AIMC Topic: Signal Processing, Computer-Assisted

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The effect of time normalization and biomechanical signal processing techniques of ground reaction force curves on deep-learning model performance.

Journal of biomechanics Apr 24, 2024
Time-series data are common in biomechanical studies. These data often undergo pre-processing steps such as time normalization or filtering prior to use in further analyses, including deep-learning classification. In this context, it remains unclear ...
Male Humans Deep Learning Neural Networks, Computer Walking Female Signal Processing, Computer-Assisted Gait Adult Models, Biological Biomechanical Phenomena
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Study on Gesture Recognition Method with Two-Stream Residual Network Fusing sEMG Signals and Acceleration Signals.

Sensors (Basel, Switzerland) Apr 24, 2024
Currently, surface EMG signals have a wide range of applications in human-computer interaction systems. However, selecting features for gesture recognition models based on traditional machine learning can be challenging and may not yield satisfactory...
Signal Processing, Computer-Assisted Algorithms Hand Humans Acceleration Biomechanical Phenomena Electromyography Neural Networks, Computer Pattern Recognition, Automated Gestures Machine Learning
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Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images.

Physical and engineering sciences in medicine Apr 23, 2024
Schizophrenia (SZ) has been acknowledged as a highly intricate mental disorder for a long time. In fact, individuals with SZ experience a blurred line between fantasy and reality, leading to a lack of awareness about their condition, which can pose s...
Image Processing, Computer-Assisted Electroencephalography Signal Processing, Computer-Assisted Wavelet Analysis Schizophrenia Adult Humans Automation Male Machine Learning
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Classification Method of ECG Signals Based on RANet.

Cardiovascular engineering and technology Apr 23, 2024
BACKGROUND: Electrocardiograms (ECG) are an important source of information on human heart health and are widely used to detect different types of arrhythmias.
Databases, Factual Reproducibility of Results Diagnosis, Computer-Assisted Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Humans Deep Learning Arrhythmias, Cardiac Neural Networks, Computer Electrocardiography Heart Rate
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Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.

IEEE transactions on bio-medical engineering Apr 22, 2024
OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position wi...
Humans Female Biomechanical Phenomena Young Adult Male Adult Signal Processing, Computer-Assisted Neural Networks, Computer Artificial Limbs Hand Machine Learning Forearm Electromyography Algorithms
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Physics-Informed Transfer Learning to Enhance Sleep Staging.

IEEE transactions on bio-medical engineering Apr 22, 2024
OBJECTIVE: At-home sleep staging using wearable medical sensors poses a viable alternative to in-hospital polysomnography due to its lower cost and lower disruption to the daily lives of patients, especially in the case of long-term monitoring. Machi...
Electroencephalography Signal Processing, Computer-Assisted Polysomnography Sleep Stages Humans Machine Learning Wearable Electronic Devices
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Frequency Domain Channel-Wise Attack to CNN Classifiers in Motor Imagery Brain-Computer Interfaces.

IEEE transactions on bio-medical engineering Apr 22, 2024
OBJECTIVE: Convolutional neural network (CNN), a classical structure in deep learning, has been commonly deployed in the motor imagery brain-computer interface (MIBCI). Many methods have been proposed to evaluate the vulnerability of such CNN models,...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Computer Security Imagination Humans Neural Networks, Computer Algorithms
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Prototype Learning for Medical Time Series Classification via Human-Machine Collaboration.

Sensors (Basel, Switzerland) Apr 22, 2024
Deep neural networks must address the dual challenge of delivering high-accuracy predictions and providing user-friendly explanations. While deep models are widely used in the field of time series modeling, deciphering the core principles that govern...
Humans Heart Rate Electrocardiography Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Deep Learning Atrial Fibrillation
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A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.

Journal of neuroscience methods Apr 19, 2024
BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals f...
Electroencephalography Signal Processing, Computer-Assisted Wrist Motor Activity Imagination Humans Brain-Computer Interfaces Young Adult Wavelet Analysis Adult Machine Learning Male Brain Female
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Imagined speech classification exploiting EEG power spectrum features.

Medical & biological engineering & computing Apr 18, 2024
Imagined speech recognition has developed as a significant topic of research in the field of brain-computer interfaces. This innovative technique has great promise as a communication tool, providing essential help to those with impairments. An imagin...
Female Young Adult Adult Male Humans Algorithms Brain Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Speech Support Vector Machine Electroencephalography
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