AIMC Topic: Signal Processing, Computer-Assisted
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Enhancing classification accuracy of HRF signals in fNIRS using semi-supervised learning and filtering.
Progress in brain research
May 31, 2024
This paper introduces a novel approach to enhance the classification accuracy of hemodynamic response function (HRF) signals acquired through functional near-infrared spectroscopy (fNIRS). Leveraging a semi-supervised learning (SSL) framework alongsi...
Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 31, 2024
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...
Exploring the potential of pretrained CNNs and time-frequency methods for accurate epileptic EEG classification: a comparative study.
Biomedical physics & engineering express
May 30, 2024
Prompt diagnosis of epilepsy relies on accurate classification of automated electroencephalogram (EEG) signals. Several approaches have been developed to characterize epileptic EEG data; however, none of them have exploited time-frequency data to eva...
A deep learning approach for generating intracranial pressure waveforms from extracranial signals routinely measured in the intensive care unit.
Computers in biology and medicine
May 29, 2024
Intracranial pressure (ICP) is commonly monitored to guide treatment in patients with serious brain disorders such as traumatic brain injury and stroke. Established methods to assess ICP are resource intensive and highly invasive. We hypothesized tha...
Arterial Distension Monitoring Scheme Using FPGA-Based Inference Machine in Ultrasound Scanner Circuit System.
IEEE transactions on biomedical circuits and systems
May 28, 2024
This paper presents an arterial distension monitoring scheme using a field-programmable gate array (FPGA)-based inference machine in an ultrasound scanner circuit system. An arterial distension monitoring requires a precise positioning of an ultrasou...
A 36-nW Electrocardiogram Anomaly Detector Based on a 1.5-bit Non-Feedback Delta Quantizer for Always-on Cardiac Monitoring.
IEEE transactions on biomedical circuits and systems
May 28, 2024
An always-on electrocardiogram (ECG) anomaly detector (EAD) with ultra-low power (ULP) consumption is proposed for continuous cardiac monitoring applications. The detector is featured with a 1.5-bit non-feedback delta quantizer (DQ) based feature ext...
Efficient in Vivo Neural Signal Compression Using an Autoencoder-Based Neural Network.
IEEE transactions on biomedical circuits and systems
May 28, 2024
Conventional in vivo neural signal processing involves extracting spiking activity within the recorded signals from an ensemble of neurons and transmitting only spike counts over an adequate interval. However, for brain-computer interface (BCI) appli...
ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization.
Physiological measurement
May 28, 2024
Cardiovascular diseases are a major cause of mortality globally, and electrocardiograms (ECGs) are crucial for diagnosing them. Traditionally, ECGs are stored in printed formats. However, these printouts, even when scanned, are incompatible with adva...
Characterization of Heart Diseases per Single Lead Using ECG Images and CNN-2D.
Sensors (Basel, Switzerland)
May 28, 2024
Cardiopathy has become one of the predominant global causes of death. The timely identification of different types of heart diseases significantly diminishes mortality risk and enhances the efficacy of treatment. However, fast and efficient recogniti...
EEG Emotion Recognition Network Based on Attention and Spatiotemporal Convolution.
Sensors (Basel, Switzerland)
May 27, 2024
Human emotions are complex psychological and physiological responses to external stimuli. Correctly identifying and providing feedback on emotions is an important goal in human-computer interaction research. Compared to facial expressions, speech, or...
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