| Project/Area Number |
09680868
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Biomedical engineering/Biological material science
|
|---|
| Research Institution | Hosei University |
|---|
Principal Investigator |
YANA Kazuo Hosei University, Faculty of Engineering, Professor, 工学部, 教授 (50138244)
|
|---|
| Project Period (FY) |
1997 – 1998
|
| Project Status |
Completed (Fiscal Year 1998)
|
| Budget Amount *help |
¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1998: ¥500,000 (Direct Cost: ¥500,000)
|
|---|
| Keywords | Heart Rate Variability / Respiration / Blood Pressure / Adaptive Signal Processing / RLS algorithm / Spectral Analysis / Autonomic Nervous System / Fluctuations Analysis / 信号処理 / 1 / fゆらぎ / 時系列解析 / 非線形 / シミュレーション / 多次元ARモデル / ニューラルネットワーク |
|---|
| Research Abstract |
Heart rate fluctuations (HRF) has been recognized as a non-invasive mean to access the autonomic nervous activity. Spectral analysis has been dominated for the analysis. Recently, some attempts have been made to relate HRF with other physiologic quantities such as the instantaneous lung volume (ILV) and/or blood pressure (BP) for more precise characterization of the HRF. This study proposes a method for extracting "genuine" heart rate fluctuations (HRF) separating from distinct respiratory and blood pressure originated fluctuations in HRF. It has been confirmed first by computer simulation that the noise injection method stabilize the estimate of transfer characteristics from HRF to ILV and from HRF to BP and the adaptive signal canceling method can be effectively applied for extracting the genuine heart rate fluctuations independent from respiration and blood pressure change. Real data analysis for 14 healthy normal male adults revealed that this cancellation technique is effective in characterizing the HRF removing the uncertainty caused by a large individual variations due to the ILV and BP component in the HRF. The method will be effectively applied for the consistent and stable estimates of the autonomic nervous activity. The method may also be useful in evaluating man-machine interface.
|
