Robustness of electrocardiogram signal quality indices
S Rahman, C Karmakar… - Journal of the …, 2022 - royalsocietypublishing.org
Electrocardiogram (ECG) signal quality indices (SQIs) are essential for improving diagnostic
accuracy and reliability of ECG analysis systems. In various practical applications, the ECG …
accuracy and reliability of ECG analysis systems. In various practical applications, the ECG …
Golden standard or obsolete method? Review of ECG applications in clinical and experimental context
T Stracina, M Ronzhina, R Redina… - Frontiers in …, 2022 - frontiersin.org
Cardiovascular system and its functions under both physiological and pathophysiological
conditions have been studied for centuries. One of the most important steps in the …
conditions have been studied for centuries. One of the most important steps in the …
[HTML][HTML] FLIRT: A feature generation toolkit for wearable data
Abstract Background and Objective: Researchers use wearable sensing data and machine
learning (ML) models to predict various health and behavioral outcomes. However, sensor …
learning (ML) models to predict various health and behavioral outcomes. However, sensor …
A deformable CNN architecture for predicting clinical acceptability of ECG signal
The degraded quality of the electrocardiogram (ECG) signals is the main source of false
alarms in critical care units. Therefore, a preliminary analysis of the ECG signal is required to …
alarms in critical care units. Therefore, a preliminary analysis of the ECG signal is required to …
A multimodal data fusion technique for heartbeat detection in wearable IoT sensors
The accurate detection of heartbeats is of paramount importance in the current healthcare
scenario as they act as an indicator for various underlying cardiac conditions and provides …
scenario as they act as an indicator for various underlying cardiac conditions and provides …
Signal quality analysis for long-term ECG monitoring using a health patch in cardiac patients
Cardiovascular diseases (CVD) represent a serious health problem worldwide, of which
atrial fibrillation (AF) is one of the most common conditions. Early and timely diagnosis of …
atrial fibrillation (AF) is one of the most common conditions. Early and timely diagnosis of …
Hybrid feature fusion for classification optimization of short ECG segment in IoT based intelligent healthcare system
With more than 50 million people worldwide at risk of heart disease, early diagnosis of
cardiovascular disease is essential. The classification of electrocardiogram (ECG) …
cardiovascular disease is essential. The classification of electrocardiogram (ECG) …
ELEKTRA: ELEKTRokardiomatrix application to biometric identification with convolutional neural networks
Biometric systems are an uprising technique of identification in today's world. Many different
systems have been used in everyone's daily life in the past years, such as fingerprint, face …
systems have been used in everyone's daily life in the past years, such as fingerprint, face …
Conductive Elastic Composite Electrode and Its Application in Electrocardiogram Monitoring Clothing
Wearable monitoring devices help achieve a long-term signal monitoring of the human
body, which is important for human health analyses. Silver–silver chloride electrodes used …
body, which is important for human health analyses. Silver–silver chloride electrodes used …
An arrhythmia classification algorithm using C-LSTM in physiological parameters monitoring system under internet of health things environment
W Lu, J Jiang, L Ma, H Chen, H Wu, M Gong… - Journal of Ambient …, 2021 - Springer
In order to solve the problem that the traditional convolution neural network-based
arrhythmia classification model does not extract the time series feature deeply, and ECG is a …
arrhythmia classification model does not extract the time series feature deeply, and ECG is a …