Identification of human pulse waveform by silicon microphone chip

Author(s):  
Shusaku Nomura ◽  
Yasushi Hanasaka ◽  
Masako Hasegawa-Ohira ◽  
Tadashi Ishiguro ◽  
Hiroshi Ogawa
2013 ◽  
Vol 39 (3) ◽  
pp. 268-270 ◽  
Author(s):  
D. A. Usanov ◽  
A. V. Skripal’ ◽  
E. O. Kashchavtsev

1999 ◽  
Vol T79 (1) ◽  
pp. 275 ◽  
Author(s):  
Altti Torkkeli ◽  
Jaakko Saarilahti ◽  
Heikki Sepp? ◽  
Hannu Sipola ◽  
Outi Rusanen ◽  
...  
Keyword(s):  

2009 ◽  
Vol 21 (02) ◽  
pp. 139-147 ◽  
Author(s):  
Shing-Hong Liu ◽  
Kang-Ming Chang ◽  
Chu-Chang Tyan

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.


2021 ◽  
Author(s):  
Rahul Manoj ◽  
V Raj Kiran ◽  
P M Nabeel ◽  
Mohanasankar Sivaprakasam ◽  
Jayaraj Joseph

Author(s):  
D.G. Lapitan ◽  
A.A. Glazkov ◽  
D.A. Rogatkin

Photoplethysmography (PPG) is an optical method for recording pulse wave (PW) propagating in the tissue microvasculature. As a rule, filters with infinite impulse response (Butterworth, Bessel, etc.) often used in PPG signal processing introduce distortions in the PW signal. At the same time, the filtering parameters for a more accurate reproduction of PW have not yet been substantiated. The aim of this work is to study the influence of digital filtering parameters, such as bandwidth and filter order, on the pulse waveform. In the study, a digital bandpass Butterworth filter was used. The lower cutoff frequency of the filter varied from 0.1 to 1 Hz, the upper cutoff frequency varied from 2 to 10 Hz and the filter order – from 2nd to 6th. It was found that an increase in the lower cutoff frequency of the bandpass filtering leads to a decrease in the amplitude of the reflected diastolic wave and distortion of the front of the direct systolic wave. A decrease in the upper cutoff frequency leads to damping of the dicrotic notch and a phase shift of the PW. Increasing the filter order decreases the reflected wave amplitude. The minimal distortions of the PPG signal were observed at the lower cutoff frequency of 0.1 Hz, the upper one at 10 Hz and the filter order equal to 2. Thus, these parameters of a bandpass filtering can be recommended for processing PPG signals for a more accurate morphological analysis of PW. The obtained results make it possible to create devices for PW analysis with substantiated medical and technical requirements for filtration parameters.


1997 ◽  
Vol 61 (1-3) ◽  
pp. 352-355 ◽  
Author(s):  
Christiane Thielemann ◽  
Gisela Hess
Keyword(s):  

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