AI Medical Compendium Topic:
Signal Processing, Computer-Assisted

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Deep Learning Techniques in the Classification of ECG Signals Using R-Peak Detection Based on the PTB-XL Dataset.

Sensors (Basel, Switzerland)
Deep Neural Networks (DNNs) are state-of-the-art machine learning algorithms, the application of which in electrocardiographic signals is gaining importance. So far, limited studies or optimizations using DNN can be found using ECG databases. To expl...

Epileptic Seizures Detection in EEG Signals Using Fusion Handcrafted and Deep Learning Features.

Sensors (Basel, Switzerland)
Epilepsy is a brain disorder disease that affects people's quality of life. Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper provides a computer-aided diagnosis system (CADS) for the automatic diagnosis of epil...

A Review of Deep Learning-Based Methods for Pedestrian Trajectory Prediction.

Sensors (Basel, Switzerland)
Pedestrian trajectory prediction is one of the main concerns of computer vision problems in the automotive industry, especially in the field of advanced driver assistance systems. The ability to anticipate the next movements of pedestrians on the str...

EEG-based detection of emotional valence towards a reproducible measurement of emotions.

Scientific reports
A methodological contribution to a reproducible Measurement of Emotions for an EEG-based system is proposed. Emotional Valence detection is the suggested use case. Valence detection occurs along the interval scale theorized by the Circumplex Model of...

Classification of electrocardiogram signals with waveform morphological analysis and support vector machines.

Medical & biological engineering & computing
Electrocardiogram (ECG) indicates the occurrence of various cardiac diseases, and the accurate classification of ECG signals is important for the automatic diagnosis of arrhythmia. This paper presents a novel classification method based on multiple f...

Scoring Performance on the Y-Balance Test Using a Deep Learning Approach.

Sensors (Basel, Switzerland)
The Y Balance Test (YBT) is a dynamic balance assessment typically used in sports medicine. This work proposes a deep learning approach to automatically score this YBT by estimating the normalized reach distance (NRD) using a wearable sensor to regis...

Advanced computation in cardiovascular physiology: new challenges and opportunities.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While th...

A Deep Learning-Based Classification Method for Different Frequency EEG Data.

Computational and mathematical methods in medicine
In recent years, the research on electroencephalography (EEG) has focused on the feature extraction of EEG signals. The development of convenient and simple EEG acquisition devices has produced a variety of EEG signal sources and the diversity of the...

Model Construction of Using Physiological Signals to Detect Mental Health Status.

Journal of healthcare engineering
BACKGROUND: Mental health is a direct indicator of human mental activity, and it also affects all aspects of the human body. It plays a very important role in monitoring human mental health.

Noninvasive Methods for Fault Detection and Isolation in Internal Combustion Engines Based on Chaos Analysis.

Sensors (Basel, Switzerland)
The classic monitoring methods for detecting faults in automotive vehicles based on on-board diagnostics (OBD) are insufficient when diagnosing several mechanical failures. Other sensing techniques present drawbacks such as high invasiveness and limi...