WIRELESS DEVICE FOR NONINVASIVE RECORDINGS

OF CARDIO-RESPIRATORY SIGNALS

Pedro Giassi Junior, João Fernando Refosco Baggio, Raimes Moraes

Electrical Engineering Department, Federal University of Santa Catarina, Florianópolis, Brazil

Maurício Gonçalves de Oliveira

Medical School Hospital, Federal University of Santa Catarina, Florianópolis, Brazil

Keywords: Heart rate variability, Autonomic nervous system, Respiratory sinus arrhythmia, Esmolol, Atropine,

Wireless communication.

Abstract: This work describes a portable device that acquires two ECG leads, pulse photopletismography waveform

and respiratory flow waveform that are sent, using wireless Bluetooth protocol, to a notebook where they

are shown on the screen in real time and are also stored into the hard disk. Example of recording during

cardiac autonomic activity blockade is presented. The results show that the developed system is a suitable

tool to study autonomic modulation of the heart rate variability in different scenarios.

1 INTRODUCTION

The autonomic activity is usually assessed by means

of the heart rate variability (HRV) that has been

applied to several clinical studies related to

cardiological and non-cardiological conditions.

Indexes obtained from the HRV in the time and

frequency domains are used to point out changes of

the autonomic nervous system (ANS) activity. By

means of spectral analysis, power measurements of

low-frequency (LF=0.04 to 0.15Hz) and high-

frequency (HF= 0.15 to 0.4Hz) components of the

HRV are employed to quantify the activities of the

sympathetic (SNS) and parasympathetic nervous

systems (PNS), respectively, during cardiovascular

regulation (TASK FORCE, 1996).

Despite their widespread use, there is no

consensus on the suitability of these indexes as

autonomic outflow markers (Parati et al., 2006).

Breathing strongly modulates the HF components of

the HRV and, in a less significant way, the LF

components as well (Brown et al., 1993). These

modulations occur due to the direct neural coupling

among breathing, HR control centers of the brain

and venous return changes induced by the

intrathoracic pressure variation (Saul and Cohen,

1994). Therefore, HF power is simultaneously

affected by the PNS activity and by the breathing.

The arterial blood pressure (ABP), by means of the

baroreflex mechanism, also acts on the HR control

centers of the brain, contributing to HR oscillations

in the LF and HF bands (Cavalcanti, 2000).

From the above, it is possible to state that LF

power, HF power and the LF/HF ratio do not

provide reliable figures on the ANS activity and

sympathovagal balance (Parati et al., 1995). These

arguments suggest that the HRV has limited value to

characterize the autonomic system role on the

cardiovascular regulation (Chen and Mukkamala,

2008). To obtain indexes that may better

characterize the autonomic cardiovascular

regulation, additional physiological data have been

used (Chen and Mukkamala, 2008). Pulse

photopletismography waveform (PPG) and

respiratory flow waveform (RFW) may provide

valuable clinical information to overcome HRV

limitations.

This work describes a portable device that

acquires ECG, PPG and RFW that are transmitted to

a computer by radio-frequency. The device

portability makes it suitable for application in

different clinical scenarios. Examples of clinical

recordings using the developed system are

presented.

363

Giassi Junior P., Fernando Refosco Baggio J., Moraes R. and Gonçalves de Oliveira M..

WIRELESS DEVICE FOR NONINVASIVE RECORDINGS OF CARDIO-RESPIRATORY SIGNALS.

DOI: 10.5220/0003158803630367

In Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES-2011), pages 363-367

ISBN: 978-989-8425-37-9

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

2 SYSTEM DESCRIPTION

The developed system consist of a portable

electronic device and software for Windows® OS.

The device samples ECG, PPG and RFW that are

sent to a notebook. Software presents the acquired

signals on the screen and records them into the hard

disk in real time.

2.1 Hardware

The portable device has transducers and circuits to

acquire, process and transmit the physiological

signals to the notebook. It can be divided in three

parts: acquisition and conditioning unit, control unit

and communication interface unit.

The acquisition and conditioning circuits process

ECG, PPG and RFW signals. In order to prevent

data loss due to movement artifacts or poor skin-

electrode contact, ECG from 2 leads are acquired

and recorded. Connected to the ECG lead wires,

there are passive first order low pass (LP) RC filters

with cut-off frequency (f

) of 8 kHz to attenuate

electromagnetic interference (EMI). The next stage

consists of an instrumentation amplifier (IA) AD620

(Analog Devices) with a gain (G) of 100. The

amplified ECG is applied to a Butterworth band-pass

filter ranging from 0.5 to 100 Hz that was built by

cascading a first order high-pass (HP) and a third

order LP filters. It removes half-cell potential and

attenuates interfering signals such as EMG. The

ECG signal is further amplified (gain from 10 to 15

adjusted by a potentiometer) and added to DC offset

(1.25V). The conditioned ECG ranges from 0 to

2.5V, being within the dynamic range of the analog

to digital converter (ADC). The circuits described

above were implemented with the operational

amplifier TLC2254 (Texas Instruments) that has low

power consumption (35µA typical). Figure 1 shows

the block diagram of the ECG amplifier.

For the PPG acquisition, the circuit shown in

Figure 2 was assembled. An infrared light emitting

diode (LED) with the wavelength of 850 nm

(SFH4252 - OSRAM) and a photodiode (OPT101 –

Burr-Brown) are placed on opposite faces of the

subject’s finger to measure the light attenuation

produced by the blood perfusion and other tissues.

Figure 1: Block diagram of the ECG circuit, containing

low-pass (LP) filters, instrumentation amplifier (IA), high

pass (HP) filter, baseline displacement (Σ), sample-and-

hold (S/H) and analog to digital converter (ADC).

The electric current supplied to the LED is

controlled by a potentiometer in order to adjust the

signal intensity for each individual. A LP filter

=10Hz) avoids noise interference. The PPG

generated by the light attenuation has low (related to

skin absorption, sensor displacement and long-term

changes of the mean arterial blood pressure) and

high frequency components (associated to finger

blood volume changes during the heart beat). To get

the blood volume curve (PPG-AC) with a better

resolution, a HP filter (f

=0.8 Hz) attenuates the DC

component of the PPG. This allows the components

of higher frequency to be amplified by an adjustable

gain (G) in the next stage without saturation. A LP

filter (f

=10Hz) removes noise of higher frequencies

and an offset of 1.25 V is added to the signal to fit

its amplitude to the ADC range.

RFW is obtained with a circuit based on thermal

anemometry (Figure 3). A Wheatstone bridge

contains a heated (70° C) glass sealed bead NTC

thermistor (QTMB-16C3 - Quality Thermistor). The

thermistor is placed ahead of the volunteer nostril.

When there is no air flow, the bridge is balanced and

its output is 0V. The breathing cools the NTC,

changing its resistance and the bridge balance. The

power supplied to maintain the NTC temperature

constant is an indirect measurement of the RFW.

As for the ECG amplifier, passive first order LP

RC filters (f

= 8 kHz) removes the EMI. The bridge

output is amplified by an IA (AD620), with an

adjustable gain G, and applied to the transistor base

that controls the emitter voltage supplied to the

bridge. The emitter voltage, proportional to the

square root of the flow velocity, is also amplified

and filtered by a LP anti-aliasing filter (f

=6 Hz).

1.25V offset is added to the signal to make its range

compatible to the ADC input.

After their amplification and filtering, the five

signals are simultaneously acquired by a sample-

and-hold IC (SMP-04) at a frequency of 1 kHz. A

microcontroller (ADuC841) that has an ADC built-

in converts the signals, one by one, to a 12 bits

word. It carries out the conversion in 8 µs with a

voltage resolution of 0.61mV (1LSB =2.5 V/4096).

Figure 2: The PPG waveform is sampled by two different

channels. One acquires the whole PPG waveform; the

other attenuates the DC component to allow further

amplification that improves the resolution of the higher

frequency components.

BIODEVICES 2011 - International Conference on Biomedical Electronics and Devices

364

Figure 3: Respiratory flow waveform circuit.

The wireless data transmission is carried out by a

Bluetooth module (v1.2 Protocol - KC11 ––

KCWireFree) that receives the sampled data from

the microcontroller serial port. The data transmission

occurs in the bypass mode at rate of 115 kbps,

reaching the Bluetooth receiver module connected to

the notebook USB up to a distance of 100m.

2.2 Software

Software for the notebook was developed in C++

programming language for Windows® OS.

To establish the wireless communication, it is

firstly necessary to run a Windows application that

makes the Bluetooth modules (portable device and

computer) to recognize each other and creates a

virtual serial port COMx to be accessed by the

acquisition software. The software main window

allows the user to select the virtual serial port to

receive the data. The received waveforms are plotted

and stored in real time. Since Borland C++ Builder

graphic libraries are relatively slow for real time

applications, the PlotLab library (Mitov Software)

was used.

The instantaneous heart rate (IHR), calculated

from one of the ECG channels, are also shown on

the screen (beats per minute) during the signal

acquisition to better supervise the subjects’ clinical

state. Six windows simultaneously show the ECG1,

ECG2, IHR, PPG, PPG-AC and RFW (Figure 4).

Each channel is recorded into the hard disk in a

separated file using binary format (16 bits Intel

PCM). Subject’s data (name, age, height and

weight), as well as the date and the time of the

clinical trial, can be typed and stored along with the

signals.

3 EXPERIMENTAL TRIALS

This section describes the use of the developed

system during clinical trials to assess the effect of

SNS and PNS blockade on the HRV. These

experiments are being carried out in the Medical

School Hospital of the Federal University of Santa

Catarina/Brazil after being approved by its Research

Ethics Committee (Project 529/10). Written

informed consent was obtained from the subjects

who took part in the experiments.

Two ECG leads, PPG, PPG-AC and RFW are

recorded for each experimental setting. The

volunteers are divided in two groups. Initially, the

signals are recorded in supine and standing postures

for both groups. An interval of five minutes between

these measurements allows the hemodynamic

recovery of the subject. These data are used as

reference for the other measurements described

below. For the first group, intravenous bolus of

esmolol (3 mg/kg) is administered by an infusion

pump at consecutive intervals of 3 minutes, being

the HR observed. The procedure is repeated until the

HR stops dropping (β-sympathetic blockade).

Following that, the volunteer´s signals are again

recorded for the supine and standing postures. At

last, the subjects receive 0.03 mg/kg of atropine

(Jose and Taylor, 1969) to produce a total autonomic

blockade (double blockade) and their signals are

again recorded for the same two postures.

For the second group, the same protocol is

repeated, but with the drugs applied in reverse order.

Atropine is injected first, blocking vagal stimulus.

Afterwards, esmolol is administered to bring the

total autonomic blockade about. Throughout the

recordings, the respiratory activity is guided by a

metronome, following three breathing patterns. For

each experimental condition (control, β-sympathetic

or vagal blockade and total autonomic blockade), the

subjects are asked to breathe at the fixed rates of 12

and 15 breaths/min (respiratory frequency of 0.2 and

0.25 Hz, respectively) during two minutes (each

rate) and at a random rate, during six minutes. The

random breathing phase followed a Poisson

distribution with periods from 1 to 15 seconds, mean

of 5 s (Berger et al., 1989). The random breathing

protocol allows a better analysis of the autonomic

activity since the respiratory spectra broadens,

preventing the coupling between the respiratory

frequency and the HF or LF HRV components. The

metronome is an independent application software

Figure 4: Software main window during acquisition of

signals from a volunteer.

WIRELESS DEVICE FOR NONINVASIVE RECORDINGS OF CARDIO-RESPIRATORY SIGNALS

365

Table 1: Spectral power measurements of the HRV bandwidths for 2 subjects breathing at random rates.

that shows the respiratory patterns mentioned above

as sinusoidal waves on the screen that the volunteer

has to follow.

During the experiments, the subject’s arterial

pressure was acquired by a sphygmomanometer in

intervals of 3 minutes and annotated in another file.

Such measurements provide data to investigate the

role of the pressure on the HRV. These data will be

also used to investigate the relation of the pulse

wave transit time (PWTT), measured from the ECG

and PPG-AC, as an indirect measurement of the

instantaneous arterial pressure, as proposed in other

works (Lass et al., 2004).

3.1 Data Analysis

A typical recording segment of 30 seconds (Figure

5) shows one of the acquired ECG channels (lead

II), RR-interval, RFW, PPG-AC and PPG. The RR-

interval waveform was obtained by identifying the R

waves of the ECG (red dots) using algorithm based

on Ghaffari et al. (2008). Their fluctuations reveal

the breath modulation of the HR, that is, the

respiratory sinus arrhythmia (RSA). The RSA can be

better assessed by spectral analysis. The spectra of

the HRV and RFW waveforms were calculated for a

subject breathing at two different rates (0.2 Hz and

0.25 Hz) as shown in Figure 6. In this case, the HF

spectral peak shifts from one to the other breathing

rate. Therefore, if the subject reduces his breathing

rate, for instance, from 0.16 to 0.12Hz, the LF power

increases and the HF power decreases without

modification of the ANS activity.

To illustrate the effects of the ANS blockers,

spectral analysis of the HRV was carried out for a

subject. The LF, HF and LF/HF ratio data obtained

is shown on Table 1. The left column shows the

measurements for the first group subject; the right

column presents the measurements for the second

Figure 5: ECG, RR-interval, RFW, PPG-AC and PPG

time series. The red dots correspond to the R wave

detection used to calculate the instantaneous heart rate.

group subject. During vagal blockade, the HF power

decreased markedly, as expected. However, there is

difference between its values obtained during the

random or paced breathing since, for the second

case, the RSA is within the HF bandwidth. During

the double-blockade, the results are similar. On the

other hand, during the β-blockade, the LF power and

LF/HF ratio did not decrease, as one could expect,

not revealing sympathetic activity. These findings

confirm the drawbacks of such indexes.

4 DISCUSSION

The developed device has unique characteristics

since it simultaneously samples different

physiological signals that are usually acquired using

different equipments. Thus, cardio-respiratory

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366

signals can be registered without any cable

connection, reducing sources of artifacts and

providing mobility during the recordings. The

conditioning circuits demonstrated suitable gains for

the desired measurements and good immunity

against spurious interferences during recordings in

the Hospital. Two ECG leads are acquired by the

device to avoid data loss. In case of electrode

displacement or deterioration of the electrode-skin

interface, the RR interval can be still calculated

using the other lead. Concerning the transmission

distance, the Bluetooth connection proved to be

reliable (no data loss) over a range of 20 m even

with obstacles. The elimination of the cables besides

reducing artifacts, provides more comfort to the

subjects during the recordings.

Figure 6: Example of respiratory modulation of the HRV.

The breathing rate was increased from 0.2 Hz (a) to 0.25

Hz (b) as can be seen in the RFW spectrum. As result, the

HF peak of the HRV is also shifted in the RR spectrum.

The PPG signal provides information on the

long-term changes of the mean ABP that can be used

together with the PPG-AC to better estimate the

systolic and diastolic pressure in future researches.

The presented results are similar to the ones

obtained by Chen and Mukkamala (2008) who used

propranolol, a non-selective β blocker. Signals of

other volunteers are being acquired as described

above to set a data bank that will be used to

investigate indexes that may better characterize the

ANS activity.

5 CONCLUSIONS

A wireless non-invasive system for the recording of

cardio-respiratory signals was described. Due to its

portability, the system can be used in different

scenarios, being a valuable tool for research.

The synchronized recordings of ECG, RFW and

PPG allow a better assessment of the interactions

among cardio-respiratory variables and their effect

on the HRV.

Digital signal processing techniques and

mathematical modelling will be applied to the

acquired data to further investigate the

cardiovascular regulation by the ANS.

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