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armyo

Action Recognition using Time Series CNNs for EMG Data

attention_network_with_keras

An example attention network with simple dataset.

bci_competition_iii_iva_analysis

CSP-based EEG feature extraction and visualization and classification tasks

bci_eegnet

EEGNet implementation of 2 BCI competition datasets

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.

ccsa

"Unified Deep Supervised Domain Adaptation and Generalization" (ICCV 2017)

cimap

Python algorithm to assess muscle activation patterns during cyclical movements

cnn-attention

An Image Classifier with attention layers visualized

dcnn_mu_decomp

deep-learning-for-human-activity-recognition

Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).

domainadaptionpytorch

Code for recent domain adaption implemented by pytorch.

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)

eegprocessing

emg

Python, PyQt5, microcontroller & electrode setup to measure EMG signals and test closed-loop (prosthetic) sensory feedback.

emg-gan

GANs for generating EMG signals

emg-myo-armband-lstm

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)

emg_decomposition_rhd

emg_realtime_robot

PROGRAM UNTUK REALTIME ROBOT EKSOSKELETON TANGAN BERBASIS EMG DENGAN RANDOM FOREST

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.

fs-hgr

FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography

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

keras_attention

:bookmark: An Attention Layer in Keras

meta-learning-for-eeg-classification-in-schizophrenia

Notebooks and pre-processing code for a meta learning paper/project involving the classification of EEG spectrograms.