{"title":"The Relationship between Fluctuation of Biological Signal: Finger Plethysmogram in Conversation and Anthropophobic Tendency","authors":"Haruo Okabayashi","volume":117,"journal":"International Journal of Humanities and Social Sciences","pagesStart":3228,"pagesEnd":3233,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10005707","abstract":"<p>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 &ldquo;Anthropophobic Scale.&rdquo; 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 (<em>N<\/em>=15) who have a low anthropophobic tendency show significantly more fluctuation of finger pulse waves than the participants (<em>N<\/em>=17) who have a high anthropophobic tendency (<em>F<\/em> (1, 31) =5.66, <em>p<\/em>&lt;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.<\/p>\r\n","references":"[1]\tJ.L. Feldman, G.S. Mitchell, and E.E. Nattie, \u201cBreathing: Ryhthmicity, plasticity, chemosensitivity,\u201d Annual Review of Neuroscience, vol.26, no.1, pp. 239-266, 2003.\r\n[2]\tI. Cygankiewicz, W. Zareba, R. Vazquez, M. Vallverdu, J.R. Gonzalez-Juanatey, M. Valdes, J. Almendral, J. Cinca, P. Caminal, and A.B. de Luna, \u201cHeart rate turbulence predicts all-cause mortality and sudden death in congestive heart failure patients,\u201d Heart Rhythm, vol.5, no.8, pp. 1095-1102, 2008.\r\n[3]\tA.D. Kuo, \u201cStabilization of lateral motion in passive dynamic walking,\u201d International Journal of Robotics Research, vol.18, no.9, pp. 917-930, 1999.\r\n[4]\tK.G. Pearson, \u201cProprioceptive regulation of locomotion,\u201d Current Opinion Neurobiology, vol.5, pp. 786-791, 1995.\r\n[5]\tS.L. Hooper, Central pattern generators, John Wiley & Sons, 19, Apr., 2001; doi: 10.1038\/npg.els.0000032. \r\n[6]\tY. Kuramoto, Nonlinear science: Synchronizing world. Tokyo: Shuei-sha, 2014.\r\n[7]\tH. Koori and Y. Morita, Dynamical system approach to biological rhythms. Tokyo: Kyoritsu-shuppan, 2011.\r\n[8]\tX. Zeng, R. Eykholt, and R.A. Pielke, \u201cEstimating the Lyapunov-exponent spectrum from short time series of low precision.\u201d Physical Review Letters, vol.66, no.25, pp. 3229-3232, 1991.\r\n[9]\tH. Kantz, \u201cA robust method to estimate the maximal Lyapunov exponent of a time series.\u201d Physics Letters A, vol.185, pp.77-87, 1994.\r\n[10]\tM.T. Rosenstein, J.J. Collins, and C.J. De Luca, \u201cA practical method for calculating largest Lyapunv exponents from small data sets.\u201d Physica D: Nonlinear Phenmena, vol.65, pp.117-134, 1993.\r\n[11]\tM. Oyama-Higa, T. Miao, and Y, Mizuno-Matsumoto, \u201cAnalysis of dementia in aged subjects through chaos analysis of fingertip pulse wave,\u201d in 2006 IEEE Conference on Systems, Man, and Cybernetics, Taipei, Taiwan, 2006, pp. 2863-2867. \r\n[12]\tU. Bronfenbrenner, \u201cEcology of the family as a context for human development: Research perspectives,\u201d Developmental Psychology, vol.22, no.6, Nov. pp. 723-742, 1986.\r\n[13]\tM.L. Knapp, J.A. Hall, and T.G. Horgan, Nonverbal communication in human interaction. Boston, MA: Wadsworth, 2007.\r\n[14]\tT. Horii and K. Ogawa, \u201cThe construction of a scale for the measurement of anthrophobic tendency,\u201d Psychological Report of Sophia University, vol. 20, pp. 55\u201365, 1996.\r\n[15]\tT. Horii and K. Ogawa, \u201cThe construction of a scale for the measurement of anthrophobic tendency (Second report),\u201d Psychological Report of Sophia University, vol. 21, pp. 43\u201351, 1997.\t\r\n[16]\tAmerican Psychiatric Association, Diagnostic and statistical manual of mental disorders, 4th ed. Washington, DC: American Psychiatric Association, 1994.\r\n[17]\tA. Ellis, Reason and emotion in psychotherapy. New York: Stuart, 1962.\r\n[18]\tM. Sano and Y. Sawada, \u201cMeasurement of the Lyapunov spectrum from a chaotic time series,\u201d Physical Review Letters, vol. 55, p. 1082, 1985.\r\n[19]\tF. Takens, \u201cDetecting strange attractors in turbulence,\u201d Lecture Notes in Mathematics, 898, Berlin: Springer-Verlag, 1981.\r\n[20]\tH. Whitney, \u201cDifferentiable manifolds,\u201d Annals of Mathematics, vol. 37, pp. 645\u2013680, 1936.\r\n[21]\tT.D. Sauer, Attractor reconstruction, Scholarpedia, vol.1, no.10, p. 1727, 2006. doi:10.4249\/scholarpedia.1727\r\n[22]\tB. 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, \u201cAssessment of autonomic function in humans by heart rate spectral analysis,\u201d American Journal of Physiology-Heart and Circulatory Physiology, vol. 248, pp. H151-H153, 1998.\r\n[23]\tC. M. Lee, R.H. Wood, and M.A. Welsch, \u201cInfluence of head-down and lateral decubitus neck flexion on heart rate variability,\u201d Journal of Applied Physiology, vol. 90, no.1, pp.127-132.\r\n[24]\tT. Fuwa, \u201cThe accuracy of evaluation of autonomic nervous system activity by heart rate variability under natural respiration and controlled respiration,\u201d Bulltein of Polytechnic University, no. 41-A, pp.7-12, 2012.\r\n[25]\tY. Sawada and F. Ishida, \u201cRhythm and sensory-motor control,\u201d in The world of rhythmic phenomena, Y. Kuramoto, Ed. Tokyo: University of Tokyo Press, 2013, pp. 97-135.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 117, 2016"}