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A Future Prediction Type Artificial Heart System
Author(s) -
Yambe Tomoyuki,
Tanizuka Noboru,
Tanaka Akira,
Yoshizawa Makoto,
Abe Kenichi,
Takeda Hiroshi,
Tabayashi Kouichi,
Nitta Shinichi
Publication year - 1999
Publication title -
artificial organs
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.684
H-Index - 76
eISSN - 1525-1594
pISSN - 0160-564X
DOI - 10.1046/j.1525-1594.1999.06321.x
Subject(s) - preload , artificial heart , autonomic nervous system , term (time) , autonomic nerve , artificial neural network , heart rate , mathematics , computer science , cardiology , medicine , hemodynamics , artificial intelligence , blood pressure , physics , quantum mechanics
The demand of the biological system needs to be predicted to consider the quality of life (QOL) of a patient with an artificial heart system. The purpose of this study was the prediction of the imminent cardiac output and the predictive control for an artificial heart. For that purpose, autonomic nerve information was applied in this study. Nervous sympathicus action potentials were measured, and a prediction function of cardiac output was made using the sympathetic tone and preload and afterload measurement with multiple regression analysis. The predicted value showed significant correlation with the measured value after 2.9 s. Currently, however, long‐term instrumentation of the nervous sympathicus potential is difficult. Thus, hemodynamic fluctuations, which recently have attracted attention, were used in this study. A prediction function using the Mayer wave, which represented nervous sympathicus, was determined. As a result, mid‐term prediction became possible. Furthermore, a measurement of the vagal nerve was used as a possible long‐term prediction parameter. For long‐term prediction, Hurst exponent analysis was used in this study. Vagal nerve discharges in the changing position showed alteration of long‐term determination. In conclusion, the future prediction control of an artificial heart takes shape using these prediction functions.