1987 Fiscal Year Final Research Report Summary
Mathematical Model of Arrhythmia Generating mechanism Besed on the Modulated Parasystole Theory
| Project/Area Number |
60870087
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| Research Category |
Grant-in-Aid for Developmental Scientific Research
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| Allocation Type | Single-year Grants |
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| Research Field |
医学一般
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| Research Institution | University of Tokyo |
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Principal Investigator |
IKEDA Kenji Faculty of Medicine, University of Tokyo, 医学部, 助手 (70010030)
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| Co-Investigator(Kenkyū-buntansha) |
AOKI Takao Faculty of Medicine, University of Tokyo, 医学部, 文部技官 (00101113)
TANAKA Hiroshi Hamamatsu University School of Medicine, 医療情報部, 助教授 (60155158)
FURUKAWA Toshiyuki Research Center for Advanced Science and Technology, University of Tokyo, 先端科学技術研究センター, 教授 (20101082)
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| Project Period (FY) |
1985 – 1987
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| Keywords | mathematical model of arrhymia / non-linear synchronization theory / ectopic excitation genration / finite element method / 逆問題解法 / 心房 / 心室センシング |
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| Research Abstract |
A mathematical model of the cardiac conduction system has been developed in order to clarify the mechanisms of cardiac arrhythmia. The model is consist of the network of elements which simulate the conductivity chatacteristics of the heart muscle scintidium, where each element is defines by a unique set of time parameters from the action potential. The mathematical desctiption is separated from the network structure, and defined ad a non-linear synchronization theory, thus making is possible to rum the model with different network sizes, and to apply the finite element method for precise modeling. In addition, id became possible to construct together an a prio'ri knowledge about the relationship between cardiac cell metabolism and ion channel function. The details of the model consist of three parts, i.e., impulse progaration, ectopic excitation generation mechanism and electopotential generation. In the inverse solution approach, the arrival time disteibution of excitation front within cardiac scintidium cell structure were calculated from the data of body surface potential distributions. Referring to the conduction process model, the parameters is estimated from the above same data. Conclusively, it is believable that modeling of the different mechanisms which cause cardiac arrhythmias is an important area and that the model has been shown to be useful not only for basic understaunding of cardiac electric physiology, but also for the savelopment of frontier technology of an automated atthythmia recognition and a simultaneous defibrillation treatment, for an example, the improvement of atrioventriculat sensing monitor.
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