Biomedical Signal Processing

insight - Biomedical Signal Processing

Evaluating the Potential and Limitations of Photoplethysmography Signals for Accurate Blood Pressure Estimation

Photoplethysmography (PPG) signals contain information correlated to blood pressure, but may not be sufficient for accurately predicting it. Normalized invasive arterial blood pressure (N-IABP) signals provide a realistic benchmark for assessing the capabilities and constraints of PPG-based blood pressure estimation.

Automated Detection of Attention Deficit Hyperactivity Disorder (ADHD) using Entropy Difference-based EEG Channel Selection

An automated approach for accurate detection of ADHD using an entropy difference-based EEG channel selection technique.

Efficient Spiking Neural Network for Cross-Subject Lower Limb Joint Angle Estimation from Surface Electromyography

A hierarchical spiking neural network architecture, SAFE-Net, is proposed to efficiently estimate lower limb joint angles from surface electromyography signals, achieving high accuracy in cross-subject scenarios.

Automated Classification of Pediatric Heart Sounds for Congenital Heart Disease Diagnosis

A transformer-based convolutional neural network model can accurately classify pediatric heart sounds to detect congenital heart diseases using a minimum signal duration of 5 seconds.

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