AIMC Topic: Signal Processing, Computer-Assisted

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Improved and Secured Electromyography in the Internet of Health Things.

IEEE journal of biomedical and health informatics May 5, 2022
Physiological signals are of great importance for clinical analysis but are prone to diverse interferences. To enable practical applications, biosignal quality issues, especially contaminants, need to be dealt with automated processes. For example, a...
Algorithms Signal Processing, Computer-Assisted Electromyography Internet Humans Neural Networks, Computer
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An Event-Based Digital Time Difference Encoder Model Implementation for Neuromorphic Systems.

IEEE transactions on neural networks and learning systems May 2, 2022
Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such ...
Neurons Computers Signal Processing, Computer-Assisted Neural Networks, Computer
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Recognizing Missing Electromyography Signal by Data Split Reorganization Strategy and Weight-Based Multiple Neural Network Voting Method.

IEEE transactions on neural networks and learning systems May 2, 2022
Surface electromyography (sEMG) signals have been applied widely in prosthetic hand controlling. In the sEMG signal acquisition, wireless devices bring convenience, but also introduce signal missing due to interference or failure during data transmis...
Humans Gestures Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Electromyography
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Electrocardiogram Biometrics Using Transformer's Self-Attention Mechanism for Sequence Pair Feature Extractor and Flexible Enrollment Scope Identification.

Sensors (Basel, Switzerland) Apr 30, 2022
The existing electrocardiogram (ECG) biometrics do not perform well when ECG changes after the enrollment phase because the feature extraction is not able to relate ECG collected during enrollment and ECG collected during classification. In this rese...
Databases, Factual Electrocardiography Atrial Fibrillation Biometry Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans
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The Effect of the MFCC Frame Length in Automatic Voice Pathology Detection.

Journal of voice : official journal of the Voice Foundation Apr 27, 2022
Automatic voice pathology detection is a research topic, which has gained increasing interest recently. Although methods based on deep learning are becoming popular, the classical pipeline systems based on a two-stage architecture consisting of a fea...
Speech Production Measurement Voice Quality Speech Acoustics Voice Disorders Dysphonia Predictive Value of Tests Signal Processing, Computer-Assisted Sound Spectrography Automation Acoustics Reproducibility of Results Support Vector Machine Humans Databases, Factual
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A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography.

Sensors (Basel, Switzerland) Apr 26, 2022
Non-invasive foetal electrocardiography (NI-FECG) has become an important prenatal monitoring method in the hospital. However, due to its susceptibility to non-stationary noise sources and lack of robust extraction methods, the capture of high-qualit...
Female Deep Learning Signal Processing, Computer-Assisted Fetus Electrocardiography Algorithms Humans Pregnancy Neural Networks, Computer
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Intelligent Monitoring System Based on Noise-Assisted Multivariate Empirical Mode Decomposition Feature Extraction and Neural Networks.

Computational intelligence and neuroscience Apr 25, 2022
Because of the nonlinearity and nonstationarity in the vibration signals of some rotating machinery, the analysis of these signals using conventional time- or frequency-domain methods has some drawbacks, and the results can be misleading. In this pap...
Signal-To-Noise Ratio Noise Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Key Feature Extraction Method of Electroencephalogram Signal by Independent Component Analysis for Athlete Selection and Training.

Computational intelligence and neuroscience Apr 15, 2022
Emotion is an important expression generated by human beings to external stimuli in the process of interaction with the external environment. It affects all aspects of our lives all the time. Accurate identification of human emotional states and furt...
Athletes Brain-Computer Interfaces Humans Electroencephalography Artificial Intelligence Signal Processing, Computer-Assisted Algorithms
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Deep Learning Methods for Multi-Channel EEG-Based Emotion Recognition.

International journal of neural systems Apr 2, 2022
Currently, Fourier-based, wavelet-based, and Hilbert-based time-frequency techniques have generated considerable interest in classification studies for emotion recognition in human-computer interface investigations. Empirical mode decomposition (EMD)...
Neural Networks, Computer Deep Learning Emotions Humans Electroencephalography Signal Processing, Computer-Assisted
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Engineering nonlinear epileptic biomarkers using deep learning and Benford's law.

Scientific reports Mar 30, 2022
In this study, we designed two deep neural networks to encode 16 features for early seizure detection in intracranial EEG and compared them and their frequency responses to 16 widely used engineered metrics to interpret their properties: epileptogeni...
Deep Learning Electroencephalography Signal Processing, Computer-Assisted Humans Epilepsy Biomarkers
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