Which pulse arrives first

Advanced Biomedical Engineering. Cardiovascular refers to the Cardio heart and vascular blood vessels. The system has two major functional parts: central circulation system and systemic circulation system. Central circulation includes the pulmonary circulation and the heart from where the pulse wave is generated. Systemic circulation is the path that the blood goes from and to the heart.

Green Pulse wave is detected at arteries which include elastic arteries, medium muscular arteries, small arteries and arterioles. The typical muscular artery has three layers: tunica intima as inner layer, tunica media as middle layer, and tunica adventitia for the outer layer. Langewouters et al. Functional and structural changes in the arterial wall can be used as early marker for the hypertensive and cardiac diseases.

Blood flow is the key to monitor the cardiovascular health condition since it is generated and restrict within such system. Currently the most widely used method for haemodynamic parameters detecting is invasive thermo-dilution method.

Impedance-cardiography is the most commonly used non-invasive method nowadays; however, it is too complex for clinical routine check. Pulse wave analysis is an innovative method in the market to do fast and no burden testing Zhang et al.

Pulse is one of the most critical signals of human life. It comes directly from heart to the blood vessel system. As pulse transmitted, reflections will occur at different level of blood vessels. Other conditions such as resistance of blood flow, elastic of vessel wall, and blood viscosity have clear influence on pulse. Pathological changes affect pulse in different ways: the strength, reflection, and frequency.

So pulse provides abundant and reliable information about cardiovascular system. Pulse can be recorded toa set of time series data and represented as a diagraph which is called pulse waveform or pulse wave for short. Gathering pulse at wrist by finger has been a major diagnosis method in China since BC. Physicians used palpation of the pulse as a diagnostic tool during the examination. Grecian started to notice the rhythm, strength, and velocity at BC.

Struthius described a method to watch the pulse wave by putting a leaf on the artery, which is considered as early stage of pulse wave monitoring. In , Etienne Jules Mary invented a level based sphygmograph to measure the pulse rate. It is the first device can actually record the pulse wave.

Frederick observed normal radial pressure wave and the carotid wave to find the normal waveform and the differences between those waveforms. Mahomed He figured out the special effect on the radial waveform caused by the high blood pressure. It helps to learn the natural history of essential hypertension. Mahomed The effects of arterial degeneration by aging on the pulse wave were also shown on his work.

Mahomed His researches have been used in the life insurance field. Postel-Vinay The analysis was based on the basic mathematic algorithms in nineteenth century: dividing the wave into increasing part and decreasing part, calculating the height and area of the wave.

Calculus, hemodynamic, biomathematics and pattern recognition techniques has been used in pulse wave analysis by taking advantage of Information Technology. However, utilizing the classic pulse theory with current techniques is still a big challenge. With informed consent, sets of testing data were collected from subjects. Normal people were assigned to the control group corresponding to the patients group.

All medical records were collected in order to do research on each risk factor. Using pulse data directly is unreliable since any change of haemodynamic condition has effects on pulse wave data. But there are still many researches for pulse wave analysis because the pulse data is much easier and safer to get than most other signals.

With considering related conditions, pulse wave factors analysis can achieve higher accuracy. Most recent researches give positive results with comparing pulse wave factors analysis and standard methods. Pathophysiological Laboratory Netherlands did study on continuous cardiac output monitoring with pulse contour during cardiac surgery Jansen Cardiac output was measured 8 to 12 times during the operation with pulse contour and thermodilution.

The result shows linear regression between two methods. The cardiac output calculated by pulse wave factors is accurate even when heart rate, blood pressure, and total peripheral resistance change. To reduce the effects of other factors, pulse wave factors had been tested among different groups. Both pulse wave factors and thermodilution technique had been used to calculate the cardiac output 12 times during the surgery.

The mean differences for CO did not differ in either group Rodig It suggested that pulse wave factors analysis is a comparable method during the surgery. Calibration of the device will help to achieve more accurate result. The patients with weak pulse waveform or arrhythmia should always avoid using the result of pulse wave factors as the major source since it become unreliable in such environment. Early Detection of cardiovascular diseases is one of the most important usages for pulse wave monitoring.

The convenience noninvasive technique makes it extremely suitable for widely use at community levels. Factors derived from pulse wave analysis have been used to detect hypertension, coronary artery diseases. For example, losing the diastolic component is the result of reduced compliance of arteries. Cohn Pulse wave is suggested to be early marker for those diseases and guide for health care professions during the therapy.

Point based analysis is usually designed for specific risk factor. It picks up top, bottom points from different components of the waveform or derivative curve. Then the calculation is done regarding to the medical significant of those points. Stiffness Index is a well-known factor in this category. Arteries stiffen is a consequence of age and atherosclerosis.

Two of the leading causes of death in the developed world in nowadays, myocardial infarction and stroke, are a direct consequence of atherosclerosis. Arterial stiffness is an indicator of increased cardiovascular disease risk. Among many new methods applied to detect arterial stiffness, pulse wave monitoring is a rapidly developing one. Arterial pulse is one of the most fundamental life signals in medicine, which has been used since ancient time.

With the help of new information technology, pulse wave analysis has been utilized to detect many aspects of heart diseases especially the ones involving arterial stiffness. They are recognized as the dominant risk factors for cardiovascular disease. The contour of the peripheral pressure and volume pulse affected by the vascular aging on the upper limb is also well-known. The worsen artery stiffness with an increase in pulse wave velocity is cited as the main reason for the change of pulse contour.

PWV is the velocity of the pulse pressure. The blood has speed of several meters per second at the aorta and slow down to several mm per second at peripheral network. The PWV is much faster than that.

Normal PWV has the range from 5 meters per second to 15 meters per second. Since pulse pressure and pulse wave velocity are closely linked to cardiovascular morbidity, some non- invasive methods to assess arterial stiffness based on pulse wave analysis have been introduced.

However, these methods need to measure the difference of centre artery pulse and the reflected pulse wave, which is a complicated process. On the other hand, the Digital Volume Pulse DVP may be obtained simply by measuring the blood volume of finger, which becomes a potentially attractive waveform to analyze. Millasseau et al have demonstrated that arterial stiffness, as measured by peripheral pulse wave analysis, is correlated with the measurement of central aortic stiffness and PWV between carotid and femoral artery, which is considered as a reliable method in assessment of cardiovascular pathologic changes for adults.

It is an effective non-invasive method for assessing artery stiffness. Pulse Wave Velocity is the golden standard for arterial stiffness diagnosis. It uses the reflection of the pulse as the second source to get the time difference without additional sensors which make it more applicable to the Home Monitoring System. As shown in figure 1 , the systolic top shows the time that pulse reach the finger; diastolic top represents the time that pulse reflection reach the finger.

The distance that pulse goes through has direct relationship with the height of the subject. The attempt for getting cardiac output from pulse wave started more than one hundred years ago Erlanger The pulse wave is the result of interaction between stroke volume and arteries resistance. Building the model of arterial tree helped the calculation of CO from pulse wave.

The simplest model used in clinic contains single resistance. Other elements should be involved in the calculation including capacitance element, resistance element Cholley Not all models have reliable results, even some widely used one can only work in specific environment.

Windkessel Model consists of four elements: left ventricle, aortic valve, arterial vascular compartment, and peripheral flow pathway. Testing of the model in normotensive and hypertensive subjects shows that the model is only valid when the pressure wave speed is high enough with no reflection sites exist Timothy Tomas compared the CI value among pulmonary artery thermodilution, arterial thermodilution and pulse wave analysis for critically ill patients.

The mean differences among three methods are within 1. Felbinger The pulse wave factors provide clinically acceptable accuracy. In addition to long term monitoring, pulse wave analysis is also useful for emergency environment. Cardiac Function can be evaluated within several seconds. The pulse wave sensor detects the blood flow at the index finger and tracks the strength of the flow as pulse wave data.

To record the pulse wave, the patients were comfortably rested with the right hand supported. A pulse wave sensor was applied to the index finger of right hand.

Only the appropriate and stable contour of the pulse wave was recorded. As shown in Figure, the first part of the waveform systolic component is result of pressure transmissions along a direct path from the aortic root to the wrist. The second part diastolic component is caused by the pressure transmitted from the ventricle along the aorta to the lower body.

The time interval between the diastolic component and the systolic component depends upon the PWV of the pressure waves within the aorta and large arteries which is related to artery stiffness. The SI is an estimate of the PWV about artery stiffness and is obtained from subject height h divided by the time between the systolic and diastolic peaks of the pulse wave contour. The height of the diastolic component of the pulse wave relates to the amount of pressure wave reflection.

Methods: Thirteen young healthy volunteers were studied, using an electrocardiogram and plethysmograph to simultaneously record pulse wave arrival at the ear lobe, index finger and big toe.

We compared the differences in PAT between each location at rest and post-exercise in the supine, sitting, and standing position. Results: PAT was shortest at the ear then finger and longest at the toe regardless of position or exercise status. PATs were shorter post-exercise compared to rest. When transitioning from a standing to sitting or supine position, PAT to the ear decreased, while the PAT to the toe increased, and PAT to the finger didn't significantly change.

PAT ratios were significantly smaller than predicted by the path distance ratios regardless of position or exercise status. Conclusions: Exercise makes PATs shorter. Standing position decrease PAT to the toe and increase to the ear. We conclude that PAT and PAT ratio represent the arterial vascular tree properties as surely as pulse transit time and pulse wave velocity.

When the heart contracts it ejects a bolus of blood, the stroke volume, into the arterial vascular system, which is then distributed to the peripheral tissues. The time period needed for a pulse wave to travel from the heart to the peripheral tissues depends on the distance traveled and the velocity of the pulse wave, which in turn is determined by various physical properties such as vessel diameter, wall thickness, and compliance Bramwell and Hill, Pulse wave velocity PWV has been studied extensively as a predictor for adverse cardiovascular events Steppan et al.

PWV is the ratio of vascular path length and the pulse transit time PTT between two sites of measurement. Pulse arrival to the peripheral vascular beds, the PTT, is the time from aortic valve opening till the foot of the pulse waveform at the peripheral site.

However, these two are distinctly different. PAT is defined as the time delay between the peak of the R wave of the ECG waveform and the arrival upstroke of the arterial pulse wave in the periphery.

Prior studies reported the PAT to different peripheral vascular beds in subjects of different age, height, and with different blood pressures Allen and Murray, ; Nitzan et al. The PAT was consistently shortest at the ears, and longest at the toe. They showed that higher blood pressures and age were associated with shortening of the PAT, suggesting that PWV differs in distinctive peripheral vascular beds Nitzan et al.

Indeed Liu et al. In this manuscript, we studied the effects of position and exercise on the PAT to different parts of the body. Changes in body position triggers multiple cardiovascular responses due to the changes in hydrostatic pressure and sympathetic activity. In addition, exercise affects vascular properties through both vasodilation of arterioles and increased vasoconstriction due to sympathetic stimulation Sharman et al. Moreover, we compared the pulse arrival ratios to the respective distance ratios between different locations.

Specifically, we examined the PATs to three different vascular beds ear lobe, index finger, and big toe for the same heartbeat in three different positions standing, sitting, and supine at rest and post-exercise in young healthy subjects, as these factors might significantly affect PAT at different peripheral vascular beds.

We enrolled 13 healthy volunteers with no history of vascular or cardiac disease, age 23—41 years old. Recruitment was done through e-mail or word of mouth in accordance with the Internal Review Board consent scripts. Inclusion criteria were: Healthy adults, age 21—50 years, both genders. Exclusion criteria were: Subject refusal to participate, known cardiovascular disease of any kind, pregnancy, and any disability preventing mild physical exertion. Two subjects who joined the study were excluded.

The first subject was excluded due to the inability to finish the study protocol. The second subject was excluded as we were unable to obtain a plethysmograph signal on the toes. Next, we placed capillary plethysmograph sensors [MLTEC IR Plethysmograph ear , MLTPPG IR Plethysmograph finger and toe , ADInstruments, Australia] on both left and right sides for each of the following locations: ear lobes in a standing position, index fingers in a sitting position with hands hanging free by their sides, and on the big toes lying in the supine position.

We simultaneously recorded the ECG and plethysmograph bilaterally for each location ear, index finger, big toe. Then, we simultaneously recorded the ECG along with the plethysmographs from one unilateral ear, finger, and big toe for 30 s each in the standing, sitting, and supine position. The ECG and plethysmograph sensors were then removed from the subjects and a blood pressure cuff applied to record blood pressure in the standing, sitting and prone position respectively.

For the exercise part of the experiment the subjects were required to perform 30 squats. The ECG and plethysmograph sensors were reattached to the subject's left ear lobe, index finger, big toe, and the recording redone in the standing, sitting, and supine positions.

From the data collected, the PAT to each location ear lobe, index finger, and big toe was assessed by calculating the time delay between the peak of the R wave on the ECG and the first subsequent positive inflection on the plethysmograph tracing. To compare PATs to different tissue beds from the same heartbeat, we took the corresponding R wave of the ECG, which was assigned a time value of zero. The representative data is shown in Figure 1. Periods consisting of 10 consecutive heart beats from each position standing, sitting, supine before and after exercise were then used to calculate the mean PAT for the three locations ear lobe, index finger, big toe.

The collected data was then tabulated and used for statistical analysis. Figure 1. Example reading of LabChart file. We simultaneously recorded the ECG bottom along with plethysmographs from big toe first from the top , finger second from the top , and ear third from the top and for 30 s each in standing, sitting, and supine positions.

The PAT to each location ear lobe, index finger, and big toe was assessed by calculating the time delay between the peak of the R wave on the ECG and the first subsequent positive inflection on the plethysmograph trace.

Periods consisting of 10 consecutive heart beats from each position standing, sitting, supine before and after exercise were then used to calculated the mean PAT for the three locations ear lobe, index finger, big toe.

Data was analyzed using GraphPad Prism version 6. Demographics and baseline characteristics of the volunteers are presented in Table 1. Average age was 30 years and ranged from 23 to 41 years. We therefore elected to compare only one side left to measure the PATs at different locations. Figure 2. Comparison of PATs measured in left side and those in right side. PAT, pulse arrival time; L, left side; R, right side; n. Table 2. In all positions, both at rest and post-exercise, the PATs between ear and toe were significantly different shortest at the ear and longest at the toe.

Figure 3. The effect of location and exercise on the PAT. A Comparison of PAT measured in the standing position. B Comparison of PAT measured in the sitting position. C Comparison of PAT measured in the supine position. PAT, pulse arrival time; SD, standard deviation. Post-exercise PATs at all three locations and in all three positions were shorter compared to PATs at rest although some of them were not statistically significant.

At rest, PAT to the ear was longest in the standing position 0. After exercise, PATs at the different locations were not significantly different 0. Figure 4. The effect of position and exercise on the PAT. A Comparison of PAT measured at ear. B Comparison of PAT measured at finger. If the transmitted pulse is very short in relation to the pulse period, it can be ignored.

Ignoring pulse length, the maximum unambiguous range of any pulse radar can be computed with the formula:. The greater the pulse repetition frequency f p in pulses per second , the shorter the pulse repetition time T interpulse period and the shorter the maximum unambiguous range R max of the radar. R max must be larger than the Maximum Display Range so-called: instrumented range.

According to formula 2 the maximum unambiguous range of this radar is km. Answer: That cannot be answered in this way. Figure 2: With a staggered pulse repetition frequency, a second sweep echo does not have a stable position to the following pulse period.

The pulse repetition time PRT of the radar is important when determining the maximum range because target return-times that exceed the PRT of the radar system appear at incorrect locations ranges on the radar screen. Returns that appear at these incorrect ranges are referred as ambiguous returns, second-sweep echoes or second time around echos. By employing staggered PRT the target ambiguous return isn't represented any more by small arc on an analog display.

This movement or instability of the ambiguous return is represented typically as a collection of points in certain equipment because of the change in reception times from impulse to impulse.