Verification of Individual Identification Method Using Bioelectric Potential of Plant during Human Walking

Abstract

In this study, we monitored electromagnetic waves generated by human activity and investigated a method for individual identification by looking at the bioelectric potential of a rubber tree. Four subjects were asked to walk in place at a distance of 60 cm from a rubber tree while we measured variations in the bioelectric potential of the tree as produced by the stepping. The results confirmed that electromagnetic waves generated by a human subject walking in place produce a measurable response in the bioelectric potential of a plant. It was also found that this variation in bioelectric potential varies in synchrony with each subject's walking pace. The spectral envelope of the observed signal was approximated using a straight line and the distribution of the coefficients of this line was plotted. Even for a simple straight-line approximation, we demonstrated that this coefficient distribution varies considerably among individual subjects.

Investigation of the Surrounding Environment′s Influence on Gait Sensing Using a Plant as a Sensor

“…We examined the influence that a person stepping on the spot exerted on the bioelectric potential of the plant. Figures 1,2,3,and 4 show the variations in the measured bioelectric potential for four different stepping rates (corresponding to step periods of 0.6, 0.8, 1.0, and 1.2 seconds); the subjects took five steps at each rate. Subjects took a 5-second break between changes in the stepping rate.…”

“…This is known as the bioantenna phenomenon and it has been confirmed in animals. In order to reduce the influence of the intrinsic bioelectric potential, we used a plant with a comparatively small bioelectric potential as the receiver, and succeeded in extracting the bioelectric potential of a human body [4].…”

Biometric Recognition: An Overview

“…3.10 ). Several other physiological characteristics that have been extracted for the purpose of biometric identifi cation include arterial pulse (Joshi et al 2008 ;Irvine et al 2008 ) , fi ngernails (Topping et al 1998 ) , odour (Ramus and Eichenbaum 2000 ) , bioelectric potential (Hirobayashi et al 2007 ) , knee x-rays (Shamir et al 2009 ) , frontal sinus (Falguera et al 2008 ;Tabor et al 2009 ) , and otoacoustic emissions (Swabey et al 2004 ) . These efforts explore and identify additional sources of soft biometrics to either improve the performance of traditional (hard) biometric modalities or to help provide identifi cation in the absence of primary biometric attributes.…”