KU-HAR: An Open Dataset for Human Activity Recognition

(Always use the latest version of the dataset. )

Human Activity Recognition (HAR) refers to the capacity of machines to perceive human actions. This dataset contains information on 18 different activities collected from 90 participants (75 male and 15 female) using smartphone sensors (Accelerometer and Gyroscope). It has 1945 raw activity samples collected directly from the participants, and 20750 subsamples extracted from them. The activities are:

Stand➞ Standing still (1 min)
Sit➞ Sitting still (1 min)
Talk-sit➞ Talking with hand movements while sitting (1 min)
Talk-stand➞ Talking with hand movements while standing or walking(1 min)
Stand-sit➞ Repeatedly standing up and sitting down (5 times)
Lay➞ Laying still (1 min)
Lay-stand➞ Repeatedly standing up and laying down (5 times)
Pick➞ Picking up an object from the floor (10 times)
Jump➞ Jumping repeatedly (10 times)
Push-up➞ Performing full push-ups (5 times)
Sit-up➞ Performing sit-ups (5 times)
Walk➞ Walking 20 meters (≈12 s)
Walk-backward➞ Walking backward for 20 meters (≈20 s)
Walk-circle➞ Walking along a circular path (≈ 20 s)
Run➞ Running 20 meters (≈7 s)
Stair-up➞ Ascending on a set of stairs (≈1 min)
Stair-down➞ Descending from a set of stairs (≈50 s)
Table-tennis➞ Playing table tennis (1 min)

Contents of the attached .zip files are:
1.Raw_time_domian_data.zip➞ Originally collected 1945 time-domain samples in separate .csv files. The arrangement of information in each .csv file is:
Column 1, 5➞ exact time (elapsed since the start) when the Accelerometer & Gyro output was recorded (in ms)
Col. 2, 3, 4➞ Acceleration along X,Y,Z axes (in m/s^2)
Col. 6, 7, 8➞ Rate of rotation around X,Y,Z axes (in rad/s)

2.Trimmed_interpolated_raw_data.zip➞ Unnecessary parts of the samples were trimmed (only from the beginning and the end). The samples were interpolated to keep a constant sampling rate of 100 Hz. The arrangement of information is the same as above.

3.Time_domain_subsamples.zip➞ 20750 subsamples extracted from the 1945 collected samples provided in a single .csv file. Each of them contains 3 seconds of non-overlapping data of the corresponding activity. Arrangement of information:
Col. 1–300, 301–600, 601–900➞ Acc.meter X, Y, Z axes readings
Col. 901–1200, 1201–1500, 1501–1800➞ Gyro X, Y, Z axes readings
Col. 1801➞ Class ID (0 to 17, in the order mentioned above)
Col. 1802➞ length of the each channel data in the subsample
Col. 1803➞ serial no. of the subsample

Gravity acceleration was omitted from the Acc.meter data, and no filter was applied to remove noise. The dataset is free to download, modify, and use.

More information is provided in the data paper which is currently under review:
N. Sikder, A.-A. Nahid, KU-HAR: An open dataset for heterogeneous human activity recognition, Pattern Recognit. Lett. (submitted).

A preprint will be available soon.

Backup: drive.google.com/drive/folders/1yrG8pwq3XMlyEGYMnM-8xnrd6js0oXA7

请始终使用该数据集的最新版本。

人类活动识别（Human Activity Recognition, HAR）指机器感知人类行为的能力。本数据集收录了来自90名受试者（75名男性、15名女性）的18类不同活动的数据，数据通过智能手机传感器（加速度计（Accelerometer）与陀螺仪（Gyroscope））采集得到。其中包含直接从受试者采集得到的1945条原始活动样本，以及从这些原始样本中提取得到的20750个子样本。活动类别如下：

Stand➞ 静止站立1分钟
Sit➞ 静止坐姿1分钟
Talk-sit➞ 坐姿状态下伴随手部动作的交谈，时长1分钟
Talk-stand➞ 站姿或行走状态下伴随手部动作的交谈，时长1分钟
Stand-sit➞ 反复站起与坐下，共5次
Lay➞ 静止躺卧1分钟
Lay-stand➞ 反复躺卧与站起，共5次
Pick➞ 从地面拾取物体，共10次
Jump➞ 反复跳跃，共10次
Push-up➞ 完成标准俯卧撑，共5次
Sit-up➞ 完成仰卧起坐，共5次
Walk➞ 步行20米（耗时约12秒）
Walk-backward➞ 倒退步行20米（耗时约20秒）
Walk-circle➞ 沿圆形路径步行（耗时约20秒）
Run➞ 跑步20米（耗时约7秒）
Stair-up➞ 攀登一段楼梯（耗时约1分钟）
Stair-down➞ 从一段楼梯下行（耗时约50秒）
Table-tennis➞ 打乒乓球，时长1分钟

附带的压缩文件内容如下：
1. Raw_time_domian_data.zip：包含最初采集得到的1945条时域样本，每条样本存储于独立的.csv文件中。每个.csv文件的信息排布格式如下：
第1、5列：加速度计与陀螺仪输出的记录时刻（自采集起始时刻起的流逝时长，单位：毫秒）
第2、3、4列：X、Y、Z三轴的加速度值（单位：米每二次方秒，m/s²）
第6、7、8列：X、Y、Z三轴的旋转角速度（单位：弧度每秒，rad/s）

2. Trimmed_interpolated_raw_data.zip：对原始样本的首尾冗余部分进行了裁剪，并通过插值处理将采样率统一为100Hz，文件信息排布格式与上述一致。

3. Time_domain_subsamples.zip：包含从1945条采集样本中提取得到的20750个子样本，所有子样本存储于单个.csv文件中。每个子样本包含对应活动的3秒无重叠数据。信息排布格式如下：
第1~300列、301~600列、601~900列：加速度计（Acc.meter）X、Y、Z三轴的采集数据
第901~1200列、1201~1500列、1501~1800列：陀螺仪（Gyro）X、Y、Z三轴的采集数据
第1801列：类别ID（取值范围0~17，与前文提及的活动顺序一一对应）
第1802列：子样本中各通道数据的长度
第1803列：子样本的序列号

加速度计数据中已移除重力加速度分量，且未使用任何滤波器去除噪声。本数据集可免费下载、修改与使用。

更多详细信息可参阅当前处于审稿阶段的相关论文：N. Sikder、A.-A. Nahid，《KU-HAR：面向异构人类活动识别的开源数据集》，发表于《Pattern Recognit. Lett.》（已投稿）。

预印本将于近期发布。

备份链接：drive.google.com/drive/folders/1yrG8pwq3XMlyEGYMnM-8xnrd6js0oXA7