Detecting and Quantifying T Wave Alternans Using Linear Least Squares Curve Fitting Method

2012 ◽  
Vol 239-240 ◽  
pp. 1404-1408
Author(s):  
Xiang Kui Wan ◽  
Kang Hui Yan ◽  
Ming Gui Li
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Moving Average ◽  
Correlation Coefficients ◽  
Linear Least Squares ◽  
T Wave ◽  
Patients At Risk ◽  
Invasive Method ◽  
T Wave Alternans ◽  
Curve Fitting Method

Evaluatement of T-wave alternans (TWA) is a non-invasive method to identify patients at risk for sudden cardiac death. A novel time-domain algorithm based on linear least squares method (LSM) for TWA analysis is developed in this paper. And the LSM’s ability to TWA analaysis in comparison with the modified moving average (MMA) method was demonstrated. In a simulation study LSM and MMA can both detected TWA with high accuracy, but under lower SNR levels LSM was found more robust, and its evaluated TWA values are closer to true TWA value. The algorithm was subsequently used to analyze the clinical ECGs from T-Wave Alternans Challenge Database, which showed that the results from this method vs. MMA had the correlation coefficients of 0.89.

Improved modified moving average analysis of T-wave alternans using least squares-based curve fitting method

2014 ◽  
Vol 07 (04) ◽  
pp. 1450044 ◽  
Author(s):  
Xiang-Kui Wan ◽  
Kang-Hui Yan ◽  
Ang Li ◽  
Ming-Hu Wu
Keyword(s):  
Curve Fitting ◽  
Moving Average ◽  
Least Square Method ◽  
Least Square ◽  
T Wave ◽  
Fitting Method ◽  
Average Analysis ◽  
T Wave Alternans ◽  
Improved Performance ◽  
Curve Fitting Method

T-wave alternans (TWA) in surface electrocardiograph (ECG) signal is considered a marker of abnormal ventricular function which may be associated with ventricular tachycardia. Several methods have been developed in recent years to evaluate the important feature. One such method is known as modified moving average (MMA) analysis, which performs well for different levels of TWA, but it is sensitive to the noise in T-waves. In this paper we propose an improved MMA algorithm, which adds a stage of T-wave curve fitting for the MMA method before intermediate averaging. The curve fitting is performed by means of least square method technique. Our assessment study demonstrates the improved performance.

scholarly journals GM(1,1;λ) with Constrained Linear Least Squares

Axioms ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 278
Author(s):  
Ming-Feng Yeh ◽  
Ming-Hung Chang
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Model Fitting ◽  
Ordinary Least Squares ◽  
Linear Least Squares ◽  
Unknown Parameters ◽  
Constrained Problems ◽  
Linear Least Squares Problems ◽  
Ordinary Least Squares Method ◽  
Better Than

The only parameters of the original GM(1,1) that are generally estimated by the ordinary least squares method are the development coefficient a and the grey input b. However, the weight of the background value, denoted as λ, cannot be obtained simultaneously by such a method. This study, therefore, proposes two simple transformation formulations such that the unknown parameters, and can be simultaneously estimated by the least squares method. Therefore, such a grey model is termed the GM(1,1;λ). On the other hand, because the permission zone of the development coefficient is bounded, the parameter estimation of the GM(1,1) could be regarded as a bound-constrained least squares problem. Since constrained linear least squares problems generally can be solved by an iterative approach, this study applies the Matlab function lsqlin to solve such constrained problems. Numerical results show that the proposed GM(1,1;λ) performs better than the GM(1,1) in terms of its model fitting accuracy and its forecasting precision.

Beam closed orbit correction and feedback by constrained linear least squares method in Hefei light source

2010 ◽  
Vol 22 (1) ◽  
pp. 155-158
Author(s):  
宣科 Xuan Ke ◽  
王琳 Wang Lin ◽  
李川 Li Chuan ◽  
李为民 Li Weimin ◽  
王季刚 Wang Jigang ◽  
...  
Keyword(s):  
Least Squares ◽  
Light Source ◽  
Least Squares Method ◽  
Closed Orbit ◽  
Linear Least Squares ◽  
Orbit Correction

scholarly journals Ellipse Coefficient Map-Based Geomagnetic Fingerprint Considering Azimuth Angles

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 708
Author(s):  
Ju-Hyeon Seong ◽  
Seung-Hyun Lee ◽  
Kyoung-Kuk Yoon ◽  
Dong-Hoan Seo
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Azimuth Angle ◽  
High Signal ◽  
Linear Least Squares ◽  
Positioning Accuracy ◽  
Signal Stability ◽  
Novel Approach ◽  
Magnetic Vectors ◽  
Equalization Method

Geomagnetic fingerprint has been actively studied because of the high signal stability and positioning resolution even when the time has elapsed. However, since the measured three-axis geomagnetism signals at one position are irregular according to the change of the azimuth angle, a large-sized database which is stored magnitudes per angles is required for robust and accurate positioning against the change of the azimuth angle. To solve this problem, this paper proposes a novel approach, an elliptic coefficient map based geomagnetic fingerprint. Unlike the general fingerprint, which stores strength or magnitude of the geomagnetism signals depending on the position, the proposed algorithm minimized the size of databased by storing the Ellipse coefficient map through the ellipse equation derived from the characteristics of 2-D magnetic vectors depending on the position. In addition, the curvature bias of ellipse was reduced by applying the normalized linear least-squares method to 2-D geomagnetic characteristics and the positioning accuracy was improved by applying the weighted geomagnetic signal equalization method.

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