YuanyuanGao216 / fNIRS_denoise_by_DLLinks
This for the project removing motion artifacts in fNIRS by deep learning. The publication on this code is 'Deep Learning-based motion artifact removal in functional near-infrared spectroscopy (fNIRS)' submitted to Neuroimage.
☆12Updated 3 years ago
Alternatives and similar repositories for fNIRS_denoise_by_DL
Users that are interested in fNIRS_denoise_by_DL are comparing it to the libraries listed below
Sorting:
- This repository includes the MATLAB codes for computing phase lag index and power spectrum density.☆11Updated last year
- This example shows how to build and train a convolutional neural network (CNN) from scratch to perform a classification task with an EEG …☆52Updated 2 years ago
- A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface☆15Updated 3 years ago
- Codes for our paper "Triple-Attention-based Spatio-Temporal-Spectral Convolutional Network for Epileptic Seizure Prediction "☆21Updated 2 years ago
- Parallel signal feature extraction code. The code was originally written for sEMG, but it can be applied to other data arranged as multip…☆46Updated 5 years ago
- Deep learning model for EEG artifact removal☆74Updated 3 years ago
- This toolbox offers 30 types of EEG feature extraction methods (HA, HM, HC, and etc.) for Electroencephalogram (EEG) applications.☆89Updated 4 years ago
- Different methods(STFT, CWT) transform EEG signal into image visualization☆14Updated 4 years ago
- MATLAB Project to Classify Different Sleep Stages of the EEG Signals using Machine Learning (Random Forest and Support Vector Machine)☆11Updated 5 months ago
- EEG Signal Processing - Entropy☆18Updated 5 years ago
- A Residual based Attention Model for EEG basedSleep Staging☆11Updated 3 years ago
- Collection of Matlab functions for denoising fMRI data☆13Updated 3 years ago
- Alzheimer’s Disease (AD) is the most common neurodegenerative disease. It is typically late onset and can develop substantially before di…☆31Updated 5 years ago
- An all-in-one EEG feature extraction toobox, including statistical features, Hjorth parameters, entropy, nonlinear features, power spectr…☆43Updated last year
- Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification☆72Updated 5 months ago
- This repository contains the trained deep learning models for the detection and prediction of Epileptic seizures.☆22Updated 3 years ago
- This is a matlab implementation of our article, titled "DreamNet: A Deep Riemannian Manifold Network for SPD Matrix Learning", which has …☆14Updated 2 years ago
- Usually for ECG signal, the frequency range over 80Hz is noise. So first, we need to remove this high frequency part. Next, in ECG signal…☆15Updated 7 years ago
- Sleep stage automatic classifier using CNNs and LSTMs to process frequency signals of brain activity recorded via ElectroEncephaloGram EE…☆20Updated 3 years ago
- This repository includes useful MATLAB codes for the detection of epileptic seizure in EEG signals using wavelet analysis and machine lea…☆11Updated last year
- CNN-SAE program for MI-BCI classification. (Based on "Tabar et al-2016-J Neural Eng. A novel deep learning approach for classification of…☆43Updated 6 years ago
- Matlab code for SBLEST algorithm☆43Updated last year
- Epilepsy Prediction with CNN-BiLSTM | BSc dissertation project☆21Updated 2 years ago
- ☆10Updated 3 years ago
- Here are the Matlab codes used in "Fuzzy Entropy Metrics for the Analysis of Biomedical Signals: Assessment and Comparison, IEEE ACCESS, …☆16Updated 5 years ago
- About Open source code of paper: Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX☆63Updated last year
- Adaptive riemannian geometry toolbox☆10Updated 6 years ago
- Construct a model, which contains channel-attention, CNN, LSTM, self-attention, to classify EEG data;☆11Updated 3 years ago
- Preprocessing and feature extraction (slopes, moving slopes, Kurtosis, skewness, mean and variance) codes in MATLAB for analyzing fNIRS (…☆10Updated 7 years ago
- EEGdenoiseNet, a benchmark dataset, that is suited for training and testing deep learning-based EEG denoising models, as well as for comp…☆200Updated last year