AIMC Topic: Electrocardiography

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Spectro-Temporal Feature Based Multi-Channel Convolutional Neural Network for ECG Beat Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic classification of abnormal beats in ECG signals is crucial for monitoring cardiac conditions and the performance of the classification will improve the success rate of the treatment. However, under certain circumstances, traditional classif...

RespNet: A deep learning model for extraction of respiration from photoplethysmogram.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Respiratory ailments afflict a wide range of people and manifests itself through conditions like asthma and sleep apnea. Continuous monitoring of chronic respiratory ailments is seldom used outside the intensive care ward due to the large size and co...

Optimizing Probability Threshold of Convolution Neural Network to Improve HRV-based Acute Stress Detection Performance.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
As stress is linked to numerous emotional and physical conditions, its timely detection and proper management is important for our health. Convolution neural network (CNN) has been shown to be promising in stress detection because it could automatica...

Convolutional Neural Network Based Detection of Atrial Fibrillation Combing R-R intervals and F-wave Frequency Spectrum.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial Fibrillation (AF) is one of the arrhythmias that is common and serious in clinic. In this study, a novel method of AF classification with a convolutional neural network (CNN) was proposed, and particularly two cardiac rhythm features of R-R in...

Clustering Continuous Wavelet Transform Characteristics of Heart Rate Variability through Unsupervised Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The analysis and interpretation of physiological signals acquired non-invasively are increasingly important in Smart Health, precision medicine, and medical research. However, this analysis is hampered due to the length, complexity, and inter-subject...

Cardiovascular disease diagnosis using cross-domain transfer learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While cardiovascular diseases (CVDs) are commonly diagnosed by cardiologists via inspecting electrocardiogram (ECG) waveforms, these decisions can be supported by a data-driven approach, which may automate this process. An automatic diagnostic approa...

Real-Time Cognitive Workload Monitoring Based on Machine Learning Using Physiological Signals in Rescue Missions.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
High levels of cognitive workload decreases human's performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly obs...

Biosignal-Based Multimodal Emotion Recognition in a Valence-Arousal Affective Framework Applied to Immersive Video Visualization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Many emotion recognition schemes have been proposed in the state-of-the-art. They generally differ in terms of the emotion elicitation methods, target emotional states to recognize, data sources or modalities, and classification techniques. In this w...

The Feasibility of Arrhythmias Detection from A Capacitive ECG Measurement Using Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Capacitive ECG (cECG) can measure the cardiac electrical signal via capacitive coupling between electrodes and skin. This unconstrained measurement is suitable for personal heart monitoring; however, the instability in the quality of the signal hinde...

ECG Biometric Recognition: Template-Free Approaches Based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Biometric technologies offer much convenience over the conventional approaches to identity recognition, but security and privacy concerns also accompany their applications. In this paper, an electrocardiogram (ECG)-based identification scheme is prop...