Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

The success of deep learning over the traditional machine learning techniques in handling
artificial intelligence application tasks such as image processing, computer vision, object …

With the development of the Augmented and Virtual Reality (AR/VR) technologies, massive
biometric data are collected by different organizations. These data have great significance …

In this work, a nonfiducial electrocardiogram (ECG) identification algorithm based on
statistical features and random forest classifier is presented. Two feature extraction …

The respiration status of a person is one of the vital signs that can be used to check the
health condition of the person. The respiration status has been measured in various ways in …

In this article, a convolutional neural network (CNN) enhanced radio frequency fingerprinting
(RFF) authentication scheme is presented for Internet of things (IoT). RFF is a non …

With the advent of various security attacks, biometric authentication methods are gaining
momentum in the security literature. Electrocardiogram or ECG signals are one of the …

目的针对用于无扰睡姿检测的心冲击图(Ballistocardiogram, BCG) 信号特征微弱,
并且具有非线性, 非平稳性强, 存在噪声干扰以及信号本身具有空间和时域信息的特点 …

Electrocardiogram (ECG) has become a popular biometric to study since it is highly secured
against spoofing attack. In this study, we address the issues of hard-required ECG data and …

Artificial Intelligence (AI) has found its applications in a variety of environments ranging from
data science to cybersecurity. AI helps break through the limitations of traditional algorithms …