AIMC Topic: Neural Networks, Computer

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Automatic Sleep Stage Classification using Marginal Hilbert Spectrum Features and a 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
In this paper, we propose a novel method of automatic sleep stage classification based on single-channel electroencephalography (EEG). First, we use marginal Hilbert spectrum (MHS) to depict time-frequency domain features of five sleep stages of 30-s...

Arrhythmias Classification Using Short-Time Fourier Transform and GAN Based Data Augmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Lacking sufficient training samples of different heart rhythms is a common bottleneck to obtain arrhythmias classification models with high accuracy using artificial neural networks. To solve this problem, we propose a novel data augmentation method ...

High Accuracy Respiration and Heart Rate Detection Based on Artificial Neural Network Regression.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A 24GHz Doppler radar system for accurate contactless monitoring of heart and respiratory rates is demonstrated here. High accuracy predictions are achieved by employing a CNN+LSTM neural network architecture for regression analysis. Detection accura...

Neural Network-based Classification of Static Lung Volume States using Vibrational Cardiography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
UNLABELLED: Non-invasive health monitoring has the potential to improve the delivery and efficiency of medical treatment.

Attention Networks for Multi-Task Signal Analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent advances in deep learning have enabled the development of automated frameworks for analysing medical images and signals. For analysis of physiological recordings, models based on temporal convolutional networks and recurrent neural networks ha...

Optimal Scree-CNN for Detecting NS1 Molecular Fingerprint from Salivary SERS Spectra.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Dengue fever (DF) is a viral infection with possible fatal consequence. NS1 is a recent antigen based biomarker for dengue fever (DF), as an alternative to current serum and antibody based biomarkers. Convolutional Neural Network (CNN) has demonstrat...

Robust Deep Learning Framework For Predicting Respiratory Anomalies and Diseases.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a robust deep learning framework developed to detect respiratory diseases from recordings of respiratory sounds. The complete detection process firstly involves front end feature extraction where recordings are transformed into sp...

Emergency Clinical Procedure Detection With Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Information about a patient's state is critical for hospitals to provide timely care and treatment. Prior work on improving the information flow from emergency medical services (EMS) to hospitals demonstrated the potential of using automated algorith...

Automatic Detection of Respiratory Effort Related Arousals With Deep Neural Networks From Polysomnographic Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sleep disorders have become more common due to the modern lifestyle and stress. The most severe case of sleep disorders called apnea is characterized by a complete breaking block, leading to awakening and subsequent sleep disturbances. The automatic ...

Predicting Age with Deep Neural Networks from Polysomnograms.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The aim of this study was to design a new deep learning framework for end-to-end processing of polysomnograms. This framework can be trained to analyze whole-night polysomnograms without the limitations of and bias towards clinical scoring guidelines...