AIMC Topic: Signal Processing, Computer-Assisted

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MorphBungee: A 65-nm 7.2-mm 27-µJ/Image Digital Edge Neuromorphic Chip With on-Chip 802-Frame/s Multi-Layer Spiking Neural Network Learning.

IEEE transactions on biomedical circuits and systems Feb 11, 2025
This paper presents a digital edge neuromorphic spiking neural network (SNN) processor chip for a variety of edge intelligent cognitive applications. This processor allows high-speed, high-accuracy and fully on-chip spike-timing-based multi-layer SNN...
Equipment Design Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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Supervised Contrastive Learning Framework and Hardware Implementation of Learned ResNet for Real-Time Respiratory Sound Classification.

IEEE transactions on biomedical circuits and systems Feb 11, 2025
This paper presents a supervised contrastive learning (SCL) framework for respiratory sound classification and the hardware implementation of learned ResNet on field programmable gate array (FPGA) for real-time monitoring. At the algorithmic level, m...
Humans Signal Processing, Computer-Assisted Supervised Machine Learning Respiratory Sounds Neural Networks, Computer Algorithms Bayes Theorem
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PhysioEx: a new Python library for explainable sleep staging through deep learning.

Physiological measurement Feb 10, 2025
Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding sleep disorders. This work introduces PhysioEx (Physiological Signal Explainer), a Python library designed to support the analysis of sleep stages usin...
Electroencephalography Signal Processing, Computer-Assisted Sleep Stages Humans Software Deep Learning
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Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework.

IEEE journal of biomedical and health informatics Feb 10, 2025
High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for localizing the seizure onset zone (SOZ) in patients with focal refractory epilepsy. Despite their clinical significance, HFO analysis is often compro...
Epilepsies, Partial Algorithms Electroencephalography Humans Young Adult Brain Signal Processing, Computer-Assisted Female Adult Artifacts Machine Learning Electrocorticography Male
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WaveSleepNet: An Interpretable Network for Expert-Like Sleep Staging.

IEEE journal of biomedical and health informatics Feb 10, 2025
Although deep learning algorithms have proven their efficiency in automatic sleep staging, their "black-box" nature has limited their clinical adoption. In this study, we propose WaveSleepNet, an interpretable neural network for sleep staging that re...
Humans Polysomnography Neural Networks, Computer Sleep Stages Deep Learning Algorithms Female Electroencephalography Adult Signal Processing, Computer-Assisted Male
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Multiclass Classification Framework of Motor Imagery EEG by Riemannian Geometry Networks.

IEEE journal of biomedical and health informatics Feb 10, 2025
In motor imagery (MI) tasks for brain computer interfaces (BCIs), the spatial covariance matrix (SCM) of electroencephalogram (EEG) signals plays a critical role in accurate classification. Given that SCMs are symmetric positive definite (SPD), Riema...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans Brain Imagination Neural Networks, Computer Electroencephalography Algorithms
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SleepECG-Net: Explainable Deep Learning Approach With ECG for Pediatric Sleep Apnea Diagnosis.

IEEE journal of biomedical and health informatics Feb 10, 2025
Obstructive sleep apnea (OSA) in children is a prevalent and serious respiratory condition linked to cardiovascular morbidity. Polysomnography, the standard diagnostic approach, faces challenges in accessibility and complexity, leading to underdiagno...
Sleep Apnea, Obstructive Polysomnography Electrocardiography Signal Processing, Computer-Assisted Sleep Apnea Syndromes Humans Child, Preschool Diagnosis, Computer-Assisted Female Child Deep Learning Male Adolescent
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Incremental Classification for High-Dimensional EEG Manifold Representation Using Bidirectional Dimensionality Reduction and Prototype Learning.

IEEE journal of biomedical and health informatics Feb 10, 2025
In brain-computer interface (BCI) systems, symmetric positive definite (SPD) manifold within Riemannian space has been frequently utilized to extract spatial features from electroencephalogram (EEG) signals. However, the intrinsic high dimensionality...
Principal Component Analysis Electroencephalography Signal Processing, Computer-Assisted Brain Adult Brain-Computer Interfaces Dimensionality Reduction Humans Neural Networks, Computer Machine Learning Algorithms
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EEG Temporal-Spatial Feature Learning for Automated Selection of Stimulus Parameters in Electroconvulsive Therapy.

IEEE journal of biomedical and health informatics Feb 10, 2025
The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be high if an excessive stimulus is applied to induce the necessary generalized seizure (GS); Conversely, inadequate stimulus results in failure. Recent...
Machine Learning Female Adult Humans Electroconvulsive Therapy Electroencephalography Seizures Male Signal Processing, Computer-Assisted Middle Aged
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Innovative Dual-Decoupling CNN With Layer-Wise Temporal-Spatial Attention for Sensor-Based Human Activity Recognition.

IEEE journal of biomedical and health informatics Feb 10, 2025
Human Activity Recognition (HAR) is essential for monitoring and analyzing human behavior, particularly in health applications such as fall detection and chronic disease management. Traditional methods, even those incorporating attention mechanisms, ...
Human Activities Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Monitoring, Ambulatory
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