智能媒体加速度计和陀螺仪（IM-AccGyro）数据集

Mouazma Batool http://portals.au.edu.pk/imc/ Data Set Information: We have introduced a Accelerometer and Gyroscope (IM-AccGyro) dataset using GY-521 sensors attached to the subject's arm, leg, and neck region to capture important aspects of human motion. The dataset represents motion data captured while subjects are involved in performing 6 human activity behaviors: boxing, clapping, running, sitting, standing, and walking. The ages of the participants range from 15 to 30 years with having weight ranging between 30-100 kgs. Due to multi-sensor environment and inter-behavioral similarity, the dataset itself poses adequate amount of challenges. Attribute Information: Provide information about each attribute in your data set. Relevant Papers: Provide references to papers that have cited this data set in the past (if any). Citation Request: If you have no special citation requests, please leave this field blank.

作者：Mouazma Batool
数据集来源链接：http://portals.au.edu.pk/imc/

数据集信息：本课题组构建了一款基于加速度计与陀螺仪（Accelerometer and Gyroscope，缩写IM-AccGyro）的数据集，通过附着于受试者手臂、腿部及颈部区域的GY-521传感器采集人体运动的关键特征。该数据集收录了受试者完成6类人体活动时的运动数据，活动类型涵盖拳击、拍手、跑步、坐姿、站姿与行走。参与本数据集采集的受试者年龄介于15至30岁，体重范围为30至100千克。由于存在多传感器部署环境与行为类间相似性问题，本数据集具备充足的研究挑战性。

属性信息：请说明数据集中各属性的相关信息。

相关论文：过往引用本数据集的相关文献（若有）。

引用要求：若无特殊引用要求，请留空该字段。

搜集汇总

背景与挑战

背景概述

IM-AccGyro数据集是一个用于人体活动识别研究的惯性传感器数据集，包含来自手臂、腿部和颈部的加速度计和陀螺仪数据，覆盖六种基本活动行为。数据集设计用于技术基准测试，具有多传感器和复杂行为特点。