Early chatter identification based on an optimized variational mode decomposition
K Yang, G Wang, Y Dong, Q Zhang, L Sang - Mechanical Systems and …, 2019 - Elsevier
In the milling process, chatter, which results in poor surface quality, dimensional errors, and
reduced cutter and machine life, is one of the main limitations on performance …
reduced cutter and machine life, is one of the main limitations on performance …
Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia
Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-
of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning …
of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning …
A new kind of permutation entropy used to classify sleep stages from invisible EEG microstructure
C Bandt - Entropy, 2017 - mdpi.com
Permutation entropy and order patterns in an EEG signal have been applied by several
authors to study sleep, anesthesia, and epileptic absences. Here, we discuss a new version …
authors to study sleep, anesthesia, and epileptic absences. Here, we discuss a new version …
Fuzzy entropy metrics for the analysis of biomedical signals: Assessment and comparison
Fuzzy entropy (FuzEn) was introduced to alleviate limitations associated with sample
entropy (SampEn) in the analysis of physiological signals. Over the past decade, FuzEn …
entropy (SampEn) in the analysis of physiological signals. Over the past decade, FuzEn …
Ventricular fibrillation waveform analysis during chest compressions to predict survival from cardiac arrest
Background: Quantitative measures of the ventricular fibrillation (VF) ECG waveform can
assess myocardial physiology and predict cardiac arrest outcomes, making these measures …
assess myocardial physiology and predict cardiac arrest outcomes, making these measures …
ECG-based pulse detection during cardiac arrest using random forest classifier
Sudden cardiac arrest is one of the leading causes of death in the industrialized world.
Pulse detection is essential for the recognition of the arrest and the recognition of return of …
Pulse detection is essential for the recognition of the arrest and the recognition of return of …
Heart rate variability feature selection method for automated prediction of sudden cardiac death
Sudden cardiac death is often caused by a major heart dysfunction with approximately 80%
of occurrences attributed to ventricular arrhythmias. This paper proposes a novel ventricular …
of occurrences attributed to ventricular arrhythmias. This paper proposes a novel ventricular …
A machine learning shock decision algorithm for use during piston-driven chest compressions
Goal: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation
(CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The …
(CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The …
Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques
This survey paper explores the transformative role of Machine Learning (ML) and Artificial
Intelligence (AI) in Cardiopulmonary Resuscitation (CPR). It examines the evolution from …
Intelligence (AI) in Cardiopulmonary Resuscitation (CPR). It examines the evolution from …
Order patterns, their variation and change points in financial time series and Brownian motion
C Bandt - Statistical Papers, 2020 - Springer
Order patterns and permutation entropy have become useful tools for studying biomedical,
geophysical or climate time series. Here we study day-to-day market data, and Brownian …
geophysical or climate time series. Here we study day-to-day market data, and Brownian …