Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation
, 2020 The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart's rhythmic irregularities, commonly known as arrhythmias.
Anwar, Syed M. +3 more
core +1 more source
Neuroimaging and psychophysiological investigation of the link between anxiety, enhanced affective reactivity and interoception in people with joint hypermobility [PDF]
, 2014 Objective: Anxiety is associated with increased physiological reactivity and also increased “interoceptive” sensitivity to such changes in internal bodily arousal.
Adolphs +37 more
core +2 more sources
Heart rate monitoring of physical fitness training load based on wavelet transform
The Journal of Engineering, 2022 The detection of fluctuations is a crucial step in the process of isolating heart rate oscillation signals. This is necessary to circumvent the issue wherein a variety of auditory signals will invariably interfere with the collection of centre velocity ...
Feng Zhao +2 more
doaj +1 more source
XML Schema-based Minification for Communication of Security Information and Event Management (SIEM) Systems in Cloud Environments [PDF]
, 2014 XML-based communication governs most of today's systems communication, due to its capability of representing complex structural and hierarchical data.
El-Khouly, Mahmoud +2 more
core +3 more sources
A Real Time and Lossless Encoding Scheme for Patch Electrocardiogram Monitors
Applied Sciences, 2018 Cardiovascular diseases are the leading cause of death worldwide. Due to advancements facilitating the integration of electric and adhesive technologies, long-term patch electrocardiogram (ECG) monitors (PEMs) are currently used to conduct daily ...
Hong-Wen Fang, Chih-Cheng Lu
doaj +1 more source
, 2016 A multiple instance learning (MIL) method, extended Function of Multiple Instances ($e$FUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor.
Jiao, Changzhe +4 more
core +1 more source
Accurate Heartbeat Detection on Ballistocardiogram Accelerometric Traces
IEEE Transactions on Instrumentation and Measurement, 2020 This article presents an automated procedure for acquisition and analysis of BallistoCardioGraphy (BCG) traces. A triaxial accelerometer and a microcontroller unit are used to record heart-induced recoil forces generated from a lying subject. The problem of BCG J-peak annotation is split into two subtasks: candidates extraction, based on a detection ...
Niccolò Mora +3 more
openaire +3 more sources
Touch-less Heartbeat Detection and Measurement-based Cardiopulmonary Modeling [PDF]
, 2010 ISBN: 978-1-4244-4124-2 - WOSInternational audienceThis paper presents a system for touch-less heartbeat detection and a cardiopulmonary signal modeling approach.
El Zein, Ghais +3 more
core +3 more sources
Heartbeat design for energy-aware IoT:are your sensors alive? [PDF]
, 2019 A number of algorithms now exist for using model-based prediction at the sensor node of a wireless sensor network (WSN) to enable a dramatic reduction in transmission rates, and thus save energy at the sensor node.
Brusey, James +3 more
core +1 more source
IEEE Access, 2023 This paper presents the behavioral modeling of three circuit architectures, which are suitable for heartbeat detection in wireless healthcare applications.
Rafael Vieira +4 more
doaj +1 more source