A New Method to Detect P-Wave Based on Quadratic Function

2011 ◽  
Vol 267 ◽  
pp. 462-467
Author(s):  
Nan Quan Zhou
Keyword(s):  
Quadratic Function ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
P Wave ◽  
Good Effect ◽  
Rate Variation ◽  
Optimal Interval ◽  
Wave Detection ◽  
Wide Range

The paper presents a P-wave detection algorithm based on fitting function in the optimal interval. In the algorithm we used quadratic function to fit the P wave by this means of least square method in every interval, which was shifted in local range. Then we found the optimal fitting interval of P wave by comparing the error of fitting. Finally, we obtained the characteristic points of P wave by using the fitting function to fit P wave in the optimal interval. The performance of the algorithm tested using the records of the MIT-BIH database was effective and accurate. The algorithm on the wide range of heart rate variation and small P wave of ECG P-wave detection has good effect. Also it has some capabilities of anti-interference, particularly the false dismissal probability is quite low.

Recursive field estimation and tracking for autonomous manipulation

Robotica ◽  
2011 ◽  
Vol 30 (5) ◽  
pp. 743-753 ◽  
Author(s):  
Soo Jeon
Keyword(s):  
Radial Basis Function Network ◽  
Least Square Method ◽  
Least Square ◽  
Source Tracking ◽  
Control Law ◽  
Task Space ◽  
Recursive Least Square ◽  
Wide Range ◽  
Field Estimation ◽  
Task Space Control

SUMMARYAutonomous operation of mechanical systems often requires the ability to detect and locate a particular phenomenon occurring in the surrounding environment. Being implemented to articulated manipulation, such a capability may realize a wide range of applications in autonomous maintenance and repair. This paper presents the sensor-driven task space control of an end-effector that combines the field estimation and the target tracking in an unknown spatial field of interest. The radial basis function network is adopted to model spatial distribution of an environmental phenomenon as a scalar field. Their weight parameters are estimated by a recursive least square method using collective measurements from the on-board sensors mounted to the manipulator. Then the asymptotic source tracking has been achieved by the control law based on the gradient of the estimated field. A new singularity tolerant scheme has been suggested to command the task space control law despite singular configurations. Simulation results using the three-link planar robot and the 6-revolute elbow manipulator are presented to validate the main ideas.

Ultrasonic Detection Algorithm Research on the Damage Depth of Concrete after Fire

2011 ◽  
Vol 368-373 ◽  
pp. 2229-2234
Author(s):  
Jiang Tao Yu ◽  
Yuan Liu ◽  
Zhou Dao Lu ◽  
Peng Zhao
Keyword(s):  
Ultrasonic Method ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Measured Data ◽  
Structural Member ◽  
Least Square ◽  
Propagation Time ◽  
Practical Application ◽  
Ultrasonic Detection ◽  
Damage Depth

To measure the depth of fire-damaged concrete by ultrasonic method, it was traditionally assumed that the concrete of the fire-damaged structural member could be simply classified into damaged layer and undamaged layer. Based on it, the damage depth can be calculated with a series of single-sided ultrasonic measured data. This method is simple and convenient but less accurate in the practical application. To improve the algorithm, hyperbola curves are adopted to simulate the varying of damage with depth in this paper. And parabolic curves are adopted to simulate the traces of ultrasonic wave in different measured distances. Therefore, the minimum propagation time can be obtained under different damage conditions. Through comparing the calculating results and measured data in different measured distances, the most likely damaged trend can be determined with least square method. At the end of this paper, examples are demonstrated to prove this algorithm feasible and more accurate than the traditional one.

Lane Detection Based on Improved Canny Detector and Least Square Fitting

2013 ◽  
Vol 765-767 ◽  
pp. 2383-2387 ◽  
Author(s):  
Guang Hua Chen ◽  
Wen Zhou ◽  
Feng Jiao Wang ◽  
Bin Jie Xiao ◽  
Sun Fang Dai
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Least Square ◽  
Edge Detector ◽  
Canny Edge Detector ◽  
Least Square Fitting ◽  
Video Images ◽  
Canny Edge ◽  
Single Pixel

The video images of road monitoring system contain noise, which blurs the difference between the lane and the background. The lane detection algorithm based on traditional Canny edge detector hardly detects the single-pixel lane accurately and it produces pseudo lane. The paper proposes an effective lane detection method based on improved Canny edge detector and least square fitting. The proposed method improves the dual-threshold selection of traditional Canny detector by using the histogram concavity analysis, which sets the optimal threshold automatically. The least square method is used to fit the feature points of detected edges to accurate and single-pixel wide lane. Experimental results show that the proposed method detects the lane of video images accurately in the noise environment.

Subpixel Edge Detection Algorithm of the Glass Bottle Based on Zernike Moments

2011 ◽  
Vol 80-81 ◽  
pp. 1345-1349
Author(s):  
Hao Yang ◽  
Lei Pei
Keyword(s):  
Edge Detection ◽  
Fast Algorithm ◽  
Least Square Method ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Zernike Moments ◽  
Least Square ◽  
Measuring System ◽  
Zernike Moment ◽  
Glass Bottle

The accuracy of edge detection determines the accuracy of actual dimension measurement，in order to improve the measuring accuracy, this paper proposes a fast algorithm of detecting the glass bottle dimension based on Zernike moments. Firstly, combines the traditional Zernike moment-based method with Otsu adaptive threshold algorithm and a new fast algorithm for edge detection is proposed. Then uses this fast algorithm to detect the edge of glass bottle with subpixel-level and uses the least square method to fit ellipses formed by the glass bottle mouth and bottom. Calibrated the system with standard gauge block and obtain the actual dimension at last. Experimental results show that the improved algorithm not only can make the edge detection reach the subpixel-level accuracy, but also can avoid the edge misidentification and inefficient causing by repeatedly manual adjustments to select the threshold value when detecting the edge. Making a rapid, accurate, non-contact measuring system becomes a reality.

scholarly journals Evaluation of Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction with Hypertension by Dynamic Electrocardiogram Feature Data

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Guoqiang Wang ◽  
Yu Wang ◽  
Ru Zhao
Keyword(s):  
Myocardial Infarction ◽  
Percutaneous Coronary Intervention ◽  
Coronary Intervention ◽  
Detection Algorithm ◽  
P Wave ◽  
St Segment Elevation ◽  
Segment Elevation Myocardial Infarction ◽  
Wave Detection ◽  
St Segment ◽  
Percutaneous Coronary

This work was to study the application value of dynamic electrocardiogram (ECG) feature data in evaluating the curative effect of percutaneous coronary intervention in acute ST-segment elevation myocardial infarction with hypertension, so as to facilitate the early diagnosis and treatment of the disease. In this study, 90 patients with acute ST-segment elevation myocardial infarction accompanied by hypertension were selected as the study subjects and randomly divided into group A (oral aspirin antiplatelet therapy), group B (thrombolytic drug streptokinase (SK) therapy), and group C (percutaneous coronary intervention), with 30 cases in each group. In addition, a P-wave detection algorithm was introduced for automatic detection and analysis of electrocardiograms, and the efficacy of patients was assessed by Holter feature data based on the P-wave detection algorithm. The results showed that the diagnostic error rate, sensitivity, and predictive accuracy of the P-wave detection algorithm for ST-segment elevation myocardial infarction caused by acute occlusion of left main coronary artery (LMCA) were 0.24%, 95.41%, and 92.33%, respectively; the diagnostic error rate, sensitivity, and predictive accuracy for non-LMCA (nLMCA) ST-segment elevation myocardial infarction were 0.28%, 95.32%, and 96.07%, respectively; the proportion of patients with symptom to blood flow patency time <3 h in group C (55.3%) was significantly higher than that in groups A and B (22.1% and 22.6%) ( P  < 0.05). Compared with group A, the content of B-type natriuretic peptide (pre-proBNP) at 1 week, 2 weeks, and 3 weeks after treatment in groups B and C was significantly lower and group C was significantly lower than group B ( P  < 0.05). In summary, the P-wave detection algorithm has a high application value in the diagnosis and early prediction of acute ST-segment elevation myocardial infarction. Percutaneous coronary intervention in the treatment of acute ST-segment elevation myocardial infarction with hypertension can shorten the opening time of infarction blood flow, so as to effectively protect the heart function of patients.

scholarly journals The Evaluation of the Initial Skew Rate for Printed Text

2011 ◽  
Vol 62 (3) ◽  
pp. 134-140 ◽  
Author(s):  
Darko Brodić
Keyword(s):  
Comparative Analysis ◽  
Mathematical Morphology ◽  
Least Square Method ◽  
Reference Points ◽  
Least Square ◽  
Gravity Center ◽  
Wide Range ◽  
Printed Text

The Evaluation of the Initial Skew Rate for Printed TextIn this manuscript the algorithm for identification of the initial skew rate for printed text is presented. Proposed algorithm creates rectangular hull around all text characters. Combining nearby rectangular hulls form objects. After applying mathematical morphology on it, the biggest object is characterized as well as selected. Rectangular hull gravity center forms reference points on these objects used as a base for calculationieestimation of the initial skew rate. Using the least square method, initial skew rate is calculated. Comparative analysis of the origin and estimated skew rate is presented as well as discussed. Algorithm is examined with a number of printed text examples. Proposed algorithm showed robustness for skewness of printed text in the wide range.

scholarly journals A NOVEL QRS DETECTION ALGORITHM APPLIED TO THE ANALYSIS FOR HEART RATE VARIABILITY OF PATIENTS WITH SLEEP APNEA

2005 ◽  
Vol 17 (05) ◽  
pp. 258-262 ◽  
Author(s):  
REN-GUEY LEE ◽  
I-CHI CHOU ◽  
CHIEN-CHIH LAI ◽  
MING-HSIU LIU ◽  
MING-JANG CHIU
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sleep Apnea ◽  
Sleep Apnea Syndrome ◽  
Detection Algorithm ◽  
Rate Variation ◽  
Qrs Detection ◽  
Detection Techniques ◽  
Wave Detection ◽  
Obstructive Sleep

Sleep-related breathing disorders can cause heart rate changes known as cyclical variation. The heart rate variation of patients with obstructive sleep apnea syndrome (OSAS) is more prominent in sleep. For this reason, to analyze heart rate variability (HRV) of patients with sleep apnea is a very important issue that can assist physicians to diagnose and give suitable treatment for patients. In this paper, a novel QRS detection algorithm is developed and applied to the analysis for HRV of patients with sleep apnea. The advantageous of the proposed algorithm is the combination of digital filtering and reverse R wave detection techniques to enhance the accuracy of R wave detection and easily implement into portable ECG monitoring system with light complexities of computation. The proposed algorithm is verified by simulation and experimental results.

A Skew Detection Algorithm for PDF417 Based on Feature Point

2011 ◽  
Vol 128-129 ◽  
pp. 495-499
Author(s):  
Jian Hua Li ◽  
Ping Li ◽  
Xiao Dan Li ◽  
Yi Wen Wang
Keyword(s):  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
Detection Methods ◽  
Automatic Identification ◽  
Feature Points ◽  
Skew Angle ◽  
Bar Code ◽  
Character Code ◽  
The Common

The automatic identification of 2D (two dimensional) bar code PDF417 is very sensitive to skew angle, but, the common skew angle detection methods have shortcomings such as weak performance in time complexity. In this paper, based on the properties of PDF417 character code and the extraction of feature points, we get skew angle of PDF417 bar code image using the least square method. Experiments show that this algorithm has virtue of less computation and high accuracy.

An Automated Method for Developing a Catalog of Small Earthquakes Using Data of a Dense Seismic Array and Nearby Stations

2020 ◽  
Vol 91 (5) ◽  
pp. 2862-2871 ◽  
Author(s):  
Yifang Cheng ◽  
Yehuda Ben-Zion ◽  
Florent Brenguier ◽  
Christopher W. Johnson ◽  
Zefeng Li ◽  
...  
Keyword(s):  
Time Window ◽  
Local Maximum ◽  
Velocity Model ◽  
Detection Algorithm ◽  
P Wave ◽  
Time Shift ◽  
Dense Array ◽  
Automated Method ◽  
Seismic Waveform ◽  
Wide Range

Abstract We propose a new automated procedure for using continuous seismic waveforms recorded by a dense array and its nearby regional stations for P-wave arrival identification, location, and magnitude estimation of small earthquakes. The method is illustrated with a one-day waveform dataset recorded by a dense array with 99 sensors near Anza, California, and 24 surrounding regional stations within 50 km of the dense array. We search a wide range of epicentral locations and apparent horizontal slowness values (0–15  s/km) in the 15–25 Hz range and time shift the dense array waveforms accordingly. For each location–slowness combination, the average neighboring station waveform similarity (avgCC) of station pairs &lt;150  m apart is calculated for each nonoverlapping 0.5 s time window. Applying the local maximum detection algorithm gives 966 detections. Each detection has a best-fitting location–slowness combination with the largest avgCC. Of 331 detections with slowness &lt;0.4  s/km, 324 (about six times the catalog events and 98% accuracy) are found to be earthquake P-wave arrivals. By associating the dense array P-wave arrivals and the P- and S-wave arrivals from the surrounding stations using a 1D velocity model, 197 detections (∼4 times of the catalog events) have well-estimated locations and magnitudes. Combining the small spacing of the array and the large aperture of the regional stations, the method achieves automated earthquake detection and location with high sensitivity in time and high resolution in space. Because no preknowledge of seismic-waveform features or local velocity model is required for the dense array, this automated algorithm can be robustly implemented in other locations.

Sign in / Sign up

Export Citation Format

Share Document