# Development of a Novel Contactless Mechanocardiograph Device

Authors: Kouhyar Tavakolian; Faranak M. Zadeh; Yindar Chuo; Ali  Vaseghi; Bozena Kaminska
Journal: International Journal of Telemedicine and Applications
 (2008)

---

## Abstract

A novel method of detecting mechanical movement of the heart, Mechanocardiography (MCG), with no connection to the subject's body is presented. This measurement is based on radar technology and it has been proven through this research work that the acquired signal is highly correlated to the phonocardiograph signal and acceleration-based ballistocardiograph signal (BCG) recorded directly from the sternum. The heart rate and respiration rate have been extracted from the acquired signal as two possible physiological monitoring applications of the radar-based MCG device.


---

## Body

## 1. Introduction

The
ballistocardiograph (BCG) is a vital signal in the 1–20 Hz frequency range which
is caused by the movements of the heart and blood.
The BCG can be recorded from the surface of human body by noninvasive
means. In the early 1930s, Isaac Starr recognized that the BCG signals closely
reflect the strength of myocardial contraction and classified them into four
groups to distinguish normal and abnormal heart performances [1, 2]. As a
result of his valuable research, clinicians and medical experts for almost four
decades studied the effects of different heart malfunctions by means of the BCG
and proved that these malfunctions can be related to typical patterns in BCG
signals [3, 4]. The ideal BCG waveform consists of seven waveform peaks labeled
H through N as defined by the American Heart Association, and this annotation
can be seen in Figure 1.Figure 1
BCG and ECG signals of a single heart-cycle as recorded by the microsensor with the annotation referenced to ECG.In addition to a number of clinical studies
that have been performed with the BCG, specialized BCG instruments, including
beds and chairs, have been developed by different research groups [5–7]. Due to the unrefined nature of the previous BCG signal acquisition
technologies, the lack of interpretation algorithms and the lack of practical
devices, the current health care systems do not use BCG for clinical purposes.
New microsensor and digital wireless technologies provide more accurate BCG
signal acquisition and processing, therefore, opening new possibilities to use
BCG, and in general mechanical signals of the heart, clinically as a new additional
tool in diagnosis and identification of heart malfunctions.Based on these observations, we are
improving the BCG signal acquisition system that reflects the mechanical
functioning of the heart. In our first study [8], we used a high-precision
accelerometer, which is factory calibrated, weighs 54 g, and is attached to the
sternum, the same as used in reference [9]. In our second study, we improved
the previous sensor by developing a small mechanically flexible microsensor
that could be easily attached to the sternum. It has been proven that all the aspects of a classical BCG signal, (H, I, J, K) waves similar to
that measured through a high-precision accelerometer [9], can be identified in
the novel microsensor recordings [10].The current research, reported
in this paper, is aiming to go one step further by applying contactless
measurement of the mechanical movement of the heart, using a radar-based MCG
device operating in the range of 2.45 GHz [11]. The extracted signal is
considered a mechanocardiograph (MCG) reflecting the mechanical functioning of
the heart and is highly correlated to the BCG signal acquired in previous
studies [12].This paper is organized as follows: in the second section of the
paper our signal acquisition methodology is explained and then the comparison
of the acquired MCG signal to our previous BCG recordings is presented. In
section three, the electronic circuit board design developed for the
radar-based MCG device is explained. In section four the results of breathing rate
and heart rate measurements using the new technology are presented. The
comparison results of the phonocardiograph and the acquired signal are also
presented clearly showing the correspondence of our MCG signal to cardiac
events.


## 2. MCG Signal Acquisition

The block diagram in Figure2 shows the general methodology
followed in our research for processing of the radar-based MCG signal. The MCG
signal was acquired by a microprocessor controlled, radar-based MCG device
placed at distance of 10 cm away from the subject’s chest. The data acquisition,
for the results presented in this paper, involved the measurement of ECG and
respiration signals too. These signals were acquired by a Biopac biological
data acquisition system [13]. The design principle of radar-based MCG device is
presented in section three of the paper.Figure 2
Radar-based MCG signal processing methodology.While monitoring the heart from the outside of the body contactlessly from the sternal location,
the signal passes through only a few layers of different tissues between the sternum
and the heart which can be seen in Figure3. The tissue layers between the
sensor and heart muscle include: skin, sternum, lung
and pleural tissue, pericardium and pericardial space. From
the sternum position, these tissue layers are thinner compared to the other
positions. Therefore, the best
position to record the heart's MCG signal is from the sternum (normally on the
first third of the sternum length, as this is the closest path to get to the
heart muscle).Figure 3
Positioning of different layers of tissues that the radar signal will go through. The layers between sternum and right ventricle include pericardium, pericardial cavity, and thin layers of pleural tissues.RF signal with the carrier frequency of
2.45 GHz was transmitted toward the subject’s chest, and the reflected signal
was band-passed filtered between 0.5 Hz to 25 Hz. The filtered signal was
differentiated and then band-pass filtered again between 4 Hz to 20 Hz. The
comparison of the processed MCG signal to the BCG signal recorded
simultaneously from the sternum can be seen in Figure4 together with the
synchronized ECG signal.Figure 4
Two cycles of the filtered radar-based MCG signal (bottom), the filtered signal recorded directly from the sternum using a high-precision accelerometer (middle), and the lead I of ECG signal (top).It can be observed that there is a close
correlation between the signal acquired from the radar-based MCG device and the
signal acquired from the accelerometer-based BCG device attached to the
sternum. The systolic and diastolic phases of cardiac cycle are shown to
identify the correlations of these mechanical signals to the heart functioning.Phonocardiograph signal reflects the heart
sounds that can be hared using stethoscope. Heart sound S1 corresponds to
systolic phase of the heart cycle, and S2 corresponds to the diastolic phase of
it. For the comparison purpose, the MCG signal was acquired synchronously with
phonocardiograph signal and it was observed that S1 and S2 sounds of the
phonocardiograph signal corresponded to the similar complexes on the MCG
signal. The clear correlation of this new signal to the heart cycle’s events
can be observed in Figure6.Figure 5
Block diagram of the principle design of the contactless MCG device.Figure 6
Two cycles of synchronous radar MCG, phonocardiograph, and ECG signal showing the correlation of cardiac cycle events to radar MCG signal. Systolic and diastolic complexes can be identified in the radar MCG signal corresponding to S1 and S2 of heart’s sounds.


## 3. Contactless MCG Device

As stated before, in our
experiments heart’s MCG signal was measured by a MCG device operating in the
range of 2.45 GHz. At this electromagnetic frequency, the surface of the body is
highly reflective to incident electromagnetic field. Biological tissue is very
lossy at this frequency, and there is minimal penetration of radiated
electromagnetic energy into the body. Therefore, a return signal from a
radiated electromagnetic field incident on the body will primarily contain
information associated with movement events.The effects of radio-frequency fields on
human health have been monitored and studied by the scientists around the world
for about 60 years now. The 2.45 GHz frequency is considered to be safe for
human health. This is the same frequency range as emitted from a cell phone
[14]. The specific absorption rate, SAR, is
0.42 w/kg which is below the limits as recommended by international commission
on nonionizing radiation protection [15].The
principal design of the radar-based MCG device is shown in Figure5. The
antenna mounted in the device is HFMD24 by Siemens and contains a transmitter
and a receiver in the same housing. The operating frequency is 2.45 GHz. The
transmitter transmits continuous wave radio frequency energy towards subject's
body. The returned signal is frequency shifted due to the Doppler effect, which
is the apparent change in frequency and wavelength of a wave that is perceived
by an observer moving relative to the source of the waves. This effect permits
the measurement of slight body movements from which physical heart movement
signal can be obtained by the MCG receiver.The
output signal from the receiver is filtered and amplified and is sent to the
microprocessor for further processing. The
cutoff frequencies for the band-pass filter shown in the schematic are 1 Hz and
100 Hz, and the gain of the amplifier is around 800. After filtering and
amplifying, the MCG signal is sent to the A/D unit and then to the ATMEL CPU
for further processing. The CPU is connected to a thin-film transistor (TFT)
display via its serial peripheral interface (SPI) port. The MCG device operates
with two AA batteries (2.45 V).Considering
that the MCG device has its own CPU and monitor, it can be used stand alone to
acquire and process the MCG signal. There is also another option of sending the
data to a personal computer for more advanced processing of the data using
Matlab. To have this option on our device, the digitized MCG signal is
transformed to packets and sent through UART to the USB and finally to the host
personal computer for possible further processing.


## 4. Results and Discussion

The data from subjects
were acquired at Burnaby General Hospital (British Columbia,
Canada)
and in all the measurements presented in this paper the distance from the sensor
to the chest was set to 10 cm. The processed MCG signal has been superimposed on
the phonocardiograph signal, and it has been noticed that S1 and S2 sounds of
the phonocardiograph signal corresponded to the similar complexes on the radar
MCG signal. The correlation of the MCG signal to the heart cycle’s events is
observed, and the results of this superimposition can be seen in
Figure6.For the heart rate measurement our experimental setup included
the acquisition of the MCG signal and two leads of ECG as a reference. For
respiration rate measurement, the setup included the acquisition of MCG signal
together with the respiration signal as the reference. Eight subjects took part
in the respiration measurement tests, and six of these subjects took part in
the heart rate measurement tests too. Breathing rate measurement experiments
were 60 seconds long while heart rate measurement experiments were 15 seconds
long.For
detection of breathing rate, the radar signal was low pass filtered under 0.4 Hz,
and the peaks were counted and compared to the results acquired from a strain
gauge transducer that measures the changes in thoracic circumference, using a
belt which is fastened to the subject’s thorax. As can be seen in Table1, the
accuracy of respiration rate measurement was 91.35 percent over all eight
subjects. The heart rate was measured using radar-based MCG device and was
compared to the heart rate calculated from the simultaneous ECG signal for six
subjects. The average of the heart rate accuracy on these subjects was
calculated to be 92.9 percent.Table 1
The heart rate and respiration rate measurements using the MCG device
for eight subjects. The numbers represent the percentage of correctly detected
heart beats or breathing cycles to the total number of heart beats or breathing
cycles.
Subjects
Heart rate
Respiration rate
1
93
90
2
—
94.2
3
84
90
4
91
90
5
100
87.1
6
89.4
92
7
100
100
8
—
87.5
Averages
92.9
91.35As an example,
for subject six we had 14 cycles of respiration from which 13 of them where
correctly identified. Thus, for this subject, the 92 percent accuracy for
respiration rate detection was achieved. For the same subject and out of 19
heart beats, 17 of them were correctly identified. Thus, for heart beat
detection for this subject, the accuracy of 89.4 percents was achieved. Using
our device, the data can be seen real time and can be processed in near real
time. The reason for quick processing time is that the algorithm includes
filtering of the data and then peak searching to find the corresponding peaks
to the inspiration and heart beat events.The sources of
interference for contactless heart motion signal acquisition can be categorized
into two main categories. First, foreign electromagnetic radiation that may
disrupt the desired signal on its way back to the antenna, and second, motion
interference of nearby subjects. As discussed previously, the radiation
frequency of the contactless MCG device is centered about 2.4 GHz. This
frequency falls within the Industrial Scientific and Medical (ISM) bands. The ISM bands are recognized internationally,
where it has been traditionally reserved for industrial, scientific, and
medical purposes excluding communications [16].The 2.4 GHz ISM band in many urban
settings is in fact quite saturated with devices. Examples include the very
common wireless local area network (WLAN) devices, Bluetooth devices,
microwaves ovens, and household cordless phones. These devices can exhibit
relatively high signal broadcast power levels during full power transmission. In
the North American/US market, the safe power level is governed by the FCC [16].
As a result, it is possible that other 2.4 GHz, ISM devices operating in the
vicinity of measurement could pose undesirable electromagnetic signal
interference, particularly when these devices are in-motion. However, most
cellular phone devices operate in the Global System for Mobile Communications
(GSM) Bands, and thus will not pose electromagnetic interference concerns, in
the sense of disturbing the Doppler reading, for the contactless MCG device
proposed.Motion
interference is another possible source of signal disruption when operating the
device in a high-density, busy setting. The antenna patch on the contactless
MCG device is a printed patch antenna and at ranges greater than what is
specified operational for this application (i.e., more than 10 cm), its
side-lobes begin to pickup motion in its path. Also the main-lobe of the
antenna begins to exhibit relatively wide angle. In attempts to acquire useful
heart motion signals at longer ranges, more than 10 cm, the motion interference
from the subject’s general body movement or nearby movements that are not
subject-related will both disrupt the heart motion signal acquisition greatly.In
efforts to evaluate the reliability of this device considering the two major
sources of interference, in addition to the measurements at Burnaby General
Hospital,
as explained previously, measurements on 200-plus participants during the Wired
NextFest convention were obtained [17]. The environment of the convention hall
naturally provided many possible sources of both electromagnetic interference
and motion interference. In fact, the convention hosted more than 150 stations,
many equipped with audio-video setup, wireless network stations, and up to
thousands of visitors at any given moment, likely each carrying some sort of personal
mobile device.The
heart motion measurements were compared simultaneously with the corresponding
heart beat of each individual participant as assessed via wrist pulse by
research staff members. It was observed that when the subject held still, and
without other people within 50 cm of the device radius, approximately only one out
of ten subjects during 30 second recording session would exhibit grossly
delayed or out-of-sync heart rates between the wrist pulse and device reading.Although
it is unknown how many wireless broadcasting devices, using the 2.4 GHz band,
were present during the convention, nor the associated power levels, and hence
the random interference power density in the foot-ball sized convention hall,
the quasi field-test of the device provided assurance that even in the busiest
everyday environments, filled with urban electronics and random motion, when
the subject recordings are controlled properly, the reliability of the heart
rate detection is seemingly good.Further
testing on the effects of both electromagnetic and motion interference is necessary to fully assess the performance
of the proposed contactless MCG device. Though, it suffices to say that the
observations through the combined evaluations and field-trials give high-hopes
on the performance and for the eventual perfection of this device.


## 5. Conclusion

In this research work, the MCG
signal was extracted from the radar-based MCG device and by using two other
heart related signals, BCG and phonocardiograph, it has been proven that the
extracted MCG signal corresponds to the mechanical functioning of the heart.Two
physiological signals, heart rate and respiration rate, were measured using the
MCG signal and a noticeable accuracy of 91.35% for respiration rate, and 92.9%
for heart rate were achieved. It should be noticed that these results are
acquired from the first generation of our device, and the accuracy of the
detection can be improved by focused targeting of the MCG device on the sternum
and further hardware improvements. Another important factor, which is an asset of
our device, is the fact that all the electronics and the radar sensor can be
fabricated for less than $200 USD which makes our device economical for general
heart monitoring purposes.Considering
the short amount of processing and the low cost of the contactless measurement
of heart rate and breathing rate as we presented, our device can have numerous
applications in the health care system such as, prevention of sudden infant
death syndrome (SIDS), sleep apnea, and other areas in which contactless
monitoring is desired.In this research
work, we have proposed a new methodology and a new device based on radar
technology. We proved the correspondence of our acquired MCG signal to sternal
BCG and phonocardiograph signals. Further improvement of the current device can
provide us with more accurate MCG signal corresponding to mechanical
performance of the heart and ultimately development of an additional
contactless heart diagnostic tool.



---

*Source: 436870-2008-05-15.xml*