolutional neural networks
SC Bollepalli, RK Sevakula… - Journal of the …, 2021 - Am Heart Assoc
Background Accurate detection of arrhythmic events in the intensive care units (ICU) is of
paramount significance in providing timely care. However, traditional ICU monitors generate …
paramount significance in providing timely care. However, traditional ICU monitors generate …
Dynamic time warping based arrhythmia detection using photoplethysmography signals
Photoplethysmography (PPG) based methods have gained popularity in recent times for
arrhythmia detection. However, limited research has been carried out for multiple arrhythmia …
arrhythmia detection. However, limited research has been carried out for multiple arrhythmia …
Life threatening arrhythmias: Knowledge and skills among nurses working in critical care settings at Muhimbili National Hospital, Dar es Salaam, Tanzania
DI Ruhwanya, EAM Tarimo, M Ndile - Tanzania Journal of Health Research, 2018 - ajol.info
Introduction: A life threatening arrhythmia is a medical condition that requires immediate
intervention, or it can cost a patient's life. However, there is limited understanding of nurses' …
intervention, or it can cost a patient's life. However, there is limited understanding of nurses' …