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 Table of Contents  
REVIEW ARTICLE
Year : 2022  |  Volume : 9  |  Issue : 1  |  Page : 103-111

Pulse arrival time: Measurement and clinical applications


1 Department of Biomedical Engineering, MGM’s College of Engineering & Technology, Navi Mumbai, India
2 Department of Biomedical Engineering, Vidyalankar Institute of Technology, Mumbai, Maharashtra, India

Date of Submission19-Feb-2022
Date of Acceptance23-Feb-2022
Date of Web Publication23-Mar-2022

Correspondence Address:
Dr. Ghanshyam D Jindal
Department of Biomedical Engineering, MGM’s College of Engineering & Technology, Kamothe, Navi Mumbai 410209, Maharashtra.
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mgmj.mgmj_23_22

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  Abstract 

Pulse arrival time is the time elapsed between the R-wave of electrocardiogram and systolic peak in peripheral pulse obtained by any of the plethysmographic methods. Similarly, differential pulse arrival time, also known as pulse transit time, is the time elapsed between systolic peaks of proximal and distal peripheral pulse recordings in an extremity. Distance between the proximal and distal site in the extremity (in meters) divided by differential pulse arrival time (in seconds) gives arterial pulse wave velocity in the limb segment. Differential pulse arrival time has been used to discriminate between an aortic or arterial block from generalized atherosclerosis in aortic and arterial occlusive diseases for nearly four decades. All along there have been efforts to monitor beat-to-beat blood pressure with the help of these time intervals and other pulse parameters. Encouraging correlation has been observed with that obtained by Finapres. Recently pulse arrival time has been explored for the prompt detection of sudden hypertensive episodes during laryngeal microsurgery, for detection of mental stress, monitoring of baroreflex sensitivity, and real-time monitoring of blood pressure. This paper briefly describes the measurement technique of pulse arrival time and an overview of its clinical applications.

Keywords: Baroreflex sensitivity, blood pressure variability, plethysmography, pulse arrival time, pulse transit time


How to cite this article:
Deshmukh CA, Jindal GD, Bagal UR, Nagare GD. Pulse arrival time: Measurement and clinical applications. MGM J Med Sci 2022;9:103-11

How to cite this URL:
Deshmukh CA, Jindal GD, Bagal UR, Nagare GD. Pulse arrival time: Measurement and clinical applications. MGM J Med Sci [serial online] 2022 [cited 2022 May 17];9:103-11. Available from: http://www.mgmjms.com/text.asp?2022/9/1/103/340584




  Introduction Top


The pulse arrival time (PAT) is defined as the time taken by the blood to reach any particular body segment in the extremity from the instant of its ejection into the aorta. In the absence of noninvasive measurement of the instant of ejection blood into the aorta, the R-wave of electrocardiogram (ECG) is accepted as a valid reference point. Instant arrival of the blood volume pulse in the limb segment can be measured noninvasively by any of the plethysmographic methods. As impedance plethysmography (IPG) and photo-plethysmography (PPG) are considered more direct noninvasive methods for blood volume measurement in comparison to volume displacement methods, they are usually preferred for the measurement of PAT.[1],[2]

A typical impedance plethysmograph system comprises a sine-wave oscillator followed by a voltage to current converter. This converter outputs a sinusoidal current of constant amplitude (1–10 mA) which can be passed through the body segment with the help of two-band electrodes called the carrier electrodes C1 and C2. The voltage signal developed along the current path is sensed with the help of another pair of electrodes called sensing electrodes S1 and S2. The amplitude of the signal thus obtained is directly proportional to the electrical impedance of the body segment bound by electrodes S1 and S2. The amplification and detection of this signal yield an output signal, which is proportional to instantaneous impedance (Z) of the body segment. Small changes in the impedance of the body segment caused by physiological processes such as blood circulation and respiration are obtained by subtracting the initial value of the impedance (Z0) from the instantaneous impedance and is called the DZ(t) waveform. The Z is also differentiated in time to get the rate of change of impedance or the dZ/dt waveform. The digital interface of this unit with laptop PC displays all the signals (Z, DZ(t), and dZ/dt) on the screen as shown in [Figure 1].
Figure 1: Schematic diagram of a typical impedance plethysmograph system. C1 and C2 are the carrier electrodes. S1 and S2 are the sensing electrodes. Z, DZ(t), and dZ/dt are interfaced to laptop PC through microcontroller

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PPG is based on the optical properties of blood. When the red light falls on the finger/toe/earlobe, the light received from the other side through transmission depends upon several factors such as pulsatile blood volume in the arteries/arterioles, blood volume in the veins and tissues in the optical path, absorption in the skin, and tissue pigments. It has been shown that the amount of blood entering the finger/toe during systole is directly proportional to the logarithmic difference of total photoelectric output and its DC component. A typical PPG system comprises a square-wave generator connected to a light-emitting diode mounted on the upper side of a finger clip. Photodiode mounted on the other side of the clip is connected to an amplifier, bandpass filter, and a sample and hold circuit triggered by the rising edge of the square wave. The output of the sample and hold can be displayed on the laptop screen through a digital interface. The PPG output signal has pulsations synchronous with cardiac ejection superimposed on DC voltage representing the overall transmission of light through the finger as shown in [Figure 2].
Figure 2: Schematic diagram of a PPG system comprising a sensor clip having light-emitting diode in the upper segment and photodiode in the lower segment. P and (P–Po) are interfaced to laptop PC through microcontroller for recording peripheral pulse

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  Measurement of pulse arrival time Top


For measurement of PAT, ECG, and IPG/PPG signals are recorded simultaneously. Regarding the R-wave of ECG, there is no ambiguity; however, for the appearance of the pulse at the measurement site ambiguity exists. A group of researchers considers the onset of the systolic pulse as the arrival time,[3] whereas others prefer to measure the peak point as it is distinctly identifiable. There exists a compromise solution for the above ambiguity; the point of maximum slope (which is easily identifiable as the peak in the time derivative of the IPG/PPG signal) is considered the acceptable point of the arrival of the pulse[4] as shown in [Figure 3]. It shows ECG signal (top), DZ(t) signal (middle) and dZ/dt signal (bottom). As can be seen from the figure PAT measured with the onset of systolic wave in DZ(t) (from R-wave of ECG to point A) is different from that measured with a peak of the systolic wave. Further ambiguity exists due to the rounding of the signal at onset as well as the peak point. The point of maximum slope as obtained from dZ/dt (measured from an R-wave of ECG to point C in (c) is free from uncertainty and therefore accepted for PAT measurement in general. [Figure 4] shows ECG signal (a), dZ/dt signal at a proximal location (b), and the same signal at a distal location (c). As seen in the figure PAT is measured at a proximal location (PATp) as well as at a distal location (PATd). The difference between proximal and distal PAT values (PATd – PATp) gives the time taken by the pulse to travel from the proximal location to the distal location. It is called differential pulse arrival time (DPAT) or pulse transit time (PTT). Distance L between proximal and distal locations divided by DPAT gives the arterial pulse wave velocity (APWV). DPAT or APWV has been used to detect aortic/arterial blocks and also to estimate the status of collateral blood circulation and distal arterial runoff[4] as shown in [Figure 5] and [Table 1].
Figure 3: Measurement of PAT from the onset, peak, and rising slope of DZ(t) waveform with respect to R-wave of electrocardiogram. PAT (onset) is preferred over PAT (peak) due to its higher physiological correlation. Difficulty in exact detection of A point has led to PAT (slope) measurement, which is obtained from the first time derivative of the peripheral pulse (dZ/dt) as shown

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Figure 4: DPAT measured from PAT of proximal and distal locations

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Figure 5: (A) IPG waveforms in a patient (RKP-30-M) with femoral artery occlusion in the left leg. The amplitude of the waveform on the right side gives a normal appearance. The left thigh shows a marginal decrease in the amplitude of the waveform, which becomes moderately lower at knee level and markedly lower at calf and ankle levels. The BFI and DPAT values in this patient given in [Table 1] show marginal to a severe decrease in BFI in the left thigh to ankle with an increase in DPAT at knee and ankle level in comparison to those of right leg. These observations are consistent with a diagnosis of femoral artery block in the left leg with moderate collaterals up to the knee and poor distal arterial runoff distally as shown by aortogram in (B). (B) It shows complete occlusion of the left superficial femoral artery. There is the reformation of the distal part of the femoral and popliteal suggesting good collateral circulation. Further leg branches (not shown here) have not opacified indicating poor distal arterial runoff

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Table 1: BFI and DPAT values in right and left leg at various locations

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  Clinical applications Top


Baroreflex sensitivity

The baroreflex system regulates short-term fluctuations in arterial blood pressure (BP). Arterial baroreceptors located on the carotid wall and aortic arch sense changes in BP and thereby regulate efferent autonomic activity to the central nervous system. The perceived increase in BP leads to increased vagal discharge and decreased sympathetic discharge, resulting in decreased heart rate (HR), myocardial contractility, and peripheral vascular resistance. Conversely, a decrease in BP increases HR and peripheral vascular resistance by strengthening the sympathetic nervous system and suppressing vagal activity.

Baroreflex sensitivity (BRS) is defined as the change in cardiac interval (CI) with changes in systolic blood pressure (SBP). It is known to have information about the autonomic nervous system that regulates BP and CIs. The relationship can be interpreted as the amplification of the cardiac control system from the neural domain to the mechanical domain. Based on the latest technology in non-invasive BP measurement and digital signal processing, most studies on BRS use RR-interval series from ECG for CI and the corresponding value of SBP from beat-to-beat BP monitor. Chee et al.[5] have calculated BRS values using two methods: Sequence technology in the time domain, and spectrum technology in the frequency domain. To calculate the BRS value in both domains, at least two signals are needed: CI in milliseconds (ms) and SBP every heartbeat in mm Hg. In their study, they have explored the possibility of using PAT as a surrogate signal of a complicated SBP waveform. They have shown [Figure 6] plots of PAT, SBP, and CI over 300 s in a subject with a controlled respiration rate (0.07–0.12 Hz), The Coherence value between CI and SBP is similar to that between CI and PAT and observed to be more than 0.5. They have concluded by saying that for the assessment of BRS in controlled breathing, PAT can be used as a surrogate parameter of expensive and inconvenient to measure beat-to-beat SBP.
Figure 6: Plots of PAT, SBP, and CI over 300 s in a subject with a controlled respiration rate (0.07–0.12 Hz) are similar in appearance. Maxima at around 165 s shows a peak in CI and SBP however dip in PAT, suggesting an inverse relation of the latter with CI and SBP (courtesy Chee et al.[5])

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Mechanical alternans detection

Mechanical alternans (MA), also known as pulsus alternans, is defined as a BP change occurring on an every other beat basis, which can manifest in a succession of strong and weak pulses. It was discovered in the 19th century and has been recognized as a marker of cardiovascular impairment given the association with increased mortality in heart failure and idiopathic dilated cardiomyopathy. MA is a demonstration of a broader phenomenon known as cardiac alternans,[6] which involves the excitation-contraction coupling and includes electrical alternans; a phenomenon describing electrical conduction and/or repolarization changes on alternate beat basis.

Duijvenboden et al.[6] have shown that PAT can classify mechanical shifts (positive or negative) and track the discontinuous motion of MA with acceptable accuracy [Figure 7]. The results of their study have shown that cardiac contractility is a primary factor in the establishment of MA. Invasively derived measurements of PAT alternans and CI alternans can detect MA with high accuracy. They have observed a high correlation between alternans in PAT and CI with MA (accuracy >0.84).
Figure 7: Raw BP trace with temporal episodes of MA and those of ΔPAT and ΔSBP show that the latter two traces are having similar appearances however inverse relation (courtesy Duijvenboden et al.[6])

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Blood pressure estimation and beat-to-beat monitoring

High BP is a serious concern for cardiovascular disorder and related mortality. Vital organs like the brain, heart, and kidneys may be laid low with hypo or hypertension. Thus non-stop measures of SBP, diastolic blood pressure (DBP), and mean arterial pressure (MAP) is an essential requirement in a variety of scientific and non-scientific programs inclusive of in-residence tracking, secure anesthetizing, or tracking of intensive care unit (ICU) patients. Though invasive intra-arterial measurement/monitoring is the best and gold standard method, there are situations where catheterization is not justified such as spot measurement in clinics, physiological experiments in laboratories, and intensive care in nursing homes. The oscillometric method is globally accepted for noninvasive BP measurement as well as periodic (3–10 min) monitoring during intensive care but is unable to give a beat-to-beat measurement.

Geddes et al.[7] have probably for the first time established a relation between PAT/DPAT and systolic and DBP through animal experimentation. By simulation experiments, they have first postulated that the PAT at a distal location is minimum if the pressure is less than diastolic and maximum if the pressure is more than systolic in the tourniquet applied proximally. Subsequently, they have proved their hypothesis in experiments in anesthetized dogs. Disposable infant BP cuff (4.3 cm × 11 cm) was applied to the forelimb and ipsilateral and contralateral radial arteries were cannulated for recording pressure waveform along with ECG (lead II) on a high-speed strip-chart recorder. The hypothesis was further validated by raising BP by norepinephrine drip (intravenous) and lowering it by hemorrhage.[7]

Kapse et al.[8] developed an instrument comprising IPG, PPG, ECG, and oscillometric modules. The subjects were asked to lie down in a supine position and signal waveforms were obtained after the rest of 15 mins. Three sets of readings were taken and two having minimum differences were averaged to yield the reference SBP, MAP, and DBP values. Lead II configuration of ECG was used and PPG in form of the clip was put on the index finger of the left hand. The carrier electrodes (C1 and C2) of IPG were applied at the neck and palm and sensing electrodes (S1 and S2) were applied, 5 cm apart, at the left wrist. The sampling rate of 500 samples per second for 50–60 s was used to acquire ECG, IPG, and PPG signals. Linear multivariate equations derived from IPG, PPG, and ECG data in 137 subjects were used to develop a regression equation relating BP and observed plethysmographic parameters. The regression equations were validated in another group of 136 subjects, which yielded a correlation for SBP (82.6%) and MAP (73.1%). It was observed that plethysmographic parameters which complemented pulse wave velocity increased the accuracy of SBP and MAP measurements.[8]

In continuation with the above study, beat-to-beat pressure was recorded simultaneously by Finapres[9] with the above signals. [Table 2] shows the correlation of plethysmographic and physical parameters with systolic BP of the corresponding beat by Finapres and oscillometric NBP (asynchronous).[10] The regression equation for SBP formed by this correlation table using R-studio is as given as follows:
Table 2: Correlation of systolic blood pressure value with various plethysmographic and physical parameters

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SBP = 145.47 + 0.866(L_DIR_DZ_FF) – 112.73(DIR_t1) + 1.122(AG20) + 0.081(Weight) – 315.96(dIR_DIR_PF).

It was observed that inclusion of gender and treatment factor did not improve upon the Multiple R-squared: 0.8833, adjusted R-squared: 0.8827 values. Parameters representing same aspect as L_DIR_DZ_FF represented by DIR_DZ_PP/ DIR_DZ_FF/ dIR_dZ_PP/ L_dIR_dZ_PP do not appear in the regression equation.

It is also observed that L_DIR_DZ_FF representing pulse wave velocity in the limb segment has a higher correlation coefficient (CC) than that of time intervals DIR_DZ_PP/ DIR_DZ_FF/ dIR_dZ_PP/ L_dIR_dZ_PP revealing the importance of pulse wave velocity in estimating SBP.

Dash et al.[11] have used correlation analysis to study the possibility of using PAT and HR for measuring beat-to-beat BP noninvasively in critically ill patients. They have observed that PAT correlates greater with SBP than DBP. The reduced correlation between PAT and DBP is due to the hemodynamic control of the DBP and may also depend on the technique of measurement of PAT. They have concluded saying PAT and HR can track the BP changes as long as the value of the CC falls in the range of ±0.7 and ±1.

Wippermann et al.[12] have correlated inverse of PAT with systolic, diastolic, mean BP, and HR in 15 critically ill infant/pediatric patients. The patient group comprised post-surgical conditions as follows: pulmonary sling correction, mitral valve replacement, severe head trauma, subdural empyema, closure of primum atrial septal defect (ASD), atrioventricular septal defect repair, aortic valve replacement, aortic valve repair (2 nos), homograft implantation, ventricular septal defect closure (2 nos), hydrocephalus, transposition of great arteries switch (2 nos). The observations are summarized in [Table 3]. As shown in the table the mean correlation values for SBP, DBP and MBP are above 0.6 in such extreme conditions.
Table 3: Physical profile and correlations of (1/PAT) observed by Wippermann et al.

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Escobar-Restrepo et al.[13] have investigated the linear relation between PAT and BP in ICU patients. They calculated the Pearson CC and mean absolute error (MAE) for each of the eleven subjects independently to elucidate the overall relationship for a total of 73 h recording time amounting to the analysis of 333,007 beats. The MAE is calculated using the following equation:



where PO is the observed value of pressure (derived from intra-arterial pressure waveform), PE is the estimated pressure from PAT and n is the total number of beats observed.

They observed mean CC (of 333007 beats) to be –0.46 and –0.56 for diastolic and systolic pressure, respectively. However the same rose to –0.89 and –0.96 for DBP in the subject (nos. 4 and 11), respectively, who recorded lower values of MAE/Δ (0.10, 0.07). Corresponding figures for SBP are –0.92 and –0.93 against the MAE/Δ value of 0.09 as shown in [Figure 8]. Thus PAT estimated BP emerged as an indicator of wide trend changes during hypertensive/ hypotensive episodes.
Figure 8: Plot of CC on Y-axis against MAE/Δ on X-axis. Blue points indicate a correlation with SBP and orange points indicate that with DBP. It is observed that small values of MAE/Δ yield higher correlation (courtesy Escobar-Restrepo et al.[13])

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Rajala et al.[14] have shown that PAT estimation from the second derivative of the PPG signal is very close to that measured from the foot of the signal. Zheng et al.[15] have used the following nonlinear PAT-based BP model in their study for BP estimation:





SBP0, DBP0 and PAT0 are the first measurements of the cuff-based BP device and wearable PAT device for each subject during the day or nighttime, used as the calibration points for the PAT-based BP model described in the above equations. Their observations in 24 subjects have shown that the cuff-less method can estimate mean night-time SBP and DBP with errors within −1.4 ± 6.6 and 0.4 ± 6.7 mm Hg, respectively. The PAT-based method thus provided a cuff-less solution for night-time BP monitoring in clinical practice.

Lee et al.[16] have investigated the efficacy of PAT/PTT-based BP estimates in a total of 6,777,308 data points. They have used intersecting-tangent point of PPG for PAT determination and observed the highest mean correlation to BP as −0.37 and −0.30 for SBP and DBP, respectively. It outperformed the correlation between BP and PTT (−0.12 for SBP and −0.11 for DBP). They further developed a linear model of BP using PAT as a predictor with simple calibration, which qualified DBP measurement as per international standards for automatic oscillometric BP monitors.

In the study of Peng et al.[17] ECG and PPG on 34 subjects in the natural state, and 55 subjects under the cold stimulation have been simultaneously recorded. The RR-intervals and PAT were calculated and the Pearson CC was observed to be 0.551, which improved to 0.770 when the RRI series is delayed by 2 beats (2.18 ± 0.40 beats). This showed that RRI changes first and it gets reflected in PAT two beats later.

Detection of mental stress

In a repeated measure design experiment, Ernst et al.[18] have recorded PAT values in the course of 6 blocks including five relaxation blocks (1, 3, 4, 5, and 6) and one mental stress (2) block (utilizing the Mannheim Multicomponent Stress Test). Forty-two healthy volunteers were subjected to this study. After 5 min of rest, PAT was observed for 5 min (relaxation block 1) in each volunteer. Mental stress was then performed by them for 5 min (stress block) and simultaneously PAT was observed. Subsequently, their PAT was observed for four relaxation blocks of 10 min each. Finger PAT and earlobe PAT were evaluated identically for over 135,000 heart cycles. Mean and standard deviation values of earlobe PAT were observed to be 138 ± 21 ms at rest and 122 ± 22 ms under stress. Similar figures for finger PAT were 192 ± 17 ms at rest and 178 ± 20 ms under stress. There is a relative decrease of 11.6% for the mean earlobe PAT and 7.3% for the mean finger PAT due to stress. The mean BP (measured by Task Force Monitor 3040i) levels of 84 mm Hg, 93 mm Hg, 90 mm Hg, 88 mm Hg, 86 mm Hg, and 85 mm Hg were observed for blocks 1 – 6, respectively, leading to an increase of 7.4% under stress compared to average rest (86.6 mm Hg). Their results have shown that pulse wave reaches the earlobe faster than the index finger, due to the smaller distance of the former from the heart. The study also shows that PAT can be a good indicator of mental stress.

Pulse arrival time changes during anesthesia induction and laryngeal microsurgery

Kim et al.[19] have evaluated the correlation between beat-to-beat PTT and invasively measured continuous arterial BP during anesthesia induction in 23 hypertensive patients scheduled for renal transplant. They recorded arterial BP, electrocardiogram, and finger PPG simultaneously and measured PTT as the time interval from the R-peak on ECG to the maximal upslope point in PPG. During anesthesia induction, they observed changes in PTT to be directly proportional to changes in BP; decrease in BP lengthened PTT and vice versa. Correlations of BP values with the inverse of PTT were observed as given in [Table 4]. The receiver operating characteristic (ROC) curve analysis revealed that a 15% increase in PTT during anesthesia induction could detect a ≥30% decrease in systolic BP, with an area under the ROC curve of 0.85. Their study concluded with the fair correlation between systolic BP and inverse PTT and the potential of the latter in detecting BP reduction during anesthesia induction.
Table 4: Correlation of inverse PTT with blood pressure values (Kim et al.)

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These observations led to the application of inverse PTT in the detection of hypertensive episodes during laryngeal microsurgery (LMS). Laryngoscopic manipulations can stimulate the sympathetic nervous system and increase the level of epinephrine and norepinephrine, which may result in acute hypertension further leading to ischemic heart disease, stroke, or life-threatening arterial bleeding. As LMS has a short operating time and is usually an outpatient practice, invasive BP monitoring in the form of arterial catheterization is not convenient and oscillometric measurement every 3–5 min is unable to detect this abrupt hemodynamic change. Park et al.[20] have examined the potential of PAT as a marker of BP increase which is usually detected in patients undergoing LMS surgery. They have recorded ECG and PPG (sampling rate 300 Hz) and noninvasive BP (oscillometric) every 3 min. PAT was calculated for each beat using the inbuilt filter function in Vital Recorder software. PPG waveform was also analyzed to obtain characteristic features such as height, width, and slope. PAT was measured like that of PTT used by Kim et al.[19] Laryngoscopic manipulations caused a change in mean SBP and PAT values as given in [Table 5] showing an inverse correlation of r = 0.582 (P < 0.001).
Table 5: Correlation between 1/PAT and systolic blood pressure during LMS (Park et al.)

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ROC curve analysis has shown that an 11.5% increase in the inverse of PAT could detect a 40% increase in SBP with 0.814 area under the curve. The authors have thus shown the ability of PAT in the detection of the abrupt hypertensive episode during laryngoscopic manipulations.


  Conclusion Top


PAT is conventionally measured from the R-wave of ECG to a fiducial point on a peripheral pulse waveform obtained from IPG or PPG. This measurement has varied from onset of the peripheral pulse to peak of its first or second-time derivative. Best results have been obtained by using the peak of the second-time derivative, considering ambiguity in the detection of the onset of the pulse. PAT finds applications in many fields and can be used in place of SBP for estimation of BRS, beat-to-beat BP monitoring, detection of MA, detection of mental stress, and monitoring of hypertensive episodes during LMS. Correlation between the inverse of PAT with systolic BP has ranged between 0.60 and 0.94 in the majority of the studies. The highest correlation has been obtained between changes in SBP and inverse of PAT making it most suitable for beat-to-beat BP monitoring during intensive care or microscopic surgery. This also makes it suitable for SBP variability as a substitute for a highly expensive Finapres system. This application of PAT may open new avenues in investigations relating to the autonomic nervous system.

Acknowledgement

The authors are grateful to Shri RK Jain, senior scientist, Electronics Division, Bhabha Atomic Research Centre for arousing our interest in PAT and Dr. Geeta S Lathkar, director, MGMCET and Dr. V.G. Sayagavi, vice principal, MGMCET for providing continuous encouragement throughout the study. The authors are also thankful to Shri Nazim Momin and Shri Bhaskar Gaikwad from BME Department, MGMCET for helping in the preparation of the manuscript.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Jindal GD, Sawant MS, Jain RK, Sinha V, Bhat SN, Deshpande AK Seventy-five years of impedance plethysmography in physiological data acquisition and medical diagnostics. MGM J Med Sci 2016;3:84-90.  Back to cited text no. 1
    
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Jindal GD, Lakhe AS, Jethe JV, Mandlik SA, Jain RK, Sinha V, Deshpande AK Photoplethysmography and its clinical applications. MGM J Med Sci 2017;4:89-96.  Back to cited text no. 2
    
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Chee Y, Lee J, Park H, Kim I Baroreflex sensitivity with pulse arrival time. Proceedings, 6th International Special Topic Conference on Information Technology Applications in Biomedicine, 2007. p. 67-9.  Back to cited text no. 5
    
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van Duijvenboden S, Hanson B, Child N, Lambiase PD, Rinaldi CA, Jaswinder G, et al. Pulse arrival time and pulse interval as accurate markers to detect mechanical alternans. Ann Biomed Eng 2019;47:1291-9.  Back to cited text no. 6
    
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Geddes LA, Voelz M, James S, Reiner D Pulse arrival time as a method of obtaining systolic and diastolic blood pressure indirectly. Med Biol Eng Comput 1981;19:671-2.  Back to cited text no. 7
    
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Escobar-Restrepo B, Torres-Villa R, Kyriacou PA Evaluation of the linear relationship between pulse arrival time and blood pressure in ICU patients: Potential and limitations. Front Physiol 2018;9:1848.  Back to cited text no. 13
    
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Rajala S, Ahmaniemi T, Lindholm H, Taipalus T Pulse arrival time (Pat) measurement based on arm ECG and finger PPG signals: Comparison of PPG feature detection methods for Pat calculation. Annu Int Conf Ieee Eng Med Biol Soc 2017;2017:250-3.  Back to cited text no. 14
    
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Park YS, Kim SH, Lee YS, Choi SH, Ku SW, Hwang GS Real-time monitoring of blood pressure using digitalized pulse arrival time calculation technology for prompt detection of sudden hypertensive episodes during laryngeal microsurgery: Retrospective observational study. J Med Internet Res 2020;22:e13156.  Back to cited text no. 20
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
 
 
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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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