Congenital heart disease detection by pediatric electrocardiogram based deep learning integrated with human concepts
Early detection is critical to achieving improved treatment outcomes for child patients with
congenital heart diseases (CHDs). Therefore, developing effective CHD detection …
congenital heart diseases (CHDs). Therefore, developing effective CHD detection …
An efficient compression of ECG signals using deep convolutional autoencoders
Background and objective Advances in information technology have facilitated the retrieval
and processing of biomedical data. Especially with wearable technologies and mobile …
and processing of biomedical data. Especially with wearable technologies and mobile …
Breaking barriers in emerging biomedical applications
The recent global COVID-19 pandemic has revealed that the current healthcare system in
modern society can hardly cope with the increased number of patients. Part of the load can …
modern society can hardly cope with the increased number of patients. Part of the load can …
A comparative analysis of performance of several wavelet based ECG data compression methodologies
Compression of an electrocardiogram (ECG) signal has given much consideration to the
researchers since the computer-aided analysis of ECG has come into being. In some critical …
researchers since the computer-aided analysis of ECG has come into being. In some critical …
[HTML][HTML] An efficient technique for image compression and quality retrieval using matrix completion
In this paper, an efficient technique for image compression and quality retrieval using matrix
completion is presented. The proposed technique is based on low-rank matrix completion …
completion is presented. The proposed technique is based on low-rank matrix completion …
Electrocardiogram signal compression based on singular value decomposition (SVD) and adaptive scanning wavelet difference reduction (ASWDR) technique
In the field of biomedical, it has become necessary to reduce data quantity due to the
limitation of storage in real-time ambulatory system and Tel-e-medicine system. Data …
limitation of storage in real-time ambulatory system and Tel-e-medicine system. Data …
ECG signal compression based on optimization of wavelet parameters and threshold levels using evolutionary techniques
The ECG (electrocardiogram) signals are an indicator of the electrical activity of the heart.
Given its noninvasive nature ECG are an extremely popular medium for heart checkups …
Given its noninvasive nature ECG are an extremely popular medium for heart checkups …
Computationally efficient cosine modulated filter bank design for ECG signal compression
In this work, computationally efficient and reliable cosine modulated filter banks (CMFBs) are
designed for Electrocardiogram (ECG) data compression. First of all, CMFBs (uniform and …
designed for Electrocardiogram (ECG) data compression. First of all, CMFBs (uniform and …
Analysis of Time—Frequency EEG Feature Extraction Methods for Mental Task Classification
C Uyulan, TT Erguzel - International Journal of Computational Intelligence …, 2017 - Springer
Many endogenous and external components may affect the physiological, mental and
behavioral states in humans. Monitoring tools are required to evaluate biomarkers, identify …
behavioral states in humans. Monitoring tools are required to evaluate biomarkers, identify …
Electrocardiogram signal compression using singular coefficient truncation and wavelet coefficient coding
In this study, an inter‐and intra‐beat correlation‐based compression technique for
electrocardiogram (ECG) signal is proposed using singular coefficient truncation, based on …
electrocardiogram (ECG) signal is proposed using singular coefficient truncation, based on …