Ultrasensitive wearable strain sensor for promising application in cardiac rehabilitation
Real-time physiological signal monitoring is very essential to evaluate the function recovery,
and the construction of ultrasensitive strain sensor has become the key technique and …
and the construction of ultrasensitive strain sensor has become the key technique and …
Integrated memristor network for physiological signal processing
Humans are complex organisms made by millions of physiological systems. Therefore,
physiological activities can represent physical or mental states of the human body …
physiological activities can represent physical or mental states of the human body …
A systematic review of machine learning and IoT applied to the prediction and monitoring of cardiovascular diseases
A Cuevas-Chavez, Y Hernandez, J Ortiz-Hernandez… - Healthcare, 2023 - mdpi.com
According to the Pan American Health Organization, cardiovascular disease is the leading
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
Feature selection using selective opposition based artificial rabbits optimization for arrhythmia classification on Internet of medical things environment
GS Nijaguna, ND Lal, PB Divakarachari… - IEEE …, 2023 - ieeexplore.ieee.org
An Electrocardiogram (ECG) is a non-invasive test that is broadly utilized for monitoring and
diagnosing the cardiac arrhythmia. An irregularity of the heartbeat is generally defined as …
diagnosing the cardiac arrhythmia. An irregularity of the heartbeat is generally defined as …
Enhancing dynamic ECG heartbeat classification with lightweight transformer model
Arrhythmia is a common class of Cardiovascular disease which is the cause for over 31% of
all death over the world, according to WHOs' report. Automatic detection and classification of …
all death over the world, according to WHOs' report. Automatic detection and classification of …
A federated learning and blockchain framework for physiological signal classification based on continual learning
A key challenge of physiological signal processing in the Internet of Medical Things is that
physiological signals usually have dynamic distribution changes. Another challenge is that …
physiological signals usually have dynamic distribution changes. Another challenge is that …
A scalable and transferable federated learning system for classifying healthcare sensor data
With the development of Internet of Medical Things, massive healthcare sensor data (HSD)
are transmitted in the Internet, which faces various security problems. Healthcare data are …
are transmitted in the Internet, which faces various security problems. Healthcare data are …
IoMT-based smart healthcare detection system driven by quantum blockchain and quantum neural network
Z Qu, W Shi, B Liu, D Gupta… - IEEE journal of biomedical …, 2023 - ieeexplore.ieee.org
Electrocardiogram (ECG) is the main criterion for arrhythmia detection. As a means of
identification, ECG leakage seems to be a common occurrence due to the development of …
identification, ECG leakage seems to be a common occurrence due to the development of …
ECG classification using 1-D convolutional deep residual neural network
An electrocardiograph (ECG) is widely used in diagnosis and prediction of cardiovascular
diseases (CVDs). The traditional ECG classification methods have complex signal …
diseases (CVDs). The traditional ECG classification methods have complex signal …
Deep representation learning with sample generation and augmented attention module for imbalanced ECG classification
Develo** an efficient heartbeat monitoring system has become a focal point in numerous
healthcare applications. Specifically, in the last few years, heartbeat classification for …
healthcare applications. Specifically, in the last few years, heartbeat classification for …