Supporting data for "Personalized Electromyography Based Control Algorithm Development and Training System for Hand Prosthesis" for HKU Libraries

This dataset serves as the supporting data for thesis entitled “Personalized Electromyography Based Control Algorithm Development and Training System for Hand Prosthesis”.
It contains 5 upper limb amputees’ surface EMG signal for developing their customized intelligent prosthesis. And it also contains 11 normally subjects’ handedness’ surface EMG signal for comparison. 21-channels’s surface EMG signal were collected from the amputees and normal subjects to build the neuromuscular model of the amputees’ residual limb and normal subjects. The signal was collected with a sampling rate of 1000Hz and saved in .npy format. Corresponding data pre-processing program was included in the folder for processing while detailed data processing procedure was described in the thesis.
For the electrodes part, the Signal-to-Noise Ratio (SNR) were collected and compared in the 1_ subfolder.
For the hardware part, the 3D printable material to build the EAM-based prosthesis hand was included in the 2_ subfolder for reference.
For the proposed Shorted-Surface-Distance-Matrix(SSDM)’s detailed description and calculation were included in the 3-subfolder and the program to compare the SSDM’s effect were included in this folder for further analysis.
Due to the privacy concern of the amputees and the signed consent form, some data were not included in the dataset, but will be provided upon reasonable request.

本数据集作为题为《基于个性化肌电图控制算法开发与训练系统的手部假肢》的论文的辅助数据。其中包含了5名上肢截肢者表面肌电图信号，用于开发定制化的智能假肢。此外，还包含了11名正常受试者手部偏好的表面肌电图信号以供比较。从截肢者及正常受试者身上收集了21通道的表面肌电图信号，以构建截肢者残肢及正常受试者的神经肌肉模型。信号以1000Hz的采样率采集，并以.npy格式保存。数据预处理程序包含在文件夹中，详细的预处理步骤在论文中有所描述。

在电极部分，1_子文件夹中收集并比较了信噪比（SNR）。

在硬件部分，2_子文件夹中包含了用于构建基于EAM（电磁仿生）假肢手的3D可打印材料以供参考。

关于提出的缩短表面距离矩阵（SSDM）的详细描述和计算方法包含在3-子文件夹中，用于比较SSDM效果的程序也包含在此文件夹中，以供进一步分析。

鉴于对截肢者隐私的关注及已签署的同意书，部分数据未包含在数据集中，但可根据合理请求提供。