Open Access Dataset and Toolbox of High-Density Surface Electromyogram Recordings

We provide an open access dataset of _High densitY Surface Electromyogram_
(HD-sEMG) _Recordings_ (named " _Hyser_ "). We acquired data from 20 subjects
with each subject participating in our experiment twice on separate days
following the same experiment paradigm. Our _Hyser_ dataset contains five sub-
datasets: (1) pattern recognition (PR) dataset acquired during 34 hand
gestures, (2) maximal voluntary muscle contraction (MVC) dataset while
subjects contracted each individual finger, (3) one-degree of freedom (DoF)
dataset acquired during force-varying contraction of each individual finger,
(4) N-DoF dataset acquired during prescribed contractions of combinations of
multiple fingers, and (5) random task dataset acquired during random
contraction of combinations of fingers without any prescribed force
trajectory. Sub-dataset 1 can be used for gesture recognition studies. Sub-
datasets 2-5 also recorded individual finger forces, thus can be used for
studies on proportional control of neuroprostheses.

搜集汇总

背景与挑战

背景概述

该数据集是一个名为'Hyser'的高密度表面肌电图（HD-sEMG）开放访问数据集，包含20名受试者的两次实验数据，涵盖五个子数据集：手势识别、最大自主收缩、单指力变化、多指组合收缩和随机收缩。这些数据可用于手势识别和神经假体比例控制研究，特别适用于机器学习、生物医学工程和康复技术领域。