Welcome to BIOEN 2023

6th International Conference on Biomedical Engineering and Science (BIOEN 2023)

January 21-22, 2023, Virtual Conference



Accepted Papers
Immune System Self- Foreignness

Brian Daunter, Australia

ABSTRACT

The immune response is generally considered to be defense system, against foreign antigens, by the production of antibodies and reactive cells. However, there is no genetic system that can account for antibody variability, and for antigens that have not previously been encountered. It is proposed that to identify foreignness, there must be a point ofreference. It is proposed that this reference point is ‘self .’That is identifying self-foreignness. That the foreignness is associated with changes in the plasma membrane of the cell that is specific for cell type, cell surface pattern, identified by tissue specific lymphocytes.This may be demonstrated by blood groupantigens.


Pulse Transit Time Pat as a Surrogate for Blood Pressure Assessment

Radjef Lilia and Omari Tahar, Department of Electrical Engineering Systems, Boumerdes University, Boumerdes, Algeria

ABSTRACT

Accurate and continuous measurement of Blood pressure (BP) monitoring can provide valuable information about an individual's health status. Pulse transit time (PTT) and (PAT) are accurate markers of blood pressure and have been widely applied in the estimation of continuous Blood pressure (BP). The pulse transit time (PTT) is the time taken for the arterial pulse to travel from the heart to a peripheral site while the pulse arrival time (PAT) is defined as the interval between the pulse beat and the arrival of the pulse wave at the periphery. In other words, (PAT) is the sum of the pulse transit time (PTT) and the pre ̵ejection period (PEP). This paper investigates the possibility of estimating blood pressure using the pulse arrival time PAT (heart to index finger), from photoplethysmography (PPG), electrocardiogram (ECG) signals, and instantaneous Blood pressure (ABP). The obtained results a moderate negative correlation was observed between (SBD) and theoretical PTT (r=-0.64), p < 0.001), between (DBP) and (PTT) (r=-0.66, p < 0.001), and a high negative correlation between (MBP) and (PTT) (r= -0.72, p < 0.001. We show a weak mean correlation (r=0.17), and a low dependence between the blood pressure (SBP, DBP, and MBP), and either (PAT-f) or (PAT-p), which confirms the non-applicability of this parameter in the estimation of blood pressure.

KEYWORDS

Blood pressure (BP), Pulse arrival time (PAT), Pulse transit time (PTT). Photoplethysmograph (PPG), Electrocardiogram (ECG), Systolic Blood pressure, Diastolic Blood pressure, Mean Blood pressure.


A New Algorithm for Measuring Pulse Transit Time Ptt From ECG and PPG Signals

Radjef Lilia and Omari Tahar, Department of Electrical Engineering Systems, Boumerdes University, Boumerdes, Algeria

ABSTRACT

In this paper, we propose a new and low-complexity algorithm for the Pulse transit time (PTT) measurement. The (PTT) is a physiological parameter that is based on characteristics of the pulse waveform, a direct indicator of Cardiovascular Diseases (CVD). It is commonly derived from Electrocardiogram (ECG) and Photoplethysmogram (PPG) signal calculations. The pulse transit time (PTT) is defined as the time taken for the arterial pulse to travel from the heart to a peripheral site and is calculated as the interval between the peak of the electrocardiogram (ECG) R-wave and a time point on the photoplethysmogram (PPG). This study aimed to develop a new algorithm for (PTT) estimation, using these two signals and detecting (PTT- foot) and (PTT- peak). We built a 37 subjects dataset containing a simultaneous recording of the (ECG) and (PPG). The calculation of (PTT) consists of detecting the peak and foot points of a (PPG) and the R peak of the (ECG) signal. Intermediate operations such as normalization and thresholding are processed on noisy signals, this algorithm is improved by a windowing temporal analysis. The obtained results are promising for the first step. The average sensitivity (SEN) and accuracy (ACC) obtained were (97.5%, and 96.82%) respectively for R-peaks detection and respectively (97.77%, and 97.64%) for (PPG-peak) detection. The sensitivity (SEN) and accuracy (ACC) of (PPG- foot) detection were (98.33%, and 94.14%).

KEYWORDS

Pulse transit time (PTT), Cardiovascular Disease (CVD), Electrocardiogram (ECG), Photoplethysmography (PPG), Algorithm, Peaks detection, Sensitivity (SEN), Accuracy (ACC).