AI Medical Compendium Topic

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Signal Processing, Computer-Assisted

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Application of Convolutional Neural Network for Decoding of 12-Lead Electrocardiogram from a Frequency-Modulated Audio Stream (Sonified ECG).

Sensors (Basel, Switzerland)
Research of novel biosignal modalities with application to remote patient monitoring is a subject of state-of-the-art developments. This study is focused on sonified ECG modality, which can be transmitted as an acoustic wave and received by GSM (Glob...

Feasibility and validity of using deep learning to reconstruct 12-lead ECG from three‑lead signals.

Journal of electrocardiology
BACKGROUND: In the field of mobile health, portable dynamic electrocardiogram (ECG) monitoring devices often have a limited number of lead electrodes due to considerations, such as portability and battery life. This situation leads to a contradiction...

Fast reconstruction of EEG signal compression sensing based on deep learning.

Scientific reports
When traditional EEG signals are collected based on the Nyquist theorem, long-time recordings of EEG signals will produce a large amount of data. At the same time, limited bandwidth, end-to-end delay, and memory space will bring great pressure on the...

12-Lead ECG Reconstruction Based on Data From the First Limb Lead.

Cardiovascular engineering and technology
PURPOSE: Electrocardiogram (ECG) data obtained from 12 leads are the most common and informative source for analyzing the cardiovascular system's (CVS) condition in medical practice. However, the large number of electrodes, specific placements on the...

Optimized FFNN with multichannel CSP-ICA framework of EEG signal for BCI.

Computer methods in biomechanics and biomedical engineering
The electroencephalogram (EEG) of the patient is used to identify their motor intention, which is then converted into a control signal through a brain-computer interface (BCI) based on motor imagery. Whenever gathering features from EEG signals, maki...

Person identification with arrhythmic ECG signals using deep convolution neural network.

Scientific reports
Over the past decade, the use of biometrics in security systems and other applications has grown in popularity. ECG signals in particular are attracting increased attention due to their characteristics, which are required for a trustworthy identifica...

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction.

Magnetic resonance in medicine
PURPOSE: To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP).

Deep learning and predictive modelling for generating normalised muscle function parameters from signal images of mandibular electromyography.

Medical & biological engineering & computing
Challenges arise in accessing archived signal outputs due to proprietary software limitations. There is a notable lack of exploration in open-source mandibular EMG signal conversion for continuous access and analysis, hindering tasks such as pattern ...

A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.

Medical & biological engineering & computing
In recent years, fatigue driving has become the main cause of traffic accidents, leading to increased attention towards fatigue detection systems. However, the pooling and strided convolutional operations in fatigue detection algorithm based on tradi...

The Impact of Feature Extraction on Classification Accuracy Examined by Employing a Signal Transformer to Classify Hand Gestures Using Surface Electromyography Signals.

Sensors (Basel, Switzerland)
Interest in developing techniques for acquiring and decoding biological signals is on the rise in the research community. This interest spans various applications, with a particular focus on prosthetic control and rehabilitation, where achieving prec...