Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30121
The Relationship between Fluctuation of Biological Signal: Finger Plethysmogram in Conversation and Anthropophobic Tendency

Authors: Haruo Okabayashi


Human biological signals (pulse wave and brain wave, etc.) have a rhythm which shows fluctuations. This study investigates the relationship between fluctuations of biological signals which are shown by a finger plethysmogram (i.e., finger pulse wave) in conversation and anthropophobic tendency, and identifies whether the fluctuation could be an index of mental health. 32 college students participated in the experiment. The finger plethysmogram of each subject was measured in the following conversation situations: Fun memory talking/listening situation and regrettable memory talking/ listening situation for three minutes each. Lyspect 3.5 was used to collect the data of the finger plethysmogram. Since Lyspect calculates the Lyapunov spectrum, it is possible to obtain the largest Lyapunov exponent (LLE). LLE is an indicator of the fluctuation and shows the degree to which a measure is going away from close proximity to the track in a dynamical system. Before the finger plethysmogram experiment, each participant took the psychological test questionnaire “Anthropophobic Scale.” The scale measures the social phobia trend close to the consciousness of social phobia. It is revealed that there is a remarkable relationship between the fluctuation of the finger plethysmography and anthropophobic tendency scale in talking about a regrettable story in conversation: The participants (N=15) who have a low anthropophobic tendency show significantly more fluctuation of finger pulse waves than the participants (N=17) who have a high anthropophobic tendency (F (1, 31) =5.66, p<0.05). That is, the participants who have a low anthropophobic tendency make conversation flexibly using large fluctuation of biological signal; on the other hand, the participants who have a high anthropophobic tendency constrain a conversation because of small fluctuation. Therefore, fluctuation is not an error but an important drive to make better relationships with others and go towards the development of interaction. In considering mental health, the fluctuation of biological signals would be an important indicator.

Keywords: Anthropophobic tendency, finger plethymogram, fluctuation of biological signal, LLE.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 842


[1] J.L. Feldman, G.S. Mitchell, and E.E. Nattie, “Breathing: Ryhthmicity, plasticity, chemosensitivity,” Annual Review of Neuroscience, vol.26, no.1, pp. 239-266, 2003.
[2] I. Cygankiewicz, W. Zareba, R. Vazquez, M. Vallverdu, J.R. Gonzalez-Juanatey, M. Valdes, J. Almendral, J. Cinca, P. Caminal, and A.B. de Luna, “Heart rate turbulence predicts all-cause mortality and sudden death in congestive heart failure patients,” Heart Rhythm, vol.5, no.8, pp. 1095-1102, 2008.
[3] A.D. Kuo, “Stabilization of lateral motion in passive dynamic walking,” International Journal of Robotics Research, vol.18, no.9, pp. 917-930, 1999.
[4] K.G. Pearson, “Proprioceptive regulation of locomotion,” Current Opinion Neurobiology, vol.5, pp. 786-791, 1995.
[5] S.L. Hooper, Central pattern generators, John Wiley & Sons, 19, Apr., 2001; doi: 10.1038/npg.els.0000032.
[6] Y. Kuramoto, Nonlinear science: Synchronizing world. Tokyo: Shuei-sha, 2014.
[7] H. Koori and Y. Morita, Dynamical system approach to biological rhythms. Tokyo: Kyoritsu-shuppan, 2011.
[8] X. Zeng, R. Eykholt, and R.A. Pielke, “Estimating the Lyapunov-exponent spectrum from short time series of low precision.” Physical Review Letters, vol.66, no.25, pp. 3229-3232, 1991.
[9] H. Kantz, “A robust method to estimate the maximal Lyapunov exponent of a time series.” Physics Letters A, vol.185, pp.77-87, 1994.
[10] M.T. Rosenstein, J.J. Collins, and C.J. De Luca, “A practical method for calculating largest Lyapunv exponents from small data sets.” Physica D: Nonlinear Phenmena, vol.65, pp.117-134, 1993.
[11] M. Oyama-Higa, T. Miao, and Y, Mizuno-Matsumoto, “Analysis of dementia in aged subjects through chaos analysis of fingertip pulse wave,” in 2006 IEEE Conference on Systems, Man, and Cybernetics, Taipei, Taiwan, 2006, pp. 2863-2867.
[12] U. Bronfenbrenner, “Ecology of the family as a context for human development: Research perspectives,” Developmental Psychology, vol.22, no.6, Nov. pp. 723-742, 1986.
[13] M.L. Knapp, J.A. Hall, and T.G. Horgan, Nonverbal communication in human interaction. Boston, MA: Wadsworth, 2007.
[14] T. Horii and K. Ogawa, “The construction of a scale for the measurement of anthrophobic tendency,” Psychological Report of Sophia University, vol. 20, pp. 55–65, 1996.
[15] T. Horii and K. Ogawa, “The construction of a scale for the measurement of anthrophobic tendency (Second report),” Psychological Report of Sophia University, vol. 21, pp. 43–51, 1997.
[16] American Psychiatric Association, Diagnostic and statistical manual of mental disorders, 4th ed. Washington, DC: American Psychiatric Association, 1994.
[17] A. Ellis, Reason and emotion in psychotherapy. New York: Stuart, 1962.
[18] M. Sano and Y. Sawada, “Measurement of the Lyapunov spectrum from a chaotic time series,” Physical Review Letters, vol. 55, p. 1082, 1985.
[19] F. Takens, “Detecting strange attractors in turbulence,” Lecture Notes in Mathematics, 898, Berlin: Springer-Verlag, 1981.
[20] H. Whitney, “Differentiable manifolds,” Annals of Mathematics, vol. 37, pp. 645–680, 1936.
[21] T.D. Sauer, Attractor reconstruction, Scholarpedia, vol.1, no.10, p. 1727, 2006. doi:10.4249/scholarpedia.1727
[22] B. Pomeranz, R.J. Macaulay, M.A. Caudill, L. Kutz, D. Adam, D. Gordon, K.M. Kilborn, A.C. Barger, D.C. Shannon, R.J. Cohen, and H. Benson, “Assessment of autonomic function in humans by heart rate spectral analysis,” American Journal of Physiology-Heart and Circulatory Physiology, vol. 248, pp. H151-H153, 1998.
[23] C. M. Lee, R.H. Wood, and M.A. Welsch, “Influence of head-down and lateral decubitus neck flexion on heart rate variability,” Journal of Applied Physiology, vol. 90, no.1, pp.127-132.
[24] T. Fuwa, “The accuracy of evaluation of autonomic nervous system activity by heart rate variability under natural respiration and controlled respiration,” Bulltein of Polytechnic University, no. 41-A, pp.7-12, 2012.
[25] Y. Sawada and F. Ishida, “Rhythm and sensory-motor control,” in The world of rhythmic phenomena, Y. Kuramoto, Ed. Tokyo: University of Tokyo Press, 2013, pp. 97-135.