Reproducibility of Pulse Wave Analysis and Pulse Wave Velocity

in Healthy Subjects

T. Pereira

, I. Santos

, T. Pereira

, H. Santos

, V. Almeida

, H. Pereira

1,3

, C. Correia

and J. Cardoso

Instrumentation Center, Physics Department, University of Coimbra, Coimbra, Portugal

Coimbra College of Health Technology, Coimbra, Portugal

ISA- Intelligent Sensing Anywhere, Coimbra, Portugal

Keywords: Optical Probe, Waveform Distension, Pulse Wave Analysis, Pulse Wave Velocity, Reproducibility.

Abstract: The hemodynamic parameters extracted from pulse pressure waveform, by pulse wave analysis (PWA) and

pulse wave velocity (PWV) are strong independent predictors of cardiovascular morbidity. The aim of this

study is to investigate the reproducibility of pulse pressure profile and arterial stiffness indicators, i.e.,

Augmentation Index (AIx), Subendocardial Viability Ratio (SEVR), maximum rate of pressure change

(dP/dt

max

), Ejection Time Index (ETI), as measured using a contactless optical system. Reproducibility was

evaluated in 13 healthy subjects by two senior operators (‘A’ and ‘B’) that acquired signals in alternate

order (ABAB or BABA). The PWV result showed a good inter and intra-operator reproducibility. The mean

difference between the two operators is 0.1570 m/s with a SD of 0.8160 m/s, this difference represents

approximately 3.49% of the arithmetic average of the means obtained by each operator per trial. Between

trials, differences of less than 8% of the mean PWV value for each operator were obtained. PWA

repeatability results are considered high for HR, strong for Aix and moderate for dP/dt

max

. The newly

developed optical system showed good reproducibility as evaluated by both inter-operator and intra-

operator methods.

1 INTRODUCTION

Cardiovascular diseases are the main cause of death

in the general population. For this reason, the

identification of risk factors at an early preclinical

stage of disease is an important clinical issue.

Besides, also markers of arterial stiffness such as

Pulse Wave Velocity (PWV) and Pulse Wave

Analysis (PWA) comprised of Augmentation Index

(AIx), Subendocardial Viability Ratio (SEVR),

maximum rate of pressure change (dP/dt

max

Ejection Time Index (ETI), have been shown, in

recent studies, to be strong independent predictors of

cardiovascular morbidity (Crilly et al., 2007).

Several standard techniques are widely used for

estimation of pulse pressure waveform and main

hemodynamic parameters, however, all of them

require direct contact with the patient’s skin at the

artery site, this procedure may distort the waveform

integrity. The optical solutions represent a

significant improvement to overcome this limitation

for measuring the distension waveform of the carotid

artery due to their truly non-invasive nature (Pereira

et al., 2011a; Pereira et al., 2011b; Pereira et al.,

2012).

In peripheral arteries, like the carotid, the

pressure wave travels across the arterial tree in a

compliant way, forcing the blood vessels to distend

elastically according to the pressure wave profile

and imparting a visible distension effect. The

distension waveform and the pressure waveform

have an analogous wave contour and, therefore, can

reciprocally be used for pulse wave analysis

(Laurent et al., 2006; Pereira et al., 2013a; Pereira et

al., 2013b).

In previously studies, the optical system proved

to be reliable in detecting the arterial distension

waveform. In order to evaluate the capability of the

developed optical device to accurately detect the

pulse waveform several studies was developed

(Pereira et al., 2011b, Pereira et al., 2013b).

This study investigates the reproducibility of

pulse pressure profile, and both inter-operator

(systematic differences among the observers) and

intra-operator (deviations of a particular observer's

score on a particular patient) variability analysis

221

Pereira T., Santos I., Pereira T., Santos H., Almeida V., Pereira H., Correia C. and Cardoso J..

Reproducibility of Pulse Wave Analysis and Pulse Wave Velocity in Healthy Subjects.

DOI: 10.5220/0004802502210228

In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS-2014), pages 221-228

ISBN: 978-989-758-011-6

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

were performed. Thus the aim of the present study is

to assess intra- and inter-operator reproducibility.

Reproducibility was evaluated in 13 healthy subjects

by two senior operators, and evaluates the degree of

closeness of the repeated measurements made on the

same subject either by the same instrument.

This is a prospective study and similar studies of

this kind presents a sample of the same magnitude

(Protogerou et al., 2012; Vappou et al., 2011).

The reproducilbity study covering inter-operator

and intra-operator variability analysis. Inter-operator

variability refers to systematic differences among

the observers. Intra-operator variability refers to

deviations of a particular observer's score on a

particular patient that are not part of a systematic

difference.

This work contributes to the design a protocol for

this type of non-invasive probes used in

determination of hemodynamic parameters, which

contains the required guidelines to assessment test

for the operator variability.

2 MATERIALS AND METHODS

2.1 Technology

The proposed probes were developed to measure the

arterial pulse wave profile at the carotid site and are

based on the reflectance fluctuations of the skin

surface during the underlying pulse wave

propagation (Pereira et al., 2011b; Pereira al., 2012).

The illumination source is provided by light

emitting diodes (LEDs) with 635 nm and the light

detection is performed by two photodetectors, placed

at a specific distance of 20 mm apart (see Figure1),

to assess the pulse pressure waveform at two distinct

spots, ensuring the accurate determination of local

pulse transit time (PTT) and thus, of the local PWV.

Figure 1: Structure of optical probe inside the plastic box.

The enclosing box contacts the skin, to stabilize

and maintain constant the distance between the

photodector and the artery site (3 mm), however in

the local of measurement there is no contact and

consequently no distortion of signal.

The signals were digitized with a 16-bit

resolution data acquisition system (National

Instruments, USB6210®) with a sampling rate of 20

kHz and stored for offline analysis using Matlab®

(R2011a).

2.2 Study Population

The group consisted of 13 healthy human

volunteers, normotensive and with no documented

history of cardiovascular disorders or diabetes that

had undergone signal acquisitions with the optical

probe. The characteristics of the volunteers are

presented in Table 1.

Table 1: Main characteristics of the sample.

Parameters Range values

n (Males/Females) 13 (7/6)

Age (years) 24.1 ± 2.2

Height (cm) 166.6 ± 8.0

Weight (kg) 63.8 ± 12.8

BMI (kg/m

) 22.8 ± 2.9

Brachial SBP* (mmHg) 113.5 ± 12.5

Brachial DBP* ( mmHg) 73.2 ± 9.1

Heart Rate* (bpm) 65.4 ± 11.4

BMI indicates body mass index; SBP, systolic blood pressure;

DBP, diastolic blood pressure.

* Measure in brachial, with commercial sphygmomanometer

(blood pressure cuff).

2.3 Study Protocol

Two trained blinded operators (further referred as

‘A’ and ‘B’) alternatively undertook 2

measurements each, in the same location, using the

same probe in the same day, over a short period of

time. The subjects rested for 10 minutes in supine

position, reached the physiological baseline

conditions, both operators measured blood pressure

(BP) before each measurement and acquired signals

in alternate order (ABAB or BABA). Each trial

consisted of few acquisitions, usually between 2 and

4, and the values of each trial were further averaged.

Similar reproducibility studies have been carried

BIOSIGNALS2014-InternationalConferenceonBio-inspiredSystemsandSignalProcessing

222

out with same protocol, that accepted as rigorous

approach this evaluation of PWA and PWV

repeatability (Crilly et al., 2007; Frimodt-Moller et

al., 2008). As expected BP, pulse pressure waveform

and consequently the hemodynamic indices

remained, are stable during the assessment period.

The sequence of operator was random, which reduce

bias will have tended to compromise intra-operator

variability. The study protocol was approved by the

ethical committee of the Centro Hospitalar e

Universitário de Coimbra, Portugal. All the subjects

were volunteers and gave a written informed

consent.

2.4 Hemodynamic Measurement

The assessment of the cardiovascular system

condition based on multi-parameters allows a more

precise and accurate diagnosis of the heart and the

arterial tree condition. The multiple parameter risk

response score is a useful tool to categorize patients

for selection of appropriate interventions. The

optical system allows the determination the several

parameters based in the pulse pressure wave profile,

and possible to overcome errors in the determination

of one of the parameters. Risk indicators, can be

determined from the main parameters extracted from

waveform and its time characteristics and pulse

wave velocity.

In the pulse wave analysis, AIx is the most

widely researched index and is defined as the ratio

of blood pressure amplitudes at the timings of the

reflection point (RP) and systolic peak (SP), thus

resulting in RP/SP expressed as a percentage. A

convention for the signal of AIx, defines when the

reflected wave arrival occurs earlier than the systolic

peak the AIx have positive value while a negative

value of AIx indicates that the reflected wave arrives

after the systolic peak (Crilly et al., 2007).

The Subendocardial Viability Ratio, or Buckberg

Index, varies between 119 and 254% in healthy

subjects, and is a parameter that estimates the

myocardial oxygen supply–demand relative to the

cardiac workload and is an indicator of

subendocardial ischaemia (Crilly et al., 2007).

The ejection time, also referred to as Left

Ventricular Ejection Time, corresponds to the

ventricular systolic ejection time between the aortic

valve opening and closing. Its ratio to the total

duration of the cardiac cycle represents the ETI (%)

and varies between 30 and 42% in healthy

individuals (Kara, Okandan et al., 2004).

The dP/dt

max

parameter reports the maximum rate

of pressure change in the systolic upstroke and gives

information about the initial velocity of the

myocardial contraction, which is also an index of

myocardial performance and the range of values

expected for a healthy population is 772 ± 229

(mmHg/s) (Miller et al., 2007).

2.5 Signal Processing

The pulse wave velocity was calculated using the

PTT determined by the cross-correlation method

between the signals from the two photodetectors.

A set of cyclic waveforms coming from one of

the channels, undergo segmentation and

normalization to the diastolic–systolic pressure

interval. The signal segmentation is performed using

the wave foot, detected by the minimum, and was

based on an automated peak detection function in

Matlab® (Peakdetect from the Mathworks, by Tom

McMurray). The average pulse are digitally low-

pass filtered (with a cut-off frequency of 30 Hz),

which removes the noise, thus allowing the signal

differentiation. The developed algorithm for

waveform features determination is based on

differential calculus and was applied to the

remarkable points as a tool to quantify arterial

pressure waveform features (Korpas et al., 2009).

An assessment of arterial brachial pressure by

conventional measurement using a

sphygmomanometer was conducted prior and after

the exam for calibration purposes. These values

were used to calibrate the carotid pressure waveform

as recommended and according to the calibration

method proposed by Kelly and Fitchett (Kelly &

Fitchett, 1992).

2.6 Statistical Analysis

The data are reported as mean values ± standard

error with 95% confidence intervals and percentages

were used to describe qualitative variables. The

Bland-Altman approach for ‘95% limits of

agreement’ was used in inter and intra-operator

differences in paired measurements.

Reproducibility was assessed by Intraclass

Correlation Coefﬁcients (ICC), Coefﬁcients of

Variation (CV), Standard Error of Measurement

(SEM) and Limits of Agreement (LA) (Euser et al.,

2008; Vanmolkot et al., 2005).

Intraclass correlation coefficient was computed

for repeatability studies, based on one-way analysis

of variance (ANOVA). ICC describes how strongly

measurements in the same group resemble each

other. The CV expresses the variation between

measurements in relation to the mean value of all

ReproducibilityofPulseWaveAnalysisandPulseWaveVelocityinHealthySubjects

223

measurements. The LA provides direct information

about the absolute measurement error. The standard

error of measurement takes the amount of

measurement error into consideration (Bartlett &

Frost, 2008). Statistical analysis was performed by

SPSS

software (SPSS Inc., Chicago, Illinois).

3 RESULTS

3.1 PWV Results

The normality of the variables distribution for each

trial/operator were assessed using the test of

normality Shapiro-Wilk, all the sets of PWV values

follow a normal distribution (Significance value

≥0.169, p<0.05). The correlation between the PWV

values obtained by both operators is plotted in

Figure 2a.

Figure 2: Comparison between two operators (A and B).

(a) Correlation between the operators for PWV

measurements. (b) Bland-Altman plot displays the inter-

operator difference for the two operators as a function of

the mean of the determined PWV.

The mean difference between the two operators is

0.1570 m/s with a SD of 0.8160 m/s as shown in a

Bland-Altman plot (Figure 2b). This difference

represents approximately 3.49% of the arithmetic

average of the means obtained by each operator per

trial.

Considering all measurements there is only one

that has a difference greater than 2 m/s, and just 4

measurements have a difference higher than 1 m/s.

According to Figure 2 the acceptable intra-operator

PWV differences (<1 m/s) are observed in 22

measurements (85%).

The between-operator ICC of 0.602 (95% from

0.12 to 0.82) revealed a moderate agreement between

classes (measurement made by operator ‘A’ and

operator ‘B’).

Considering variance results, in Table 2, there is

no evident variation depending on the operator.

However, considering the values between trials, the

trial 2 shows lower variance comparing to trial 1 for

each operator. Furthermore, the coefﬁcients of

variation obtained for inter-observer and intra-

observer reproducibility were less than 15%.

The graph represented in Figure 3 shows that

values obtained by operator ‘A’ are very similar to

the operator ‘B’. Also the mean values for PWV

from different trials of each operator have very close

values.

In spite of this apparent difference, the ICC for

both trials per operator shows that for operator ‘A’

there is a moderate agreement between trial 1 and 2

(ICC=0.674; 95% CI from 0.01 to 0.82) and for

operator ‘B’ this coefficient has a similar value of

agreement (ICC=0.654; 95% CI from -0.17 to 0.89).

Table 2: PWV mean values obtained by each operator A

and B, per trial.

Trial Ope

Range

(min-max)

(m/s)

Mean

(m/s)

Var

(3.090-

5.463)

4.263 0.734 0.539

(3.616-

5.699)

4.629 0.714 0.510

(2.932-

5.710)

4.568

0.649

0.422

(3.558-

5.729)

4.517

0.663

0.440

Ope: operator; SD: standard deviation; Var: variance.

To better understand the variability of the PWV

values, the values obtained within each operator and

between trials are represented in the Figure 4.

No significant association between the PWV

intra-operators values was found after a correlation

analysis. The average difference between the two

trials assessed by the operator A was

-0.3049 m/s with a SD of 0.7388 m/s as shown in a

BIOSIGNALS2014-InternationalConferenceonBio-inspiredSystemsandSignalProcessing

224

Figure 3: Bar graphs for mean values of PWV by operator.

with a SD of 0.7388 m/s as shown in a Bland-

Altman plot in Figure 4 b). This limit of agreement

(from -1.78 to 1.17 m/s) represents at most 6.9% of

the mean PWV for this operator.

The average difference between the two trials

assessed by operator B was 0.1123 m/s with a

0.6801 SD of m/s as shown in a Bland-Altman plot

in Figure 4 c). This limit of agreement (from -1.25 to

1.47 m/s) represents at most 7.6% of the mean PWV

value for operator B.

3.2 PWA Results

Relatively to the other PWA parameters the values

determined in this dataset by the optical system are

shown in Table 3.

The standard deviation of measurement errors is

therefore a reflection of the reliability of the test

response (Bartlett & Frost, 2008). The SEM is

expressed in the actual units of measurement,

making it easy to interpret, i.e. the smaller the SEM,

the greater the reliability and the values obtained for

HR, AIx and ETI parameter are low values, only in

the case of dP/dt

max

and SEVR were presents slightly

higher values for the SEM.

a) b)

c) d)

Figure 4: Comparison between two trials for two operators. (a) Correlation of PWV between two trials acquired by

Operator A. (b) Bland-Altman plot displays the intra-operator difference for the Operator A. c) Correlation of PWV

between the two trials acquired by Operator B. d) Bland-Altman plot displays the intra-operator difference for the Operator

ReproducibilityofPulseWaveAnalysisandPulseWaveVelocityinHealthySubjects

225

Table 3: Mean values of PWA hemodynamic parameters

for each operator.

Ope Mean SEM (95% CI) SD

HR (bpm)

A 65.41 1.47

62.48 to

68.35

11.18

B 64.95 1.79

61.34 to

68.57

11.90

AIx (%)

A -1.57 1.70

-5.15 to

2.00

13.61

B -4.19 1.89

-7.99 to -

0.39

12.51

SEVR (%)

A 149.4 9.38

130.98 to

168.53

71.20

B 152.9 13.04

126.63 to

179.84

86.53

dP/dt

max

(mmHg/s)

A 328.4 20.75

286.92 to

370.00

158.00

B 347.7 19.59

308.29 to

387.25

129.94

ETI (%)

A 42.24 1.96

38.31 to

46.16

14.93

B 42.61 2.27

38.04 to

47.18

15.04

3.2.1 Inter-Operator Repeatability

The proximity of the mean values Inter-operator is

expressed in the ICC results (Table 4). Some

parameters showed good agreement. As one can

observe, the HR and dP/dt

max

had shown high ICC

values, concordant with almost perfect agreement.

On the other hand for SEVR and ETI parameters,

the determined low ICC is congruent with fair

agreement. Concerning AIx, its corresponding ICC

values show a moderate level of between-operator

agreement.

In Figure 5 the results for AIx measurements for

all subjects for operator ‘A’ and operator ‘B’ are

represented. It is visible that there are not major

differences between AIx values obtained by the two

operators for each subject. The results in the figure

show a common trend between the values obtained

for AIx parameter by two operators measurement for

each subject.

A positive Augmentation Index could indicate a

case of arterial stiffness. With an increase in

stiffness there is a faster propagation of the forward

pulse wave as well as a more rapid reflected wave, a

positive AIx means that the reflected wave arrival

occurs earlier than the systolic peak is. Depending

on the AIx value (positive or negative) the pulse

wave type is defined as follows: when a negative

value occurs the pulse shows characteristic of

healthy subjects and when a positive value occurs

the pulse have characteristic of subjects suffering

from arterial stiffness (Almeida et al., 2013).

Table 4: Inter-operator repeatability of PWA: based in the

differences correspond to ‘Operator A’ measurement

minus ‘Operator B’ measurement).

ICC

(95%

CI)

Mean

diff

(2SD)

Limits of

agreement

HR (bpm) 0.976

0.95

0.99

-0.279

3.52

(7.03)

-7.31 to

6.75

AIx (%) 0.734

0.41

0.88

-1.929

10.01

(20.02)

-21.95 to

18.09

SEVR

(%)

0.472

-0.20

0.77

7.173

152.26

(304.52)

-151.75 to

166.09

dP/dt

max

(mmHg/s)

0.581

0.09

0.81

-2.660

14.96

(29.91)

-263.61 to

345.44

ETI (%) 0.442

-0.24

0.75

0.014

0.09

(0.19)

-32.57 to

27.25

Intraclass correlation coefficient (ICC) using an absolute

agreement definition.

Limits of agreement for differences= mean difference ± 2SD.

Mean diff means Mean of difference between measures.

Figure 5: Trends in AIx measurements: mean of values for

each subject by operator A and operator B.

3.2.2 Intra-Operator Repeatability

Comparing the ICC results from Table 5 with those

presented in Table 4, which are referent to within-

operator differences, one could see that there are no

major discrepancies, except for AIx that has a lower

ICC and dP/dt

max

that is slightly higher.

BIOSIGNALS2014-InternationalConferenceonBio-inspiredSystemsandSignalProcessing

226

Table 5: Intra-operator repeatability of PWA, based in the

differences corresponds to ‘trial 1’ measurement minus

‘trial 2’ measurement.

ICC

(95%

CI)

Mean

diff

(2SD)

Limits of

agreement

HR (bpm) 0.926

0.83

0.97

1.837

5.73

(11.46)

-9.62 to

13.30

AIx (%) 0.448

-0.23

0.75

-2.398

13.00

(26.00)

-28.40 to

23.61

SEVR

(%)

0.473

-0.20

0.77

-4.804

79.53

(159.05)

-163.86 to

154.25

dP/dt

max

(mmHg/s)

0.678

0.27

0.86

6.902

141.85

(283.70)

-276.80 to

290.60

ETI (%) 0.494

-0.16

0.78

0.740

14.63

(29.27)

-28.53 to

30.00

4 CONCLUSIONS

The reproducibility study was performed in 13

volunteers by two trained operators. Both operators

measured BP before each measurement and acquired

trials in alternate order. This measurements

reproducibility study has demonstrated a subjective

component based on the measurement techniques

used by different operators.

The main limitations of this study are its small

size and the inclusion of healthy volunteers rather

than patients. However it is common to evaluate

emerging techniques in volunteers initially and these

studies are important platforms for further method

improvement and subsequent patient studies.

The PWA repeatability results are considered

high for HR, strong for AIx, moderate for dP/dt

max

and low for SEVR and ETI. Actually, for all analysis

the resulting values for dP/dt

max

and SEVR differ

substantially from the ones presented as reference

and show the lower values for reproducibility

evaluation, probably originated by the calibration

method used.

The PWV results had a good inter and intra-

operator reproducibility judged by the Bland-Altman

plots as well as the test of differences between

measures. The two photodetectors (placed at a

precise and well-known distance of 20 mm), detect

the pulse wave propagation, along the arterial

segment. This distance could be a limitation only in

cases was a small segment of carotid artery is

accessible, which difficult the position of two

photodetectors centered on the artery.

The factors such as the position of two

photodetectors in the carotid vessel, tremors in the

hands of an operator, respiratory movements of the

volunteers could introduce differences in the

measurements between operators and trials. These

factors might affect the measurements and are

possible to quantify making changes in the probe by

the introducing an accelerometer or a respiratory

band in the volunteers, however escaped to the

objective of this work.

The newly developed optical system showed

good reproducibility as evaluated by both inter-

operator and intra-operator methods. This study

could be extended by comparing PWV and PWA

values from patients with vascular risks.

The cohort size is only 13 but it is enough to

draw conclusions about both inter-operator and

intra-operator variability analysis, however the

present results and clinical implications need to be

confirmed by larger studies that enable the predicted

ability of the optical system and including

population with heterogeneity characteristics: age,

blood pressure, BMI, cardiovascular diseases.

ACKNOWLEDGEMENTS

The authors acknowledge the support from

Fundação para a Ciência e Tecnologia (FCT) for

funding (SFRH / BD / 79334 / 2011). Project

developed under the initiative of QREN, funding by

UE/FEDER, through COMPETE - Programa

Operacional Factores de Competitividade.

REFERENCES

Almeida, V., Vieira, J., Santos, P., Pereira, T., Pereira, H.,

Correia, C., … Cardoso, J. (2013). Machine Learning

Techniques for Arterial Pressure Waveform Analysis.

Journal of Personalized Medicine, 3(2), 82–101.

Bartlett, J. W., & Frost, C. (2008). Reliability,

repeatability and reproducibility: analysis of

measurement errors in continuous variables.

Ultrasound in obstetrics & gynecology : the official

journal of the International Society of Ultrasound in

Obstetrics and Gynecology, 31(4), 466–75.

Chemla, D., Nitenberg, A., Teboul, J.-L., Richard, C.,

Monnet, X., le Clesiau, H., … Brahimi, M. (2008).

Subendocardial viability ratio estimated by arterial

tonometry: a critical evaluation in elderly hypertensive

patients with increased aortic stiffness. Clinical and

experimental pharmacology & physiology, 35(8), 909–

15.

Crilly, M., Coch, C., Bruce, M., Clark, H., & Williams, D.

ReproducibilityofPulseWaveAnalysisandPulseWaveVelocityinHealthySubjects

227

(2007). Indices of cardiovascular function derived

from peripheral pulse wave analysis using radial

applanation tonometry: a measurement repeatability

study. Vascular medicine (London, England), 12(3),

189–97.

Euser, A. M., Dekker, F. W., & le Cessie, S. (2008). A

practical approach to Bland-Altman plots and variation

coefficients for log transformed variables. Journal of

clinical epidemiology, 61(10), 978–82.

Frimodt-Moller, M., Nielsen, A. H., Kamper, A.-L., &

Strandgaard, S. (2008). Reproducibility of pulse-wave

analysis and pulse-wave velocity determination in

chronic kidney disease. Nephrology, dialysis,

transplantation : official publication of the European

Dialysis and Transplant Association - European Renal

Association, 23(2), 594–600.

Kara, S., Okandan, M., Usta, G., & Tezcaner, T. (2004).

Investigation of a new heart contractility power

parameter. Computer methods and programs in

biomedicine, 76(2), 177–80.

Kelly, R., & Fitchett, D. (1992). Noninvasive

determination of aortic input impedance and external

left ventricular power output: a validation and

repeatability study of a new technique. Journal of the

American College of Cardiology, 20(4), 952–963.

Korpas, D., Hálek, J., & Dolezal, L. (2009). Parameters

describing the pulse wave. Physiological research /

Academia Scientiarum Bohemoslovaca, 58(4), 473–9.

Laurent, S., Cockcroft, J., Van Bortel, L., Boutouyrie, P.,

Giannattasio, C., Hayoz, D., … Struijker-Boudier, H.

(2006). Expert consensus document on arterial

stiffness: methodological issues and clinical

applications. European heart journal, 27(21), 2588–

605.

Miller, R. S., Rudra, C. B., & Williams, M. a. (2007).

First-trimester mean arterial pressure and risk of

preeclampsia. American journal of hypertension,

20(5), 573–8.

Pereira, T, Cabeleira, M., Matos, P., Borges, E., Cardoso,

J., & Correia, C. (2011a). Optical Methods for Local

Pulse Wave Velocity Assessment. In 4th International

Joint Conference on Biomedical Engineering Systems

and Technologies Rome Italy (pp. 74–81).

Pereira, T, Santos, I., Oliveira, T., Vaz, P., Santos, H.,

Pereira, H., Cardoso, J. (2013a). Local PWV and other

Hemodynamic Parameters Assessment : Validation of

a New Optical Technique in an Healthy Population. In

6th International Joint Conference on Biomedical

Engineering Systems and Technologies, Barcelona

Spain (Vol. 1, p. 10).

Pereira, Tânia, Oliveira, T., Cabeleira, M., Matos, P.,

Pereira, H. C., Almeida, V., … Correia, C. (2011b).

Signal Analysis in a New Optical Pulse Waveform

Profiler for Cardiovascular Applications. Signal and

Image Processing and Applications / 716: Artificial

Intelligence and Soft Computing, (Sipa), 19–25.

Pereira, Tânia, Santos, I., Oliveira, T., Vaz, P., Correia, T.,

Pereira, T., Correia, C. (2013b). Characterization of

Optical System for Hemodynamic Multi-Parameter

Assessment. Cardiovascular Engineering and

Technology, 4(1), 87–97.

Protogerou, A. D., Papaioannou, T. G., Sfikakis, P. P.,

Blacher, J., Karatzis, E., Lekakis, J. P., … Safar, M. E.

(2012). Differences in pulse pressure day variability

between the brachial artery and the aorta in healthy

subjects. Artery Research, 6(1), 34–40.

Tânia Pereira, Manuel Cabeleira, Patrícia Matos, Elisabeth

Borges, Vânia Almeida, João Cardoso, C. C. (2012).

Non-contact Pulse Wave Velocity Assessment.

Springer-Verlag Berlin Heidelberg 2012, BIOSTEC

2011, CCIS 273, (2), 246–257.

Vanmolkot, F. H. M., & de Hoon, J. N. J. M. (2005).

Reproducibility of forearm vasodilator response to

intra-arterial infusion of calcitonin gene-related

peptide assessed by venous occlusion

plethysmography. British journal of clinical

pharmacology, 59(4), 387–97.

Vappou, J., Luo, J., Okajima, K., Di Tullio, M., &

Konofagou, E. E. (2011). Non-invasive measurement

of local pulse pressure by pulse wave-based ultrasound

manometry (PWUM). Physiological measurement,

32(10), 1653–62.

BIOSIGNALS2014-InternationalConferenceonBio-inspiredSystemsandSignalProcessing

228