scholarly journals Long-term Blood Pressure Measurement in Freely Moving Mice Using Telemetry

Author(s):  
Mohammad Afaque Alam ◽  
Cory Parks ◽  
Salvatore Mancarella
2012 ◽  
Vol 192 (3) ◽  
pp. 541-543 ◽  
Author(s):  
Deborah Penteado Martins Dias ◽  
Luisa Gouvêa Teixeira ◽  
Paulo Aléscio Canola ◽  
Raquel Mincarelli Albernaz ◽  
José Antônio Marques ◽  
...  

Author(s):  
Hong Long Pua ◽  
Kok Beng Gan

It is not only a problem for old age anyone. So, blood pressure is the one provides importance information with vital signs about cardiovascular health using oscillometric method. Unfortunately, this method required inflation and following deflation of the cuff. This method only gives instantaneous blood pressure and continuous measurement is not available. It is not available to the patients that required long term monitoring. To overcome this problem, the development of Continuous Non-Invasive Blood Pressure (NIBP) algorithm based on Pulse Transit Time (PTT) using two channel Photoplethysmograph (PPG) is proposed in this study. PPG is a non-invasive device for detecting blood volume changes can be affected by various physiological factors, analysis of the PPG signal can provide sufficient information on the human health condition; more specifically their cardio-vascular related performance. Literatures show that the PTT has linear relationship with blood pressure. Nevertheless, the determination of the model structure, order and real-time implementation to offer a continuous measurement of the PTT still remains challenging tasks in this area. PTT can be as index to monitor cardiovascular disease. In this project, dynamic model based on pulse transit time will be proposed to continuously monitor blood pressure by using PPG signals. Different kind of resolutions in microcontroller combined with PPG sensor will be used as well. MATLAB software is also been applied for PTT calculation based on two PPG sensors. PPG is method for detect blood volume changes with optical source transmitter send from one end and received the signal from another by receiver through body tissue as medium. MATLAB functions as Digital Signal Processing (DSP) for signals received in computer. Linear Regression technique and Fung's algorithm are applied to obtain the best fit line for all the points in order to systolic and diastolic blood pressure measurement. The results showed that the algorithm based on pulse transit time has been developed for the assessment of blood pressure and justify patient’ condition with 86.34% and 88.20% accuracy. Finally, this technique is a simple, user friendly and operator independent PPG system suitable for long term and wearable blood pressure monitor.


Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 851 ◽  
Author(s):  
Ting-Wei Wang ◽  
Shien-Fong Lin

Non-invasive continuous blood pressure measurement is an emerging issue that potentially can be applied to cardiovascular disease monitoring and prediction. Recently, many groups have proposed the pulse transition time (PTT) method to estimate blood pressure for long-term monitoring. However, the PTT-based methods for blood pressure estimation are limited by non-specific estimation models and require multiple calibrations. This study aims to develop a low-cost wearable piezoelectric-based system for continuous beat-to-beat blood pressure measurement. The pressure change in the radial artery was extracted by systolic and diastolic feature points in pressure pulse wave (PPW) and the pressure sensitivity of the sensor. The proposed system showed a reliable accuracy of systolic blood pressure (SBP) (mean absolute error (MAE) ± standard deviation (SD) 1.52 ± 0.30 mmHg) and diastolic blood pressure (DBP, MAE ± SD 1.83 ± 0.50), and its performance agreed with standard criteria of MAE within 5 mmHg and SD within ±8 mmHg. In conclusion, this study successfully developed a low-cost, high-accuracy piezoelectric-based system for continuous beat-to-beat SBP and DBP measurement without multiple calibrations and complex regression analysis. The system is potentially suitable for continuous, long-term blood pressure-monitoring applications.


1984 ◽  
Vol 74 (7) ◽  
pp. 704-709 ◽  
Author(s):  
S M Stahl ◽  
C R Kelley ◽  
P J Neill ◽  
C E Grim ◽  
J Mamlin

2018 ◽  
Vol 19 (3) ◽  
pp. 97-101 ◽  
Author(s):  
Sachiko Ozone ◽  
Mikiya Sato ◽  
Ayumi Takayashiki ◽  
Naoto Sakamoto ◽  
Hisashi Yoshimoto ◽  
...  

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