An Unobtrusive Wearable Device for Ambulatory Monitoring of

Pulse Transit Time to Estimate Central Blood Pressure

Hanne O. Austad, Jon Vedum, Morten H. Røed, Steffen Dalgard, Tomas Brødreskift,

Anders E. Liverud, Frode Strisland and Trine M. Seeberg

SINTEF Informatics and Communication Technology, NO-0314 Oslo, Norway



Keywords: Wearable Sensor, Blood Pressure, Pulse Transit Time, ICG, PPG.

Abstract: There is a clinical need for improved ambulatory, frequent and unobtrusive monitoring of blood pressure

and cardiac parameters like systolic time intervals. Truly unobtrusive wearable devices combining

impedance cardiography with other sensors may be one possible solution. The IsenseU-BP+ device

presented in this article measures single channel ECG, impedance cardiography and photo plethysmography

at the chest. The device also measures activity and posture, as well as skin temperature. In this study, we

report on the possibility to use these signals to measure pulse transit time for estimating blood pressure

changes. Six subjects has been tested. Four of them showed good correlation between PTT and mean

arterial pressure while two of the subjects had too low signal to noise ratio in the photoplethysmography

signal for good estimation of PTT. Thus these results show that the quality of the raw data is promising for

calculating a pulse transit time that shows good coherence with mean arterial pressure. 

1 INTRODUCTION

High blood pressure, hypertension, is estimated to

cause about 13% of the total of all deaths world

wide. In 2008 40% of adults aged 25 and over

suffered from hypertension globally (World Health

Organization Global Health Observatory (GHO)

data on raised blood pressure, n.d). Raised blood

pressure levels represent a major risk factor for

coronary heart disease and stroke. The risk increases

with increasing blood pressure level. Treating

systolic blood pressure and diastolic blood pressure

to get below 140/90 mmHg, is associated with a

reduction in cardiovascular complications (Mancia

et al., 2013). Increasingly, the medical community is

also focusing on blood pressure variability

(Rothwell et al., 2010) and the night level blood

pressure in the assessment and treatment of

hypertension. For a person with high and poorly

controlled blood pressure, the pressure often varies

significantly throughout the day, as well as between

days. Point measurements taken in a doctor's office

therefore tend to be inadequate or even misleading.

For ambulatory monitoring to evaluate the variation

during day and night at home the state of the art is to

measure blood pressure over a 24-hour period with

cuff-based equipment. Typically, point

measurements are taken three times per hour during

daytime and once per hour during sleep. The

equipment is usually validated at rest only (O'Brian

et al., 2010). Patients are instructed to sit down when

the measurements are to be taken, thereby

interfering with daily living. A significant group of

the patients finds the cuff inflation stressful and

disturbing, and this is particularly a problem during

night. Thus, there is a need for better ambulatory

blood pressure measurement equipment.

One approach for a new cuff-less ambulatory

blood pressure system is to measure the pulse wave

velocity or the inversely proportional pulse transit

time (PTT). Assumed correlation between blood

pressure and PTT is based on the Moens-Korteweg

equation (Nichols and O'Rourke, 2005), which

describes how the pulse wave velocity of elastic

tubes are associated to structural arterial stiffness.

The average pressure of the arterial wall defines the

stiffness and therefor PTT should correlate better

with Mean Arterial Pressure (MAP) than systolic

and diastolic blood pressure. Different technical

solutions have been proposed and several studies

show correlation between PTT and blood pressure (a

good summary was given in Buxi et al., (2015)).

Austad, H., Vedum, J., Røed, M., Dalgard, S., Brødreskift, T., Liverud, A., Strisland, F. and Seeberg, T.

An Unobtrusive Wearable Device for Ambulatory Monitoring of Pulse Transit Time to Estimate Central Blood Pressure.

DOI: 10.5220/0005701401790186

In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Volume 1: BIODEVICES, pages 179-186

ISBN: 978-989-758-170-0

179

Several of the studies measured the time from ECG

R-peak to the pulse wave reached a peripheral

artery. This time measurement includes both PTT

and part of the pre-ejection period, which is the

period from start of the depolarization of the heart,

represented with the ECG-Q wave, to the aortic

valve opening. Both the pre-ejection period and the

PTT vary with blood pressure, and combining the

two makes extraction of blood pressure values

difficult (Muehlsteff, Aubert and Shuett, 2006).

Including part of the pre-ejection period also makes

the measurement dependent on posture (Muehlsteff,

Aubert and Morren, 2008). Impedance cardiography

(ICG) can be used to detect aortic valve opening and

therefore the pre-ejection period can be excluded

from the measurements. ICG is a diagnostic method

based on measurement of the electrical properties of

the biological tissues applied to the thorax region.

Changes in impedance on each heartbeat reflect

changes in blood volume in the great vessels, but the

origin of the signal is complicated and not well

understood (Patterson, 2010).

In most of the studies estimating blood pressure

based on PTT, as well as in commercially available

devices (ViSiMobile, n.d.), a peripheral point at the

finger or earlobe is used. Using e.g. the finger allows

vasoconstriction (narrowing of the blood vessels

resulting from contraction of the muscular wall of

the vessels), to affect the results (Budidha and

Kyriacou, 2014). Vasoconstriction can be caused by

e.g. exercise or temperature changes. Measuring the

peripheral pulse on the chest makes the system less

vulnerable to vasoconstriction. Sola et al. (2013)

have demonstrated a chest sensor system complying

with the British Hypertension Society requirements

of Grade A blood pressure monitors for MAP

readings. PTT in Solà et al.'s system is measured

from opening of the aortic valve to the internal

thoracic artery, just after it arise from the subclavian

artery. However, only a prototype setup, that is not

fully integrated, is shown and only results for

subjects at rest in supine position were presented.

This paper introduces a new, compact and

unobtrusive wearable sensor device intended for

long term continuous blood pressure estimations.

This device, IsenseU-BP+, is to our knowledge the

first fully integrated device aiming for estimating

blood pressure, with ECG, ICG and photo

plethysmography (PPG) sensors as well as all

necessary electronics and processing; everything

combined in one small unit strapped around the

chest which make it truly unobtrusive in daily life.

Results from tests that compares the individual

sensor signal quality to reference sensors are

presented, followed by PTT measurements and an

evaluation of how these correlates with changes in

blood pressure.

2 MATERIALS AND METHODS

2.1 The IsenseU-BP+ Device

Figure 1: The IsenseU-BP+ wearable device with

electrodes.

Physically, the device resembles the heart rate

monitor commonly used during exercise, but with

the addition of three standard ECG electrodes. The

electronic compartment has an elliptic-like form

with a major axis 12.5 cm, and minor axis of 4.5 cm.

An image of a subject wearing the device is shown

in figure 1. The device is built around a 32-bit ARM

Cortex-M3 microcontroller (Cypress PSoC® 5LP),

and provides wireless Bluetooth communication.

The Bluetooth Serial Port Profile is implemented for

live transmission of all data, and a Continua Health

Alliance based Health Device Profile

implementation is made for exchange of a sub-set of

the data. An internal flash memory allows offline

data logging. The belt is a commercially available

off-the-shelf belt with rubber electrodes.

There are three primary sensors:

1) A single-channel (2-electrode) ECG circuit

detecting the electrical activity of the heart

2) ICG that monitors variations in the electrical

impedance of the heart region during the contraction

cycle. This is a four-point measurement, using two

electrode sets for sourcing a weak AC current (1mA

RMS, 60 kHz), and two sense electrodes.

3) A PPG sensor detecting changes in the blood

flow at the chest. A green LED (570nm) sends light

pulses into the skin, and the returned light is

measured by a photodetector. The LED and the

BIODEVICES 2016 - 9th International Conference on Biomedical Electronics and Devices

180

Figure 2: Drawing of the IsenseU-BP+ wearable device

with sensors.



detector are mounted approximately 6 mm apart on

the rear of the device. The PPG sensor location at

the chest, will make the measurements less affected

by vasoconstriction than when measuring at the

finger.

To reduce the number of electrodes, the same

electrodes are used for both ICG and ECG sensing.

One of these electrodes is located at or close to the

lower part of sternum and the other close to the left

collarbone. The ICG current source uses the two

chest-belt electrodes in parallel in addition to an

electrode behind the neck. Electrode locations

optimize the ICG signal rather than the ECG signal.

Locations are selected after in-house testing based

on work by Patterson (2010) and inspired by the

testing done by Tan, Lai and Hwang (2006) on

electrode placement with the Physio Flow®

impedance cardiograph device for cardiac output

(Physioflow, n.d.). The position of the sense

electrodes gives a non-standard ECG waveform, but

does not influence the detection of the R-peak of the

ECG signal or the R-to-R distance or variation.

Figure 2 shows a drawing of IsenseU-BP+ with

sensor locations. Mechanically, the device was

designed to be comfortable for both genders of all

weights, with rounded edges and smooth surfaces.

The prototype was made by rapid prototyping with

laser sintered plastic (PA2200).

PTT was measured from the ICG-B point (see

figure 3) to the point of pulse arrival seen in the PPG

signal. The ICG-B point indicates the opening of the

aortic valve. In this work a method for ICG-B point

estimation described by Van Lien et al. (2013) was

used. Even though this estimation method did not

estimate pre-ejection period with the accuracy

required by van Lien et al. (2013), the precision of

the ICG-B-point detection was judged sufficient for

this first evaluation of using IsenseU-BP+ to

estimate blood pressure changes. The RC interval

was first computed as the time between the R-peak

of the ECG and the C point of the ICG trace (RC in

ms) Thereafter, the time from R-peak to B (RB in

Figure 3: Detection of distal and proximal time from PPG

and ICG signals. (PEP – pre ejection period of the heart).

ms) was calculated according to van Lien et al

(2013), RB = -15 + (0.7*RC). Knowing the timing

of the R peak and the RB distance, the time of the B-

point is found. The distal time was found from the

PPG signal as the foot of the pressure wave. This

was defined for a heart cycle by the intersection of

the tangent through the minimum PPG and the

tangent through the maximum slope of the PPG.

Finally, PTT was calculated as the difference

between time of the PPG

Foot

and the B-point. The

characteristic points for the signals are shown in

figure 3.

2.2 Test Setup

According to the Norwegian Health Research Act,

no approval by committee for medical and health

research ethics was needed for these tests. For

storing personal data, an approval from the The Data

Protection Official for Research under the Personal

Data Act/Personal Health Data Filing System Act

was obtained.

The IsenseU-BP+ ICG and ECG sensors were

compared to a BioNomadix system (BioPac

Systems, Inc., Goleta, CA, USA). The fields of two

ICG sensors applied at the same time may affect the

result of the sensors, and therefore the testing with

the two systems was done sequentially. The

sampling rate for IsenseU-BP+ sensors was 250 Hz,

while for the BioNomadix system it was 1 kHz. The

Nonin finger signal was captured with a 100Hz low

pass filter, and BioNomadix ECG and ICG with a

20Hz filter. IsenseU-BP+ sensors were captured

ufiltered. Both IsenseU-BP+ and BioPac system was

attached before the test started. The subjects rested

for 5 minutes to minimize changes in heart rate. For

ICG the same electrodes were used for both systems.

For BioNomadix ECG the electrodes were in pulse

An Unobtrusive Wearable Device for Ambulatory Monitoring of Pulse Transit Time to Estimate Central Blood Pressure

181

belt position with ground on the right hip. ICG and

ECG with the BioNomadix system as well as PPG

signal from a Nonin 8000AA finger clip sensor

(Nonin Medical, Inc, Plymouth, MN, USA) were

recorded for 1 minute, while the IsenseU-BP+

device was turned off. When the BioNomadix units

were turned off, its wires for ICG was switched with

the IsenseU-BP+ electrode wires. IsenseU-BP+ were

turned on for recording of ICG, ECG and PPG for 1

minute.

IsenseU-BP+ was tested for correlation between

PTT and blood pressure on six healthy volunteers,

three men and three women, aged 25 to 45. The

persons were in supine position with upper body

slightly elevated (~10 degrees.). Blood pressure

changes were induced using an isometric handgrip

manoeuvre. The reference system used for

measuring blood pressure was the CNAP® Monitor

500 HD (CNSystems Medizintechnik AG; Graz,

Austria). This system is precise compared to arterial

blood pressure measurements for MAP and diastolic

blood pressure, but with some variation for systolic

blood pressure (Ilies et al., 2015; Wagner et al.,

2015). Jamar® Plus+ Digital Hand Dynamometer

(Patterson Medical /Samsons' Preston, Warrenville,

IL, USA) was used to define the maximum grip

force of the right hand and to monitor the grip force

during the handgrip tests. Target handgrip force

during test was 30% of maximum force. The

CNAP® system was calibrated according to the

instruction manual using the integrated upper arm

cuff immediately before the tests were started. The

test protocol started with a 5 minutes rest period in

supine position, followed by three periods of

handgrip exercise lasting for minimum 3 minutes

each, and with at least 1.5 minutes intermediate rest.

At the end, the subject rested until blood pressure

was stable before he/she raised and a final upright

measurements were done. The CNAP® system was

recalibrated when standing up.

2.3 Statistical Methods

To define the relationship between PTT and MAP a

linear correlation has been assumed, and the least

square regression method has been used to find the

best linear fit. To evaluate the fit of the line the R

values (based on R

calculations) and root mean

square values for each point to the regression line,

has been calculated.

Figure 4: Comparing approximately six seconds ECG,

ICG and PPG from IsenseU-BP+ with ECG and ICG from

BioNomadix and PPG from Nonin finger sensors. The

BioNomadix signals and Nonin finger sensor signal was

recorded prior to the IsenseU-BP+ signal.

Figure 5: Comparing IsenseU-BP+ and CNAP® heart rate

(HR) for subject 5.

3 RESULTS

3.1 Verification against Reference

Sensors

As simultaneously recording of the ICG raw signals

with the two systems is not possible, raw data have

not been quantitatively compared, only a qualitative

comparison of signal form was done. Figure 4 show

data from subject 1. ECG, ICG and PPG data from

the middle of the recording with reference sensor

signals are compared to signals from IsenseU-BP+.

The signals were scaled to show approximately the

same amplitude. The figure shows IsenseU-BP+

ICG and PPG filtered using a 15Hz 4th-order

Butterworth filter.

IsenseU-BP+ calculates heart rate from the ECG

R-peak-to-R-peak interval. Figure 5 compares heart

rate from IsenseU-BP+ and heart rate detected by

the finger cuff in the CNAP® equipment for subject

5. The figure shows the test with three handgrip

manoeuvres that increase the heart rate and blood

pressure.

BIODEVICES 2016 - 9th International Conference on Biomedical Electronics and Devices

182

Figure 6: MAP (green) from CNAP® reference equipment

plotted together with PTT (black) from IsenseU-BP+

equipment. Plotted PTT is a moving average of 10

samples/heart cycles, while MAP shows every heart cycle.

Data is from subject 5.



Figure 7: Average PTT plotted versus the corresponding

MAP, for the start and end rest periods, and the elevated

blood pressure peaks for subject 1, 2, 5 and 6.

3.2 Correlation between PTT and

Blood Pressure

Six subjects completed the test protocol for

correlation study. In this first test it was however

only possible to estimate PTT with a reasonable low

level of noise in four of the six data sets, and only

results from these four data sets are further analyzed.

Possible reasons for the noise are discussed in

subsection 4.1.

Figure 6 shows the estimated PTT from IsenseU-

BP+ and MAP from the CNAP® reference

equipment through a complete test for subject 5. For

PTT the moving averages of 10 heart cycles was

plotted. MAP values was plotted for every heart

cycle. Figure 7 shows PTT versus MAP for five

different periods of the test: The rest period before

handgrip manoeuvre, the three blood pressure peaks

during the handgrip manoeuvres and the rest period

after the handgrip manoeuvre. During the handgrip

manoeuvre, the MAP values used was the maximum

moving average of 10 heart cycles and the PTT was

the, minimum moving average in the same peak

Table 1: R-values for linear fit of PTT as function of

MAP, RMS values for MAP to the fit line, and slope and

interception for the line. Subject 3 and 4 had too much

noise.

Subject

R-value

linear fit

Average

RMS

value

Slope Interception

1 0.93 4.2 -0,6 173,4

2 0.93 5.0 -0,6 145,4

5 0.93 11.0 -0,9 231,9

6 0.95 4.4 -0,7 180,4

(within ±15s from the detected MAP peak). For the

start and end rest periods, an average MAP of

approximately 30 seconds with stable blood pressure

and a corresponding average PTT value was used.

The figure shows a linear relation between MAP and

PTT. Table 1 summarize the R-values for linear fit

of the regression lines, as well as the average root

mean square values for the measured PTT value's

deviation from the line.

4 DISCUSSION

4.1 Detection of the Characteristic

Points and Heart Rate

In figure 4 a representative part of the signals from

IsenseU-BP+ is compared to signals from reference

systems. The ECG R-peak is less prominent with the

IsenseU-BP+ location of electrodes. For all subjects

ECG R-peaks were easily detectable, both for using

as a guide for detection of the ICG-C-peak, and for

calculating of heart rate based on R-R interval.

Figure 5 compares the heart rate detected by the

IsenseU-BP+ device and the CNAP® system. There

are some divergent heart rate measurements for both

systems, but the periods with divergent

measurements were similarly detected by both

systems and was probably realistic. These results

shows that the use of combined ECG and ICG sense

electrodes are acceptable. ICG signals in figure 4

were recorded with the same electrodes and have

similar shape. The IsenseU-BP+ ICG signal had

some noise, even though IsenseU-BP+ had a lower

filter frequency in this plot. The subject had a double

ICG-C peak and this is more clearly seen in the

BioNomadix recording and may be due to the lower

filter frequency and lower sampling rate used for

IsenseU-BP+ in this study. For the detection of the

ICG-C peak, the quality of the ICG signal from

IsenseU-BP+ was similar to BioNomadix, but the

lower sampling rate decreased the resolution. The

An Unobtrusive Wearable Device for Ambulatory Monitoring of Pulse Transit Time to Estimate Central Blood Pressure

183

IsenseU-BP+ ICG signal quality was not evaluated

for direct detection of B-point.

van Lien et al (2013) did not find the estimation

of ICG-B point through RC distance to be precise

enough for pre-ejection period estimation. They

were looking for changes in order of 3.5 ms in

individual heart cycles. In the laboratory/

ambulatory study they had a mean difference

between the actual pre-ejection period and estimated

pre-ejection period of +8ms/-4ms. Approximately

half of the error was due to using a fixed value for

the period from onset of depolarization of the heart

till ECG-R. The error in the individual heart cycle

RB period in their study was then +4ms/-2ms. We

have looked at an averaged PPT value and assuming

the error in B detection had a random component,

the averaging decreased the error. A change in mean

blood pressure of 10 mmHg is expected to give a

change in PTT about 8ms-16ms (Proenca et al.,

2010). Their calculations was based on PTT values

in the range 100ms to 200ms. Thus, the error caused

by this method for ICG-B point detection will

influence the possibility to detect small changes in

blood pressure, and the beat-to-beat variation. For

changes in the range evaluated in this study (>20

mmHg and averaged over 10 heart cycles) the error

of the ICG-B point detection was judged acceptable.

Figure 4 shows that during supine rest the quality

of the PPG signal is good. The PPG-foot is as

sharply defined when measured at the chest as at the

finger. It was observed that quality of the chest PPG

signal vary with small changes in location of the

sensor as well as with the pressure towards the skin.

Breathing will cause changes in the level of the PPG

signal. In this study, 2 out of the 6 subjects had high

noise in their PPG foot detection. Initial studies of

these data indicates that this is caused by low signal

quality due to none-optimal placement of the PPG

sensor, and filtering of the PPG signal to reduce

breathing artefacts. Filtering to remove the breathing

artefacts without influencing the PPG foot detection

must be further improved. In this device, the PPG

sensor has only one LED, while others have

suggested advanced arrays of LEDs and detectors

(Solà et al., 2011). For a more robust PPG foot

detection during movement an improvement in the

PPG sensor and better algorithms for motion artefact

suppression are required.

4.2 IsenseU-BP+ as a Device for

Estimating Blood Pressure

To evaluate blood pressure, physicians usually

relates to all the three blood pressure values;

systolic, diastolic and mean. According to the

Moens-Kortweg equation (Nichols and O'Rourke,

2005) estimation techniques based on pulse wave

velocity, and its inversely proportional pulse transit

time, provides estimates of MAP and not systolic or

diastolic pressure, since the average pressure of the

arterial wall defines the structural arterial stiffness.

Based on this, this study focus on MAP. Others have

however reported good correlation with systolic

blood pressure.

Measured PTT and MAP versus time are plotted

for subject 5 in figure 6. These data indicates that the

measured PTT response is delayed compared to the

pressure measured with the finger cuff. This may be

due to measurements at different locations. Central

blood pressure changes may differ from peripheral

blood pressure changes. Further work is needed to

investigate this delay, whether it shows a real

physiological difference or if it is caused by a

weakness in the algorithms that detects the

characteristics point in the raw signal. MAP during

rest before the test is higher than after the test. This

decrease was observed for several subjects and may

be due to a drift in the CNAP® reference equipment.

The first part of the test lasted 35 minutes with no

recalibration of the CNAP® reference system during

the test. The default recalibration, with arm cuff,

interval of the CNAP® equipment is 15 minutes.

This possible small drift has not been judged critical

for these initial tests to verify the design of the

IsenseU-BP+ device.

The PPT values in range 80ms-180ms are

reasonable compared to the overall value of 95ms

presented by Solà et al. (2013). IsenseU-BP+ detects

the PPG signal further away from the heart than the

system made by Solà et al. (2013).

Muehlsteff, Aubert and Morren (2008) have

found that when the person changed posture form

lying to sitting the pre-ejection period increased

significantly (25-45 ms) while blood pressure was

stable or slightly increased. We found a slight

decrease in PTT when subject rose corresponding to

an expected slight increase in blood pressure, thus

the PTT measurements was not dependent on

posture (results not shown).

Figure 7 and table 1 show good correlation

between PTT and MAP for the four subjects

evaluated (two excluded due to noise in PPG

measurements as discussed in section 4.1). The

number of points in the regression analysis was

however low, and there were also an uncertainty in

the MAP measurements. To increase the confidence

in the regression parameters, a test set-up that gives

more points per person is needed.

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184

The maximum of the moving average CNAP®

MAP and the minimum the moving average

IsenseU-BP+ PTT, within ±15s of the time for

maximum MAP, are used in the plot. The maximum

MAP and minimum PTT do not match exactly in

time (as seen also in figure 6); this may be related to

the different location of the sensors but has to be

further investigated. The current version of the

equipment was not intended for beat to beat

comparison of values and hence this approach is

judged acceptable. With more stable changes in

blood pressure, a longer averaging period could be

used. The slope of the PTT – MAP linear regression

line differs between persons and individual

calibration functions will be needed. This is the

same as reported by others (Solà et al., 2013).

As seen from the RMS values in table 1 subject 5

has significantly higher RMS values. This is mainly

caused by eight subsequent high values of individual

heart cycle MAPs in the middle blood pressure peak.

These values, which differ from the shape of the

curve, can be seen in figure 6. During the same

blood pressure peak, also divergent heart rate

measurements were observed with both systems

(figure 5). Excluding these eight MAP values lowers

the RMS values to the level of the other subjects

(not shown).

According to the British Hypertension Society

standard, a blood pressure device falls into the

category Grade A if it complies with a cumulative

percentage (CP) of the readings within ±5mmHg >

60%, CP at ±10 mmHg > 85% and CP at ±15 mmHg

> 95%. This standard is defined for systolic and

diastolic blood pressure, and is mostly used for cuff

based equipment measuring slow changes in blood

pressure (measurement time is 20s-60s). The hand

grip manoeuvre test induced pronounced changes for

a short period of time and therefore it was only

possible to average about ten heart beats (5s-10s).

The subjects in this test was only tested once,

therefor there are not enough data to calculate the

calibration curve, and subsequently see how a new

dataset fits into this. Calculating the error for the

points used to make the calibration curve 85% of the

measurements are within 10 mmHg, 90% of the

measurements are within ±15mmHg, but only 25%

within 5 mmHg. Max deviation are 20 mmHg. The

MAP estimations diverging most from the estimated

relationship are caused by the high MAP readings

for test subject 5 described in the former section.

The test setup with short periods of induced high

blood pressure and test equipment measuring on

different locations of the body, makes the result

vulnerable for short time deviations and anomalies.

This must be taken into account when planning a

more thorough verification test.

These results are very promising taking into

account the demanding tests and the known

weaknesses in the current version of test equipment.

The raw signal sampling rate used in this study are

too low and more work has to be done to improve

the signal filtering (adaptive filtering) and

algorithms for B-point detection. These changes may

be implemented in the embedded software in the

device. It may also be necessary to improve the PPG

sensor through hardware improvements, the

IsenseU-BP+ is prepared for a second LED. In

addition, there are some uncertainties in the

reference measurements when it comes to

calibration and differences between central and

finger blood pressure.

Based on this it is reasonable to assume that the

estimation of PTT and correlation with MAP can be

further improved, and that a grade A classification is

possible with the current design. These

improvements may also make the equipment

suitable for studying beat-to-beat variations.

5 CONCLUSIONS

We have presented IsenseU-BP+, a new compact

wearable device suitable for both female and male

users. The first testing shows that it is feasible to

make an easy to use device to monitor blood

pressure changes and possibly additional heart

parameters. More effort has to be put into the PPG

sensor design and the signal processing algorithms

for characteristic point's detection to get stable and

reliable results for a wide variety of persons. Testing

during activity is also needed. The device has to be

tested on a wide range of persons (different gender,

age and BMI) to show that a manageable calibration

regime for PTT to blood pressure calculation is

feasible.

ACKNOWLEDGEMENTS

The research leading to these results has been

carried out within the d-LIVER integrated project,

which has received funding from the European

Union's Seventh Framework Programme (FP7/2007-

2013) under grant agreement no. 287596.

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185

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