NDLI: Gender-specific velocity recognition of caress-like stimuli through nonlinear analysis of Heart Rate Variability

Content Provider	IEEE Xplore Digital Library
Author	Nardelli, M. Valenza, G. Bianchi, M. Greco, A. Lanata, A. Bicchi, A. Scilingo, E.P.
Copyright Year	2015
Description	Author affiliation: Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy (Nardelli, M.; Valenza, G.; Bianchi, M.; Greco, A.; Lanata, A.; Bicchi, A.; Scilingo, E.P.)
Abstract	This study reports on the development of a gender-specific classification system able to discern between two levels of velocity of a caress-like stimulus, through information gathered from Autonomic Nervous System (ANS) linear and nonlinear dynamics. Specifically, caress-like stimuli were administered to 32 healthy volunteers (16 males) while monitoring electrocardiogram signal to extract Heart Rate Variability (HRV) series. Caressing stimuli were administered to the forearm at a fixed force level (6 N) and two levels of velocity, 9.4 mm/s and 37 mm/s. Standard HRV measures, defined in the time and frequency domain, as well as HRV nonlinear measures were extracted during the pre- and post-stimulus sessions, and given as an input to a Support Vector Machine (SVM) classifier implementing a leave-one-subject-out procedure. Results show an accuracy of velocity recognition of 70% for the men, and 84.38% for the women, when both standard and nonlinear HRV measures were taken into account. Conversely, non-significant results were achieved considering standard measures only, or a gender-aspecific classification. We can conclude that caress-like stimuli elicitation significantly affect HRV nonlinear dynamics with a highly specific gender dependency.
Starting Page	298
Ending Page	301
File Size	1537970
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318359
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart rate variability Standards Physiology Accuracy Support vector machines Entropy Nonlinear dynamical systems
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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