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JACIII Vol.18 No.3 pp. 297-304
doi: 10.20965/jaciii.2014.p0297
(2014)

Paper:

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An Assessment Tool for Effective Monitoring of Autonomic Nervous System Activity in Healthy People

Takuto Yanagida*, Yoshimitsu Okita**, Harunobu Nakamura***,
Toshifumi Sugiura*, and Hidenori Mimura*

*Research Institute of Electronics, Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu 432-8011, Japan

**Graduate School of Science and Technology, Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu 432-8011, Japan

***Graduate School of Human Development and Environment, Kobe University, 3-11 Tsurukabuto, Nada-ku, Kobe 657-8501, Japan

Received:
August 23, 2013
Accepted:
March 14, 2014
Published:
May 20, 2014
Creative Commons License
Keywords:
lifestyle-related diseases, autonomic nervous system activity, electrocardiogram, plethysmogram, pulse transmission time
Abstract
This paper proposes an application that analyzes and displays electrocardiograms (ECG; electrical activity of the heart over time) and plethysmograms (PTG; pulse waves produced by the heart pumping blood to the periphery) measured simultaneously. Recently in developed countries, chronic conditions typified by lifestyle-related diseases have become the leading cause of death. Simplified monitoring of the condition can be an effective approach to disease prevention and health promotion. We have focused on autonomic nervous system activity (ANSA) because it responds to stress as well as to changes in dietary patterns, and is correlated with hypertension, the source of some diseases, such as coronary disease. In this paper, we deal with both ECGs and PTGs as part of the biological data that reflects ANSA. The proposed application enables doctors to seamlessly negotiate analyzed waveforms and index charts of ECGs and PTGs in sync with each other. It also helps them comprehend the transition of ANSA. It offers a user interface (UI) that enables doctors to observe the two measures and the relationship between them for a quick assessment of ANSA; the sonification function of the ECG indices is implemented for providing the multi-modality of the UI. An experiment was conducted to confirm the feasibility of the analysis method of the application.
Cite this article as:
T. Yanagida, Y. Okita, H. Nakamura, T. Sugiura, and H. Mimura, “An Assessment Tool for Effective Monitoring of Autonomic Nervous System Activity in Healthy People,” J. Adv. Comput. Intell. Intell. Inform., Vol.18 No.3, pp. 297-304, 2014.
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