Abstract
This paper presents a method of human identification based on ensemble empirical mode decomposition (EEMD) of an one-lead electrocardiogram (ECG) signal and by box approximation geometry of reconstructed attractors in latent space of a signal measured by an accelerometer located on the waist. Preprocessing of the ECG signal eliminates effects of noise and heart rate variability. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and significant heartbeat signal features are extracted using Welch spectral analysis. Human gait is considered a dynamical system and the features are the eigenvalues of the reconstructed attractor in the odd principal dimensions obtained using the Singular Spectrum Analysis methodology. The K-nearest neighbours (K-NN) method is applied as the classifier tool.
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© 2015 Springer International Publishing Switzerland
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Luetić, I., Celić, L., Batoš, V., Magjarević, R. (2015). Human Identification by Simultaneous Recording of Acceleration and ECG Data. In: Lacković, I., Vasic, D. (eds) 6th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-319-11128-5_10
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DOI: https://doi.org/10.1007/978-3-319-11128-5_10
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11127-8
Online ISBN: 978-3-319-11128-5
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