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A novel deep-learning model based on Ï„-shaped convolutional network (Ï„Net) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals
In recent years, fatigue driving has become the main cause of traffic accidents, leading to increased attention towards fatigue detection systems....
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Spectral analysis and Bi-LSTM deep network-based approach in detection of mild cognitive impairment from electroencephalography signals
Mild cognitive impairment (MCI) is a neuropsychological syndrome that is characterized by cognitive impairments. It typically affects adults 60 years...
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Effect of time windows in LSTM networks for EEG-based BCIs
People with impaired motor function could be helped by an effective brain–computer interface (BCI) based on a real-time electroencephalogram (EEG)...
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Improved recovery of cardiac auscultation sounds using modified cosine transform and LSTM-based masking
Obtaining accurate cardiac auscultation signals, including basic heart sounds (S1 and S2) and subtle signs of disease, is crucial for improving...
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Long short-term memory (LSTM) recurrent neural network for muscle activity detection
BackgroundThe accurate temporal analysis of muscle activation is of great interest in many research areas, spanning from neurorobotic systems to the...
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Image Segmentation in 3D Brachytherapy Using Convolutional LSTM
PurposeThe accuracy of the segmentation of the target lesion and at-risk surrounding organs is important for cervical cancer patients treated with...
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Application of RESNET and Combined RESNET+LSTM Network for Retina Inspired Emotional Face Recognition System
Various Facial Expression Recognition (FER) systems have been studied in the field of computer vision and machine learning to encode expression...
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Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy
BackgroundSurface-guided radiation therapy can be used to continuously monitor a patient’s surface motions during radiotherapy by a non-irradiating,...
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Automatic Diagnosis of Schizophrenia in EEG Signals Using Functional Connectivity Features and CNN-LSTM Model
Schizophrenia (SZ) is a mental disorder that threatens the health of many people around the world. People with schizophrenia always suffer from...
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Prediction of medial knee contact force using multisource fusion recurrent neural network and transfer learning
Estimation of knee contact force (KCF) during gait provides essential information to evaluate knee joint function. Machine learning has been employed...
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Application of expert system and LSTM in extracting index of synaptic plasticity
The indexes of synaptic plasticity, including long-term potentiation (LTP) and long-term depression (LTD), can usually be measured by evaluating the...
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Deep learning networks based decision fusion model of EEG and fNIRS for classification of cognitive tasks
The detection of the cognitive tasks performed by a subject during data acquisition of a neuroimaging method has a wide range of applications:...
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An Effective Hybrid Deep Learning Model for Single-Channel EEG-Based Subject-Independent Drowsiness Recognition
Nowadays, road accidents pose a severe risk in cases of sleep disorders. We proposed a novel hybrid deep-learning model for detecting drowsiness to...
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Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification
Spiking neural networks (SNNs), as the third generation of neural networks, are based on biological models of human brain neurons. In this work, a...
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VascuConNet: an enhanced connectivity network for vascular segmentation
Medical image segmentation commonly involves diverse tissue types and structures, including tasks such as blood vessel segmentation and nerve fiber...
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Cardiac disease prediction using AI algorithms with SelectKBest
Atherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease (CHD) and ischemic stroke, is the leading cause of mortality...
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Estimation of lower limb joint moments based on the inverse dynamics approach: a comparison of machine learning algorithms for rapid estimation
AbstractThe aim of this study is to estimate the joint moments of the ankle, knee, and hip joints during walking. A sit-to-stand (STS) movement...
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Ensemble classifier fostered detection of arrhythmia using ECG data
Electrocardiogram (ECG) is a non-invasive medical tool that divulges the rhythm and function of the human heart. This is broadly employed in heart...
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LieWaves: dataset for lie detection based on EEG signals and wavelets
This study introduces an electroencephalography (EEG)-based dataset to analyze lie detection. Various analyses or detections can be performed using...
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KDeep: a new memory-efficient data extraction method for accurately predicting DNA/RNA transcription factor binding sites
This paper addresses the crucial task of identifying DNA/RNA binding sites, which has implications in drug/vaccine design, protein engineering, and...
