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An efficient optimized feature selection with machine learning approach for ECG biometric recognition
In machine learning, an efficient classifier model design is mostly based on effective feature
extraction and appropriate feature selection. This work mainly focused on different optimized …
extraction and appropriate feature selection. This work mainly focused on different optimized …
ECG data optimization for biometric human recognition using statistical distributed machine learning algorithm
KK Patro, SPR Reddi, SKE Khalelulla… - The Journal of …, 2020 - Springer
Currently, security plays a crucial role in military, forensic and other industry applications.
Traditional biometric authentication methods such as fingerprint, voice, face, iris and …
Traditional biometric authentication methods such as fingerprint, voice, face, iris and …
Effective feature extraction of ECG for biometric application
Biometric systems performing identity recognition based upon extracted informative data
from an individual are vital for security applications. The vital characteristics of an ECG …
from an individual are vital for security applications. The vital characteristics of an ECG …
Performance evaluation of plain weave and honeycomb weave electrodes for human ECG monitoring
Long‐time monitoring of physiological parameters can scrutinize human health conditions
so as to use electrocardiogram (ECG) for diagnosis of some human's chronic cardiovascular …
so as to use electrocardiogram (ECG) for diagnosis of some human's chronic cardiovascular …
[PDF][PDF] Machine learning classification approaches for biometric recognition system using ECG signals.
Person identification is an essential task in defense and forensic applications such as
surveillance and criminal investigation activities. Studies conducted in the past included …
surveillance and criminal investigation activities. Studies conducted in the past included …
Reconfigurable architecture for multi-lead ECG signal compression with high-frequency noise reduction
Electrocardiogram (ECG) is a record of the heart's electrical activity over a specified period,
and it is the most popular noninvasive diagnostic test to identify several cardiac diseases. It …
and it is the most popular noninvasive diagnostic test to identify several cardiac diseases. It …
Ecg analysis: A brief review
In recent years, cardiac problems have been found proportional to technology development.
As the cardiac signal (Electrocardiogram) relates to the electrical activity of the heart of a …
As the cardiac signal (Electrocardiogram) relates to the electrical activity of the heart of a …
A comparative study of fuzzy vault based security methods for wirless body sensor networks
Wireless Body Sensor Networks (WBSNs) are widely used for healthcare monitoring
applications. Owing to the significance of confidentiality and security, the transmissions of …
applications. Owing to the significance of confidentiality and security, the transmissions of …
A new method for denoising ECG signal using sharp cut-off FIR filter
An electrocardiogram (ECG) is a graphical interface that shows its implication for the
diagnosis of various cardiac problems by recording the electrical activity of heart with …
diagnosis of various cardiac problems by recording the electrical activity of heart with …
ECG-based heartbeat classification for arrhythmia detection using artificial neural networks
Cardiovascular disease (CVD) has quickly grown in prevalence over the previous decade,
becoming the major cause of human morbidity on a global scale. Due to the massive …
becoming the major cause of human morbidity on a global scale. Due to the massive …