Spatio temporal chaos and local determinism of ECG-PPG

2019 Fiscal Year Final Research Report

• Project/Area Number: 16K15016
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Agricultural environmental engineering/Agricultural information engineering
• Research Institution: Tokyo University of Agriculture and Technology
• Principal Investigator: Sakai Kenshi 東京農工大学, (連合)農学研究科(研究院), 教授 (40192083)
• Project Period (FY): 2016-04-01 – 2020-03-31
• Keywords: 心電 / 脈波 / カオス解析 / 位相解析 / ヒルベルト変換 / ポアンカレ断面

Outline of Final Research Achievements

ECG-Pulse wave ECGc signals were used to generate pulsating Poincare sections. With this method, it was possible to observe a clearer structure with less fluctuation than in the case of generating only from the pulse wave. By focusing on the QS interval of ECG and setting a time delay to 1/4 of that, the clear dynamics of the electrocardiogram were reconstructed. Nonlinear time series analysis methods such as transition error and normalized deterministic nonlinear prediction can be applied to ECG signals, and the existence of high determinism can be detected. On the other hand, the versatility of the phase synchronization extraction method developed for electrocardiogram-pulse wave was clarified. It was also effective for metadata such as RGB image sequences, allergic pollen dispersal amounts, and spatio-temporal distribution of infectious diseases.

Free Research Field

農業環境工学

Academic Significance and Societal Importance of the Research Achievements

農作業においては強い労働負荷過程の下でのリアルタイムでの計測が必要である。本研究は、ウェアラブルの心電―脈波センサーを用いて、農作業下データにおいても信号データからのダイナミクス同定をより高精度で行うことを可能とした。ここで得られた解析手法は汎用性が高く、生体情報への応用だけではなく、RGB画像列、生態系データなどへの汎用性も確認できた。