AIMC Topic: Signal Processing, Computer-Assisted

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Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram.

Physiological measurement
OBJECTIVE: This study classifies sleep stages from a single lead electrocardiogram (ECG) using beat detection, cardiorespiratory coupling in the time-frequency domain and a deep convolutional neural network (CNN).

A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features.

IEEE transactions on bio-medical engineering
UNLABELLED: Cough is a protective reflex conveying information on the state of the respiratory system. Cough assessment has been limited so far to subjective measurement tools or uncomfortable (i.e., non-wearable) cough monitors. This limits the pote...

Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types.

Computers in biology and medicine
Abnormality of the cardiac conduction system can induce arrhythmia - abnormal heart rhythm - that can frequently lead to other cardiac diseases and complications, and are sometimes life-threatening. These conduction system perturbations can manifest ...

Classification of needle-EMG resting potentials by machine learning.

Muscle & nerve
INTRODUCTION: The diagnostic importance of audio signal characteristics in needle electromyography (EMG) is well established. Given the recent advent of audio-sound identification by artificial intelligence, we hypothesized that the extraction of cha...

Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Arterial oxygen saturation ([Formula: see text]) is an indicator of how much oxygen is carried by hemoglobin in the blood. Having enough oxygen is vital for the functioning of cells in the human body. Measurement of [Formula: see text] is typically e...

Distributed Repetitive Learning Control for Cooperative Cadence Tracking in Functional Electrical Stimulation Cycling.

IEEE transactions on cybernetics
Closed-loop control of functional electrical stimulation coupled with motorized assistance to induce cycling is a rehabilitative strategy that can improve the mobility of people with neurological conditions (NCs). However, robust control methods, whi...

Automated Sleep Apnea Detection in Raw Respiratory Signals Using Long Short-Term Memory Neural Networks.

IEEE journal of biomedical and health informatics
Sleep apnea is one of the most common sleep disorders and the consequences of undiagnosed sleep apnea can be very severe, ranging from increased blood pressure to heart failure. However, many people are often unaware of their condition. The gold stan...

Automatic seizure detection using three-dimensional CNN based on multi-channel EEG.

BMC medical informatics and decision making
BACKGROUND: Automated seizure detection from clinical EEG data can reduce the diagnosis time and facilitate targeting treatment for epileptic patients. However, current detection approaches mainly rely on limited features manually designed by domain ...

A robust and subject-specific sequential forward search method for effective channel selection in brain computer interfaces.

Journal of neuroscience methods
BACKGROUND: The input signals of electroencephalography (EEG) based brain computer interfaces (BCI) are extensively acquired from scalp with a multi-channel system. However, multi-channel signals might contain redundant information and increase compu...

Bidirectional Recurrent Auto-Encoder for Photoplethysmogram Denoising.

IEEE journal of biomedical and health informatics
Photoplethysmography (PPG) has become ubiquitous with the development of smart watches and the mobile healthcare market. However, PPG is vulnerable to various types of noises that are ever present in uncontrolled environments, and the key to obtainin...