A NEW SYSTEM FOR MEASUREMENT OF THE PULSE TRANSIT TIME, THE PULSE WAVE VELOCITY AND ITS ANALYSIS

被引:7
|
作者
Bereksi-Reguig, Anes. [1 ]
Bereksi-Reguig, F. [1 ]
Ali, A. Nait [2 ]
机构
[1] Univ Tlemcen, Fac Technol, Dept Biomed Engn, Biomed Engn Res Lab, Chetouane, Algeria
[2] Univ Paris Est, LISSI Lab, Creteil, France
关键词
Pulse wave velocity; heart rate variability; electrocardiogram; photoplethysmogram; regression models; HEART-RATE;
D O I
10.1142/S0219519417500105
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Arterial stiffness is a strong determinant of cardiovascular risk. Pulse wave velocity (PWV) is an index of arterial stiffness, and its prognostic value has been repeatedly emphasized. The work presented in this paper is concerned with the design of a new system for measurement of the PWV and analysis. It is in fact related to the description of the hardware setup and the software development in order to measure and analyze the PWV. In the proposed system, the determination of the PWV is carried out through the measurement of the pulse wave transit time (PWTT) using the electrocardiogram (ECG) and the photoplethysmogram (PPG) and the distance separating the site of ejection of the systolic pulse and the site of measuring the PPG signal. The hardware setup therefore consists of an optical device to detect the PPG and electrodes to detect ECG, and different boards to process and digitalize these signals to be acquired in the PC and analyzed. The developed software is concerned with first, the acquisition and processing of both ECG and PPG signals then the determination of the PWV and finally its analysis for different subjects and conditions. The analysis of the PWV is carried out for subjects of different ages in different physiological conditions according to heart activity. The obtained results show that there is a high correlation (r = 0.88), between heart rate variability (HRV) and PWV. They also show that PWV increases with age. The analysis of the PWV variations with age is also carried out through different regression models. The obtained result shows that the cubic regression model best fits these variations.
引用
收藏
页数:20
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