AIMC Topic: Signal Processing, Computer-Assisted

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ECGVEDNET: A Variational Encoder-Decoder Network for ECG Delineation in Morphology Variant ECGs.

IEEE transactions on bio-medical engineering Jun 19, 2024
Electrocardiogram (ECG) delineation to identify the fiducial points of ECG segments, plays an important role in cardiovascular diagnosis and care. Whilst deep delineation frameworks have been deployed within the literature, several factors still hind...
Signal Processing, Computer-Assisted Deep Learning Electrocardiography Humans Algorithms Databases, Factual
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The Deep-Match Framework: R-Peak Detection in Ear-ECG.

IEEE transactions on bio-medical engineering Jun 19, 2024
The Ear-ECG provides a continuous Lead I like electrocardiogram (ECG) by measuring the potential difference related to heart activity by electrodes which are embedded within earphones. However, the significant increase in wearability and comfort enab...
Humans Algorithms Electrocardiography Signal Processing, Computer-Assisted Adult Deep Learning Ear Wearable Electronic Devices
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Energy-Efficient PPG-Based Respiratory Rate Estimation Using Spiking Neural Networks.

Sensors (Basel, Switzerland) Jun 19, 2024
Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pres...
Heart Rate Respiratory Rate Photoplethysmography Signal Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Deep Learning
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Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures.

Sensors (Basel, Switzerland) Jun 19, 2024
This work addresses the challenge of classifying multiclass visual EEG signals into 40 classes for brain-computer interface applications using deep learning architectures. The visual multiclass classification approach offers BCI applications a signif...
Humans Electroencephalography Signal Processing, Computer-Assisted Neural Networks, Computer Brain-Computer Interfaces Algorithms Deep Learning
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Classification of Parkinson's disease severity using gait stance signals in a spatiotemporal deep learning classifier.

Medical & biological engineering & computing Jun 17, 2024
Parkinson's disease (PD) is a degenerative nervous system disorder involving motor disturbances. Motor alterations affect the gait according to the progression of PD and can be used by experts in movement disorders to rate the severity of the disease...
Severity of Illness Index Case-Control Studies Deep Learning Male Middle Aged Parkinson Disease Signal Processing, Computer-Assisted Gait Humans Neural Networks, Computer Algorithms Female Aged
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Automated diagnosis of schizophrenia based on spatial-temporal residual graph convolutional network.

Biomedical engineering online Jun 17, 2024
BACKGROUND: Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is requ...
Humans Neural Networks, Computer Spatio-Temporal Analysis Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Schizophrenia Electroencephalography Automation
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EEG emotion recognition based on data-driven signal auto-segmentation and feature fusion.

Journal of affective disorders Jun 15, 2024
Pattern recognition based on network connections has recently been applied to the brain-computer interface (BCI) research, offering new ideas for emotion recognition using Electroencephalogram (EEG) signal. However unified standards are currently lac...
Brain-Computer Interfaces Emotions Electroencephalography Signal Processing, Computer-Assisted Male Support Vector Machine Humans Algorithms Brain Female Young Adult Adult
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Machine Learning Algorithms for Processing and Classifying Unsegmented Phonocardiographic Signals: An Efficient Edge Computing Solution Suitable for Wearable Devices.

Sensors (Basel, Switzerland) Jun 14, 2024
The phonocardiogram (PCG) can be used as an affordable way to monitor heart conditions. This study proposes the training and testing of several classifiers based on SVMs (support vector machines), k-NN (k-Nearest Neighbor), and NNs (neural networks) ...
Support Vector Machine Signal Processing, Computer-Assisted Phonocardiography Machine Learning Algorithms Wearable Electronic Devices Humans Neural Networks, Computer
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GCTNet: a graph convolutional transformer network for major depressive disorder detection based on EEG signals.

Journal of neural engineering Jun 14, 2024
Identifying major depressive disorder (MDD) using objective physiological signals has become a pressing challenge.Hence, this paper proposes a graph convolutional transformer network (GCTNet) for accurate and reliable MDD detection using electroencep...
Humans Neural Networks, Computer Algorithms Depressive Disorder, Major Electroencephalography Signal Processing, Computer-Assisted Adult Male Middle Aged Female Young Adult
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Deep learning based ECG segmentation for delineation of diverse arrhythmias.

PloS one Jun 13, 2024
Accurate delineation of key waveforms in an ECG is a critical step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using segmentation models to locate P, QRS, and T wave...
Arrhythmias, Cardiac Humans Deep Learning Algorithms Electrocardiography Signal Processing, Computer-Assisted
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