AI Medical Compendium Journal:
Physiological measurement

Showing 71 to 80 of 122 articles

Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

Physiological measurement
UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospi...

A dictionary learning approach for spatio-temporal characterization of absence seizures.

Physiological measurement
OBJECTIVE: This research explores absence seizures using data recorded from different layers of somatosensory cortex of four genetic absence epilepsy rats from Strasbourg (GAERS). Localizing the active layers of somatosensory cortex (spatial analysis...

Heart sound classification using the SNMFNet classifier.

Physiological measurement
OBJECTIVE: Heart sound classification still suffers from the challenges involved in achieving high accuracy in the case of small samples. Dimension reduction attempts to extract low-dimensional features with more discriminability from high-dimensiona...

A strategy combining intrinsic time-scale decomposition and a feedforward neural network for automatic seizure detection.

Physiological measurement
UNLABELLED: Epilepsy is a common neurological disorder which can occur in people of all ages globally. For the clinical treatment of epileptic patients, the detection of epileptic seizures is of great significance.

SleepNet: automated sleep analysis via dense convolutional neural network using physiological time series.

Physiological measurement
OBJECTIVE: In this work, a dense recurrent convolutional neural network (DRCNN) was constructed to detect sleep disorders including arousal, apnea and hypopnea using polysomnography (PSG) measurement channels provided in the 2018 PhysioNet Challenge ...

Hybrid scattering-LSTM networks for automated detection of sleep arousals.

Physiological measurement
OBJECTIVE: Early detection of sleep arousal in polysomnographic (PSG) signals is crucial for monitoring or diagnosing sleep disorders and reducing the risk of further complications, including heart disease and blood pressure fluctuations.

Beltrami-net: domain-independent deep D-bar learning for absolute imaging with electrical impedance tomography (a-EIT).

Physiological measurement
OBJECTIVE: To develop, and demonstrate the feasibility of, a novel image reconstruction method for absolute electrical impedance tomography (a-EIT) that pairs deep learning techniques with real-time robust D-bar methods and examine the influence of p...

Automatic evaluation of fetal head biometry from ultrasound images using machine learning.

Physiological measurement
OBJECTIVE: Ultrasound-based fetal biometric measurements, such as head circumference (HC) and biparietal diameter (BPD), are frequently used to evaluate gestational age and diagnose fetal central nervous system pathology. Because manual measurements ...

Ventricular ectopic beat detection using a wavelet transform and a convolutional neural network.

Physiological measurement
OBJECTIVE: Ventricular contractions in healthy individuals normally follow the contractions of atria to facilitate more efficient pump action and cardiac output. With a ventricular ectopic beat (VEB), volume within the ventricles are pumped to the bo...

Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings.

Physiological measurement
OBJECTIVE: We aim to combine deep neural networks and engineered features (hand-crafted features based on medical domain knowledge) for cardiac arrhythmia detection from short single-lead ECG recordings.