Wireless sensors system for stress detection by means of ECG and EDA acquisition
A Affanni - Sensors, 2020 - mdpi.com
This paper describes the design of a two channels electrodermal activity (EDA) sensor and
two channels electrocardiogram (ECG) sensor. The EDA sensors acquire data on the hands …
two channels electrocardiogram (ECG) sensor. The EDA sensors acquire data on the hands …
[PDF][PDF] Machine learning based congestive heart failure detection using feature importance ranking of multimodal features
In this study, we ranked the Multimodal Features extracted from Congestive Heart Failure
(CHF) and Normal Sinus Rhythm (NSR) subjects. We categorized the ranked features into 1 …
(CHF) and Normal Sinus Rhythm (NSR) subjects. We categorized the ranked features into 1 …
Accurate detection of congestive heart failure using electrocardiomatrix technique
Abstract Congestive Heart Failures (CHFs) are prevalent, expensive, and deadly, causing
damage or overload to the pumping power of the heart muscles. These leads to severe …
damage or overload to the pumping power of the heart muscles. These leads to severe …
Development of a novel wrist pulse system for early diagnosis of pathogenic bacterial infections using optimized feature selection with machine learning approaches
Pelvic inflammatory disease (PID) and urinary tract infections (UTI) are two Pathogenic
bacterial infections. PID affects the female reproductive system, whereas UTI affects the …
bacterial infections. PID affects the female reproductive system, whereas UTI affects the …
A novel phase space reconstruction‐(PSR‐) based predictive algorithm to forecast atmospheric particulate matter concentration
SA Ali Shah, W Aziz, MS Ahmed Nadeem… - Scientific …, 2019 - Wiley Online Library
The prediction of atmospheric particulate matter (APM) concentration is essential to reduce
adverse effects on human health and to enforce emission restrictions. The dynamics of APM …
adverse effects on human health and to enforce emission restrictions. The dynamics of APM …
Multi-weighted symbolic sequence entropy: a novel approach to fault diagnosis and degradation monitoring of rotary machinery
Structural health monitoring relies heavily on measurements. Entropy theory is emerging as
a critical quantitative analysis technique for interpreting measured data for both health …
a critical quantitative analysis technique for interpreting measured data for both health …
Scale based entropy measures and deep learning methods for analyzing the dynamical characteristics of cardiorespiratory control system in COVID-19 subjects …
COVID-19, known as Coronavirus Disease 2019 primarily targets the respiratory system and
can impact the cardiovascular system, leading to a range of cardiorespiratory complications …
can impact the cardiovascular system, leading to a range of cardiorespiratory complications …
Analysing the dynamics of interbeat interval time series using grouped horizontal visibility graph
Horizontal visibility graph (HVG) motifs have been recently introduced to analyze the
dynamical information encoded by biological signals. However, the result of the analysis …
dynamical information encoded by biological signals. However, the result of the analysis …
Multi-scale Poincaré analysis of three-dimensional gas bubble trajectories in liquid
J Augustyniak, DM Perkowski - … Communications in Heat and Mass Transfer, 2025 - Elsevier
This study presents an investigation of the three-dimensional trajectories of gas bubbles in a
liquid medium, utilizing multi-scale Poincaré analysis, Lyapunov exponent and …
liquid medium, utilizing multi-scale Poincaré analysis, Lyapunov exponent and …
A novel time-frequency multilayer network for multivariate time series analysis
Unveiling complex dynamics of natural systems from a multivariate time series represents a
research hotspot in a broad variety of areas. We develop a novel multilayer network analysis …
research hotspot in a broad variety of areas. We develop a novel multilayer network analysis …