AI Medical Compendium Topic:
Signal Processing, Computer-Assisted

Clear Filters Showing 851 to 860 of 1839 articles

Research and Verification of Convolutional Neural Network Lightweight in BCI.

Computational and mathematical methods in medicine
With the increasing of depth and complexity of the convolutional neural network, parameter dimensionality and volume of computing have greatly restricted its applications. Based on the SqueezeNet network structure, this study introduces a block convo...

An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features.

Computational and mathematical methods in medicine
The automatic detection of epilepsy is essentially the classification of EEG signals of seizures and nonseizures, and its purpose is to distinguish the different characteristics of seizure brain electrical signals and normal brain electrical signals....

Classification of Task-State fMRI Data Based on Circle-EMD and Machine Learning.

Computational intelligence and neuroscience
In the research work of the brain-computer interface and the function of human brain work, the state classification of multitask state fMRI data is a problem. The fMRI signal of the human brain is a nonstationary signal with many noise effects and in...

Intra-subject approach for gait-event prediction by neural network interpretation of EMG signals.

Biomedical engineering online
BACKGROUND: Machine learning models were satisfactorily implemented for estimating gait events from surface electromyographic (sEMG) signals during walking. Most of them are based on inter-subject approaches for data preparation. Aim of the study is ...

Depth in convolutional neural networks solves scene segmentation.

PLoS computational biology
Feed-forward deep convolutional neural networks (DCNNs) are, under specific conditions, matching and even surpassing human performance in object recognition in natural scenes. This performance suggests that the analysis of a loose collection of image...

Parkinson's disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study.

PloS one
Parkinson's disease (PD) is a neurodegenerative disease inducing dystrophy of the motor system. Automatic movement analysis systems have potential in improving patient care by enabling personalized and more accurate adjust of treatment. These systems...

Convolutional neural networks and genetic algorithm for visual imagery classification.

Physical and engineering sciences in medicine
Brain-Computer Interface (BCI) systems establish a channel for direct communication between the brain and the outside world without having to use the peripheral nervous system. While most BCI systems use evoked potentials and motor imagery, in the pr...

Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks.

PloS one
This research aims to analyze the effects of different parameter estimation on the recognition performance of satellite modulation signals based on deep learning (DL) under low signal to noise ratio (SNR) or channel non-ideal conditions. In this stud...

Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity.

Computer methods in biomechanics and biomedical engineering
Protruding impact peak is one of the features of vertical ground reaction force (GRF) that is related to injury risk while running. The present research is dedicated to predicting GRF impact peak appearance by setting a binary classification problem....

Non-Invasive Estimation of Intracranial Pressure by Diffuse Optics: A Proof-of-Concept Study.

Journal of neurotrauma
Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there ar...