| Autor: |
Murtadha Aldeer, Wei Emma Zhang, David Waterworth, Quan Z. Sheng, Zawar Hussain |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
DATA@SenSys |
| Popis: |
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. Most of the data has been labelled. We investigated the characteristics of the data using spectral analysis and performed a pre-processing pipeline in order to generate features used to train a Support Vector Machine Classifier. We were able to identify which part of the jaw was being brushed with 98.6% accuracy. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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