Description
Mobile devices especially smartphones have gained high popularity and become a part of daily life in recent years. Smartphones have built-in motion sensors such as accelerometer, gyroscope and orientation sensors. Recent researches on smartphones show that behavioral biometrics can be obtained from the smartphone motion sensors. In this context, we develop an Android application that collects accelerometer sensor data while user playing a game. This application records all accelerometer data and touch event information while users touch the screen. We perform two experiments and collect two different data using this application. In the first experiment, we collect data from 107 child users whose age vary from 4 to 11, and 100 adult users whose age are between 16 and 55. This dataset includes more than 11.000 taps data for child and adult users, in total. In the second experiment, data is collected from 60 female and 60 male users aged 17-57 for different activities like sitting and walking. There are more than 6.000 taps data for sitting and walking scenarios separately in the second dataset. We use popular Android smartphones in the experiments and they have all 100 Hz sampling rate. These data can be used for behavioral biometric analyses such as user age group and gender detection, user identification and authentication or tap event detection
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Publication Details
Subfield
Computer Vision and Pattern Recognition
Field
Computer Science
Domain
Physical Sciences
Confidence Score
49%
Source
Open Alex