Dataset: Toothbrushing Data and Analysis of its Potential Use in Human Activity Recognition Applications
- 1. Macquarie University, Australia
- 2. Rutgers University, USA
- 3. The University of Adelaide, Australia
Description
This is the dataset that accompanies the paper 'Dataset: Toothbrushing Data and Analysis of its Potential Use in Human Activity Recognition Applications'.
In this paper, we describe and analyze a time-series dataset from toothbrushing activity using brush-attached and wearable sensors. The data was collected from 17 participants when they brushed their teeth over one week in 5 different locations. The dataset consists of 62 toothbrushing sessions for each of the brush-attached and wearable sensor approaches, using both electric and manual brushes. The average duration of each session is 2 minutes. One sensor device was attached to the handle of the brush while the other was worn by the participants as a wrist-watch. We collected the data from a 3-axis accelerometer and a 3-axis gyroscope at a 200 Hz sampling rate.
Accompanying code can be found at our GitHub repository https://github.com/icl-mq/toothbrushing-dataset. This repository contains example code demonstrating how to process the data along with the file metadata.
Notes
Files
Zawar_Hussain-Toothbrushing_Data_and_Analysis_of_its_Potential_Use_in_Human_Activity_Recognition_Applications.zip
Files
(108.5 MB)
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