Reduction of interference in oscillometric arterial blood pressure measurement using fuzzy logic

Abstract

In oscillometry, oscillation amplitudes (OAs) embedded in the cuff pressure are drastically affected by a variety of artifacts and cardiovascular diseases, leading to inaccurate arterial blood pressure (ABP) measurement. The purpose of this paper is to improve the accuracy in the arterial pressure measurement by reducing interference in the OAs using a recursive weighted regression algorithm (RWRA). This method includes a fuzzy logic discriminator (FLD) and a recursive regression algorithm. The FLD is used to reduce the effect of artifacts caused by measurement motion disturbance or cardiovascular diseases, and to determine the truthfulness of the oscillation pulse. According to the truth degree, the relationship between the cuff pressure and OA is reconstructed using the regression algorithm. Because the regression method must utilize inverse matrix operation, which will be difficult to implement in an automatic or ambulatory monitor, the recursive regression method is proposed to solve this problem. To test the performance of this RWRA, 47 subjects underwent the ABP measurement using both the auscultation and the oscillometry combined with the RWRA. It was found that the average difference between the pooled blood pressures measured by the auscultation and those by the oscillometry combined with the RWRA was found to be only 4.9 mmHg. Clinical results demonstrated that the proposed RWRA is more robust than the traditional curve fitting algorithm (TCFA). We conclude that the proposed RWRA can be applied to effectively improve the accuracy of the oscillometric blood pressure measurement.

Novel methods of testing and calibration of oscillometric blood pressure monitors

“…Popular methods in recent years include linear or polynomial models [ 19 ], generalised curve fitting [ 20 ], or the fitting of asymmetric Gaussian or Lorentzian functions [ 21 ]. Curve fitting can also be supplemented using artificial neural network [ 22 ] or fuzzy logic [ 23 ] to minimise the MSE.…”

Mathematical biomarkers for the autonomic regulation of cardiovascular system

“…Also based on R-R features, fuzzy logic was used for ECG beat classification to detect arrhythmic and ischemic heartbeats (Tsipouras et al, 2007). Fuzzy logic approaches showed efficiency in improving oscillometric cuff pressure measurements by properly detecting outliers and noise artifacts (Lin et al, 2003). …”

Algoritma Interpolasi Nearest-Neighbor untuk Pendeteksian Sampul Pulsa Oscilometri Menggunakan Mikrokontroler Berbiaya Rendah

“…Sampul gelombang oscilometri digunakan untuk menemukan puncak pulsa oscilometri dimana nilai puncak ini adalah nilai MAP [16]. Sementara nilai DBP dan SBP ditentukan melalui rasio berkisar dari 0,5 sampai 0,8 terhadap MAP [12].…”

“…Proses pembentukan gelombang dan sampul oscilometri [15] Gambar 2. Penentuan MAP, SBP, dan DBP dari sampul gelombang dan pulsa oscilometri [16] pada posisi dalam rentang x tertentu dengan memberikan nilai yang sama dengan nilai titik yang diketahui posisinya tadi seperti yang dijelaskan pada Persamaan (1) [17].…”