northeastwang's repositories
BCI_competition_III_IVa_analysis
CSP-based EEG feature extraction and visualization and classification tasks
BPK409-Lab3-EMG
The purpose of this unit is to introduce you to the measurement and analysis of electrical activity generated by skeletal muscle, including determining the magnitude of muscle activation, the frequency spectrum of the muscle activity, and the level of muscle fatigue.
CIMAP
Python algorithm to assess muscle activation patterns during cyclical movements
Deep-Learning-for-Human-Activity-Recognition
Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).
EMG
Python, PyQt5, microcontroller & electrode setup to measure EMG signals and test closed-loop (prosthetic) sensory feedback.
EMG_REALTIME_ROBOT
PROGRAM UNTUK REALTIME ROBOT EKSOSKELETON TANGAN BERBASIS EMG DENGAN RANDOM FOREST
FS-HGR
FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography
EEG-Motor-Imagery-Classification---ANN
Classification of BCI competition VI dataset 2a using ANN by applying WPD and CSP for feature extraction
EEGANet
EEG Artifact Removal Using Deep Learning (source code, IEEE Journal of Biomedical and Health Informatics)
EMG_Crosstalk_Decomposition_Workshop
Theis repository contains notebooks that was developed to teach how the Principal Component Analysis (PCA) and Independent Component Analysis (ICA) works and how them can be used to decompose high-density surface electromyogram (HD sEMG) signals using the well-known FastICA algorithm.
EMG_Decomposition
Decomposing raw electromyography data into motor unit action potentials (MUAPs)
EMGdecomPy
A package for decomposing multi-channel EMG signals into individual motor unit activity.
fastICA_EMG_decomp
Matlab implementation of FastICA approach for hdEMG decompostion, presented in the Hyser dataset paper
FB-EEGNet
a deep neural network for ssvep target recognition.
Gest-Infer
This repository includes components used in the article titled "Event-Driven Edge Deep Learning Decoder for Real-time Gesture Classification and Neuro-inspired Rehabilitation Device Control"
hdEMG-Decomposition
MATLAB implementation of (FAST) ICA decomposition of hd-sEMG signals to motor units
Keras-FewShotLearning
Some State-of-the-Art few shot learning algorithms in tensorflow 2
Meta-Learning-for-EEG-Classification-in-Schizophrenia
Notebooks and pre-processing code for a meta learning paper/project involving the classification of EEG spectrograms.
MIN2Net
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
MNE-Cookbook
使用MNE-python过程中的小技巧,即如何处理MEG/EEG信号数据.
muscle_synergy_torque_accuracy
project to explore the relationship between muscle activation patterns and torque-perceptual accuracy
Schizophrenia-Detection-Using-EEG-and-ML
Jupyter notebook for detection of schizophrenia in subjects using EEG and ML algorithms - Logistic Regression and 1D CNN
sEMG_DeepLearning
sEMG-based gesture recognition using deep learnig
Siamese-keras
这是一个孪生神经网络（Siamese network）的库，可进行图片的相似性比较。