Basic Reaserch for Estimation of Blood Pressure Using Neural Networks in a Remote Monitoring System of Patients Implanted an Artificial Heart.

DOI 1 Citations 7 References
  • Okamoto E
    北海道東海大学大学院理工学研究科
  • Suzuki S
    北海道東海大学大学院理工学研究科
  • Baba K
    北海道東海大学大学院理工学研究科
  • Fukuoka S
    北海道東海大学大学院理工学研究科
  • Iwasawa E
    北海道東海大学大学院理工学研究科
  • Mitamura Y
    北海道大学大学院工学研究科

Bibliographic Information

Other Title
  • 人工心臓装着患者の血行動態のニューラルネットワークによる遠隔的推定の基礎研究

Search this article

Abstract

We have developed a new estimation method that uses neural networks within the remote monitoring system of artificial heart implants, which estimates blood pressure based on artificial heart driving data (motor current and motor rotational angle data). The blood pressure is estimated by separating the mean pressure component from the pulsatile pressure component and by calculating each pressure component with respect to the corresponding neural network. Neural networks learn by means of referring to the actual blood pressure of patients leave the hospital, neural networks estimate blood pressure by using artificial heart driving data that have been transmitted by a PHS (personal handy phone system). Results of in vitro experiments show that blood pressure in mock circulation can be estimated with excellent results in the cases of a change in the pump drive rate, change in arterial resistance, or a malfunction of an artificial heart actuator. These results demonstrate that estimation of the blood pressure using neural networks is effective for a remote monitoring system of patients with artificial heart implants.

Journal

  • Jinko Zoki

    Jinko Zoki 29 (2), 308-314, 2000

    JAPANESE SOCIETY FOR ARTIFICIAL ORGANS

Citations (1)*help

See more

References(7)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top