Vibration and IMU Sensing Human Activity Dataset

<p>This dataset contains fine-grained human daily activity data collected by infrastructure vibration sensors and one on-wrist IMU sensor. This dataset is collected from six persons from two domestic homes, in total, there are 12 sub-datasets.</p> <p>For the naming, &quot;p&quot; means person and &quot;l&quot; means location.</p> <p>Each dataset has 11 columns, 1o of them&nbsp;stands for&nbsp;sensors&#39; reading.</p> <p>* Due to the uploading platform, please<strong> <em>ignore</em>&nbsp;</strong>all files in the folder &#39;__MACOSX&#39;, and files whose names start with &#39;._&#39;. These are computer&nbsp;system files, not parts of the shared dataset.&nbsp;</p> <p>**&nbsp;If you are going to use this dataset for any publications, we will appreciate you to cite this dataset properly.</p> <p>************************************************************</p> <p>The following content is&nbsp;copied from README.txt in the compressed folder:</p> <p>-----------------------<br> Labels:</p> <p>Keyboard typing 1<br> Using mouse 2<br> Handwriting 3<br> Cutting vegetables 4<br> Stir-frying vegetables 5<br> Wiping the table 6<br> Sweeping floor 7<br> Using vacuum to vacuum floor: 8<br> Open and close drawer: 9</p> <p>None Activity: 10</p> <p>-----------------------<br> 11 Columns:<br> 1: Activity label<br> 2: Vibration sensor put on the Living Area floor<br> 3: Vibration sensor put on the Living Area table<br> 4: Vibration sensor put on the Studying Area floor<br> 5: Vibration sensor put on the Studying Area desk<br> 6, 7, 8: Accelerometer X,Y,Z<br> 9, 10, 11: Gyroscope X,Y,Z</p> <p>-----------------------<br> All signals are zero-meaned.<br> The vibration sensors&#39; sampling rate is roughly around 6500Hz, and the IMU sensors&#39; original sampling rate is roughly around 235Hz.</p> <p>************************************************************</p> <p>New in Version 2:</p> <p>- Added extracted features from IMU data and vibration data for reference.</p> <p>- IMU signal&nbsp;is applied with&nbsp;a sliding window of 1.5 seconds with 0.75 seconds overlapping, then the feature is extracted in each window. The feature&#39;s description can be found here:&nbsp;https://dl.acm.org/doi/abs/10.1145/3410530.3414320</p> <p>- The vibration signal is applied with&nbsp;event detection to extract events in the vibration signal. For each event, we normalize it by its energy, then extract 10~490 Hz frequency amplitude as the feature.</p> <p>&nbsp;</p> <p>Disclaimer: Both event detection and feature extraction are empirical, we don&#39;t guarantee it is an optimal one.</p>