Yet another new biometric recognition based on hand tremors acquired from leapmotion device

Published: 5 November 2017| Version 2 | DOI: 10.17632/8j9gs37r4c.2
Musa Ataş


This dataset is partly associated to the "Hand Tremor Based Biometric Recognition Using Leap Motion Device" paper (doi: 10.1109/ACCESS.2017.2764471 ). If you think this new dataset is useful for your studies please cite our paper above. Objective is to investigate whether hand jitter can be treated as a new behavioral biometric recognition trait in the filed od security so that imitating and/or reproducing artificially can be avoided.Dataset contains five subjects. 1024 samples each subject's spatiotemporal hand tremor signals as a time series data were acquired via leap motion device. Features are X, Y, Z and Mixed (Average) channels. Channel represents displacement value of adjacent frames (difference between current and previous positions) and finally the last item is class label having value from 1 to read the "Hand Tremor Based Biometric Recognition Using Leap Motion Device" paper for more details and feature extraction methods. If you have any questions related to the preprocessing and/or processing the dataset please do not hesitate to contact with me via e-mail: . It should be noted that, data acquisition software was implemented in Java (Netbeans) and I utilized Processing, Open Cezeri Library and Weka tools alongside.


Steps to reproduce

Use leapmotion device to acquire hand tremor data. Hold your right hands 20 cm above the leapmotion.


Security, Biometrics, Tremor, Classification System