Alex-Zhou's repositories
arxiv-sanity-preserver
Web interface for browsing, search and filtering recent arxiv submissions
DSP_EMGDL_Chapter
Deep Learning approaches for sEMG-based gesture recognition
GAN_generate_ninapro
Using GAN to generate new ninapro data.
MarkdownPhoto
This is my photo album for writing markdown.
NinaproCNN
Convolutional Neural Networks On Ninapro datasets
notes-for-scientific-paper
Some notes for writing paper summarized by myself, and the suggestions from my international friends. Thank them here!
sEMG_DeepLearning
sEMG-based gesture recognition using deep learnig
DeepSLR-Sign-Language-Recognition
基于sEMG和IMU的手语手势识别,包括数据收集、数据预处理(去噪、特征提取,分割)、神经网络搭建、实时识别等。
divide_NinaPro_database_5
This repository contain the code we used to divide NinaPro database 5 into train set and test set
EMG-Movement-Recognition
The source code for the the manuscript titled [M. AbdelMaseeh, T. W. Chen and D. W. Stashuk, "Extraction and Classification of Multichannel Electromyographic Activation Trajectories for Hand Movement Recognition," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 24, no. 6, pp. 662-673, June 2016.]. The paper proposes a system for hand movement recognition using multi-channel electromyographic (EMG) signals obtained from the forearm surface. This system can be potentially used to control prostheses or to provide input to a wide range of human computer interface systems. The developed methods were tested with the publicly available NINAPro database.
glow-pytorch-with-gui
This repository contains the gui for playing with the factorized feature learned from the NinaPro database 5.
lihang-code
《统计学习方法》的代码实现
Mymyo_Sunako
Learning about peocessing sEMG image
nina_helper_package
Python functions to aid working with the NinaPro databases (1 & 2)
nina_helper_package_mk2
Python functions and important data for working on NinaPro database 1 & 2
sEMG-Neural-Net
Neural network for classifying electromyographic signals into distinct gestures. Additionally, a comparison of CNN vs LSTM implementations.