Instrumentation & Measurement Magazine 25-1 - 10

Fig. 5. Displacement of the near wall of the carotid artery over the cardiac
cycles estimated from ultrasound signals obtained by the proposed WUS
system.
parameters of the decomposed wall echo was implemented to
track the motion across each frame. Fig. 5 shows the estimated
displacement waveform of the near wall of the CCA over the
cardiac cycles using this technique and the WUS system. While
the method successfully isolated and tracked the artery wall
echoes, the basis used for decomposition did not result in a discriminable
set of features for automatic identification. Further
research is being conducted to develop a model that can learn
a discriminable basis for automatic artery wall echo isolation.
Challenges and Future Research
In this paper, we proposed a WUS system using a single-element
PVDF piezoelectric polymer film UT with plane-wave
ultrasound for artery monitoring. One of the challenges of automatic
and continuous artery monitoring using the proposed
WUS system is the automatic identification of the echoes corresponding
to the artery walls in the presence of increased
scattering noises in acquired ultrasonic signals. Scattering
noise level is greater in the WUS than in the conventional ultrasound
imaging systems with focused ultrasound. To meet
this technical challenge, either novel digital signal processing
techniques or a combination of existing techniques may be required.
Machine learning approaches could be implemented
using computer vision algorithms for image segmentation
and motion tracking. For supervised learning, a reference
measurement for labelling of the training data is needed. Obtaining
generalization performance of the proposed WUS
system across subjects for artery monitoring, such as the artery
wall motion estimation accuracy, reproducibility, and
reliability, requires a high volume of in-vivo data from multiple
subjects with comparison of intra-arterial measurements.
Once a fully automated algorithm for tracking the artery diameter
changes over the cardiac cycle is developed, estimation of
cardiovascular health indicators and analytics that aid in medical
decision making could be implemented.
An integrated miniaturized low-power ultrasonic pulserreceiver
and digital acquisition system will need to be designed
for the proposed WUS system. Additional experimentation is
10
needed to evaluate the signal quality and penetration depth
using the WUS with low-power excitation. Compressed
sensing approaches could also be implemented to reduce
the sampling rate requirements and therefore the power requirements
of the digital acquisition system. Furthermore,
ultrasonic couplant materials suitable for long-term monitoring
need to be investigated.
WUS systems are well-suited for continuous measurement
of physiological mechanical properties and may complement
wearable electrode technologies that retrieve electrical
signals from the body, such as electrocardiogram and electromyogram.
In the future, a multi-modal sensor system
may be considered to improve the measured signal quality
and reduce the uncertainties in the estimated physiological
parameters. The research presented in this paper is still in a
preliminary stage of the proof of concept. Comparative studies
and metrological analyses on more WUSs and subjects will
be conducted.
Acknowledgment
This work was supported by the Natural Sciences and Engineering
Research Council of Canada, and the Carleton
University COVID-19 Rapid Response Grant. The authors
thank Dr. M. Yoshida for his guidance during the in-vivo experiments
and Mr. S. Venugopal for the data collection presented
in this work.
References
[1] " World report on ageing and health, " World Heal. Organ., 2015.
[2] I. Almohimeed, H. Turkistani, and Y. Ono, " Development of
wearable and flexible ultrasonic sensor for skeletal muscle
monitoring, " in Proc. IEEE Int. Ultrason. Symp., pp. 1137-1140,
2013.
[3] S. Golemati et al., " Carotid artery motion estimation from
sequences of B-mode ultrasound images: effect of scanner settings
and image normalization, " IEEE Trans. Instrum. Meas., vol. 58, no.
7, pp. 2102-2112, 2009.
[4] I. Almohimeed and Y. Ono, " Ultrasound measurement of skeletal
muscle contractile parameters using flexible and wearable singleelement
ultrasonic sensor, " Sensors (Switzerland), vol. 20, no. 13,
pp. 1-21, 2020.
[5] R. Giannetti, A. Petrella, J. Bach, and A. Silverman, " Feasibility
study of in vivo bone depth measurement using high frequency
ultrasound, " in Proc. IEEE Instrum. Meas. Technol. Conf., pp.
762-766, 2015.
[6] A. J. Fernandes, Y. Ono, and E. Ukwatta, " Evaluation of finger
flexion classification at reduced lateral spatial resolutions of
ultrasound, " IEEE Access, vol. 9, pp. 24105-24118, 2021.
[7] X. Yang, X. Sun, D. Zhou, Y. Li, and H. Liu, " Towards wearable
A-mode ultrasound sensing for real-time finger motion
recognition, " IEEE Trans. Neural Syst. Rehabil. Eng., vol. 26, no. 6,
pp. 1199-1208, 2018.
[8] A. Lanatà, E. Pasquale Scilingo, and D. De Rossi, " A multimodal
transducer for cardiopulmonary activity monitoring in
emergency, " IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 3, pp.
817-825, 2010.
IEEE Instrumentation & Measurement Magazine
February 2022
Instrumentation & Measurement Magazine 25-1

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