Pressure pulse waveform analysis

2011 ◽  
pp. 609-652
Keyword(s):  
Pressure Pulse ◽  
Waveform Analysis ◽  
Pulse Waveform ◽  
Pulse Waveform Analysis

Pressure pulse waveform analysis in critical care*

2006 ◽  
Vol 34 (5) ◽  
pp. 1569-1570 ◽  
Author(s):  
Michael F. O’Rourke ◽  
Junichiro Hashimoto
Keyword(s):  
Critical Care ◽  
Pressure Pulse ◽  
Waveform Analysis ◽  
Pulse Waveform ◽  
Pulse Waveform Analysis

FUZZY C-MEANS CLUSTERING FOR MYOCARDIAL ISCHEMIA ESTIMATION WITH PULSE WAVEFORM ANALYSIS

2009 ◽  
Vol 21 (02) ◽  
pp. 139-147 ◽  
Author(s):  
Shing-Hong Liu ◽  
Kang-Ming Chang ◽  
Chu-Chang Tyan
Keyword(s):  
Form Factor ◽  
Myocardial Ischemia ◽  
Radial Artery ◽  
Feature Vector ◽  
Waveform Analysis ◽  
Elderly Subjects ◽  
Pulse Waveform ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Pulse Waveform Analysis

The purpose of this study is to build an automatic disease classification algorithm by pulse waveform analysis, based on a Fuzzy C-means clustering algorithm. A self designed three-axis mechanism was used to detect the optimal position to accurately measure the pressure pulse waveform (PPW). Considering the artery as a cylinder, the sensor should detect the PPW with the lowest possible distortion, and hence an analysis of the vascular geometry and an arterial model were used to design a standard positioning procedure based on the arterial diameter changed waveform for the X-axes (perpendicular to the forearm) and Z-axes (perpendicular to the radial artery). A fuzzy C-means algorithm was used to estimate the myocardial ischemia symptoms in 35 elderly subjects with the PPW of the radial artery. Two type parameters were used to make the features, one was a harmonic value of Fourier transfer, and the other was a form factor value. A receiver operating characteristics curve was used to determine the optimal decision function. The harmonic feature vector contain second, third and fourth harmonics ( H 2, H 3, H 4) performed at the level of 69% for sensitivity and 100% for specificity while the form factor feature vector derived from left hand (LFF) and right hand (RFF) performed at the level of 100% for sensitivity and 53% for specificity. The FCM- and ROC-based clustering approach may become an efficient alternative for distinguishing patients in the risk of myocardial ischemia, besides the traditional exercise ECG examination.

The association between arterial pulse waveform analysis device and in‐hospital mortality in high‐risk non‐cardiac surgeries

2020 ◽  
Vol 64 (7) ◽  
pp. 928-935
Author(s):  
Chikashi Takeda ◽  
Masato Takeuchi ◽  
Toshiyuki Mizota ◽  
Hiroshi Yonekura ◽  
Isao Nahara ◽  
...  
Keyword(s):  
High Risk ◽  
Hospital Mortality ◽  
Waveform Analysis ◽  
Pulse Waveform ◽  
Arterial Pulse ◽  
Pulse Waveform Analysis ◽  
Arterial Pulse Waveform

Classification and comparison of AC and DC partial discharges by pulse waveform analysis

2021 ◽  
Vol 125 ◽  
pp. 106518
Author(s):  
Mojtaba Rostaghi-Chalaki ◽  
Kamran Yousefpour ◽  
Joni Klüss ◽  
Mehmet Kurum ◽  
J. Patrick Donohoe ◽  
...  
Keyword(s):  
Partial Discharges ◽  
Waveform Analysis ◽  
Pulse Waveform ◽  
Pulse Waveform Analysis
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