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.