AIMC Topic: Signal Processing, Computer-Assisted

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PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces.

PloS one Aug 6, 2025
Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative technology with applications spanning robotics, virtual reality, medicine, and rehabilitation. However, existing BCI frameworks face several limitati...
Humans Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Software Algorithms Brain
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Cross-subject EEG signals-based emotion recognition using contrastive learning.

Scientific reports Aug 3, 2025
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Emotions Electroencephalography Machine Learning Algorithms Female Brain Humans Adult Male
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Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.

Scientific reports Jul 31, 2025
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...
Machine Learning Algorithms Deep Learning Humans Heart Failure Arrhythmias, Cardiac Electrocardiography Signal Processing, Computer-Assisted
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Physics-informed neural networks for physiological signal processing and modeling: a narrative review.

Physiological measurement Jul 30, 2025
Physics-informed neural networks (PINNs) represent a transformative approach to data models by incorporating known physical laws into neural network training, thereby improving model generalizability, reduce data dependency, and enhance interpretabil...
Humans Neural Networks, Computer Signal Processing, Computer-Assisted Physiological Phenomena
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Enhancing surface electromyographic signal recognition accuracy for trans-radial amputees using broad learning systems.

Biomedical physics & engineering express Jul 28, 2025
Gesture recognition based on surface electromyography (sEMG) plays a crucial role in human-computer interaction. By analyzing sEMG signals generated from residual forearm muscle activity in trans-radial amputees, it is possible to predict their hand ...
Algorithms Female Adult Male Middle Aged Artificial Limbs Gestures Hand Pattern Recognition, Automated Electromyography Humans Movement Amputees Machine Learning Forearm Muscle, Skeletal Signal Processing, Computer-Assisted
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A hybrid model for detecting motion artifacts in ballistocardiogram signals.

Biomedical engineering online Jul 23, 2025
BACKGROUND: The field of contactless health monitoring has witnessed significant advancements with the advent of piezoelectric sensing technology, which enables the monitoring of vital signs such as heart rate and respiration without requiring direct...
Signal Processing, Computer-Assisted Motion Artifacts Humans Deep Learning Movement Ballistocardiography
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Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks.

Scientific reports Jul 19, 2025
Accurate and efficient analysis of Electroencephalogram (EEG) signals is crucial for applications like neurological diagnosis and Brain-Computer Interfaces (BCI). Traditional methods often fall short in capturing the intricate temporal dynamics inher...
Brain-Computer Interfaces Wavelet Analysis Deep Learning Electroencephalography Signal Processing, Computer-Assisted Machine Learning Algorithms Humans Neural Networks, Computer
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ModelS4Apnea: leveraging structured state space models for efficient sleep apnea detection from ECG signals.

Physiological measurement Jul 11, 2025
. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate and efficient detection methods.. This study proposes ModelS4Apnea, a deep learning framework for sleep apnea detection from electrocardiogram (ECG) ...
Sleep Apnea Syndromes Deep Learning Electrocardiography Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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How EEG preprocessing shapes decoding performance.

Communications biology Jul 10, 2025
Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classification performance remains poorly understood. To address this gap, we analyzed seven experiments with 40 participants drawn from the public ERP CORE d...
Evoked Potentials Signal Processing, Computer-Assisted Artifacts Adult Humans Male Brain Neural Networks, Computer Electroencephalography Female Young Adult
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Automated detection of air trapping from mechanical ventilation waveform through interpretable dual-channel 1D convolutional neural network.

Physiological measurement Jul 10, 2025
. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant problem in treating patients using mechanical ventilation. If not handled timely, it can pose risk of s...
Bronchodilator Agents Humans Automation Neural Networks, Computer Respiration, Artificial Air Convolutional Neural Networks Signal Processing, Computer-Assisted
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