Piezoelectric metamaterial blood pressure sensor

Piezoelectric metamaterial blood pressure sensor. Ahmadpour, A., Yetisen, A. K, & Tasoglu, S. ACS Appl. Electron. Mater., 5(6):3280–3290, June, 2023. Publisher: American Chemical Society (ACS)

Paper doi abstract bibtex

Continuous blood pressure monitoring allows for detecting the early onset of cardiovascular disease and assessing personal health status. Conventional piezoelectric blood pressure monitoring techniques have the ability to sense biosignals due to their good dynamic responses but have significant drawbacks in terms of power consumption, which limits the operation of blood pressure sensors. Although piezoelectric materials can be used to enhance the self-powered blood pressure sensor responses, the structure of the piezoelectric element can be modified to achieve a higher output voltage. Here, a structural study on piezoelectric metamaterials in blood pressure sensors is demonstrated, and output voltages are computed and compared to other architectures. Next, a Bayesian optimization framework is defined to get the optimal design according to the metamaterial design space. Machine learning algorithms were used for applying regression models to a simulated dataset, and a 2D map was visualized for key parameters. Finally, a time-dependent blood pressure was applied to the inner surface of an artery vessel inside a 3D tissue skin model to compare the output voltage for different metamaterials. Results revealed that all types of metamaterials can generate a higher electric potential in comparison to normal square-shaped piezoelectric elements. Bayesian optimization showed that honeycomb metamaterials had the optimal performance in generating output voltage, which was validated according to regression model analysis resulting from machine learning algorithms. The simulation of time-dependent blood pressure in a 3D skin tissue model revealed that the design suggested by the Bayesian optimization process can generate an electric potential more than two times greater than that of a conventional square-shaped piezoelectric element.

@article{ahmadpour_piezoelectric_2023,
	title = {Piezoelectric metamaterial blood pressure sensor},
	volume = {5},
	issn = {2637-6113},
	url = {https://pubs.acs.org/doi/10.1021/acsaelm.3c00344},
	doi = {10.1021/acsaelm.3c00344},
	number = {6},
	abstract = {Continuous blood pressure monitoring allows for detecting the
early onset of cardiovascular disease and assessing personal health status.
Conventional piezoelectric blood pressure monitoring techniques have the
ability to sense biosignals due to their good dynamic responses but have
significant drawbacks in terms of power consumption, which limits the operation
of blood pressure sensors. Although piezoelectric materials can be used to
enhance the self-powered blood pressure sensor responses, the structure of the
piezoelectric element can be modified to achieve a higher output voltage. Here, a
structural study on piezoelectric metamaterials in blood pressure sensors is
demonstrated, and output voltages are computed and compared to other
architectures. Next, a Bayesian optimization framework is defined to get the
optimal design according to the metamaterial design space. Machine learning
algorithms were used for applying regression models to a simulated dataset, and
a 2D map was visualized for key parameters. Finally, a time-dependent blood pressure was applied to the inner surface of an artery
vessel inside a 3D tissue skin model to compare the output voltage for different metamaterials. Results revealed that all types of
metamaterials can generate a higher electric potential in comparison to normal square-shaped piezoelectric elements. Bayesian
optimization showed that honeycomb metamaterials had the optimal performance in generating output voltage, which was validated
according to regression model analysis resulting from machine learning algorithms. The simulation of time-dependent blood
pressure in a 3D skin tissue model revealed that the design suggested by the Bayesian optimization process can generate an electric
potential more than two times greater than that of a conventional square-shaped piezoelectric element.},
	journal = {ACS Appl. Electron. Mater.},
	author = {Ahmadpour, Abdollah and Yetisen, Ali K and Tasoglu, Savas},
	month = jun,
	year = {2023},
	note = {Publisher: American Chemical Society (ACS)},
	keywords = {Savas Scholar},
	pages = {3280--3290},
}

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Although piezoelectric materials can be used to enhance the self-powered blood pressure sensor responses, the structure of the piezoelectric element can be modified to achieve a higher output voltage. Here, a structural study on piezoelectric metamaterials in blood pressure sensors is demonstrated, and output voltages are computed and compared to other architectures. Next, a Bayesian optimization framework is defined to get the optimal design according to the metamaterial design space. Machine learning algorithms were used for applying regression models to a simulated dataset, and a 2D map was visualized for key parameters. Finally, a time-dependent blood pressure was applied to the inner surface of an artery vessel inside a 3D tissue skin model to compare the output voltage for different metamaterials. Results revealed that all types of metamaterials can generate a higher electric potential in comparison to normal square-shaped piezoelectric elements. Bayesian optimization showed that honeycomb metamaterials had the optimal performance in generating output voltage, which was validated according to regression model analysis resulting from machine learning algorithms. The simulation of time-dependent blood pressure in a 3D skin tissue model revealed that the design suggested by the Bayesian optimization process can generate an electric potential more than two times greater than that of a conventional square-shaped piezoelectric element.","journal":"ACS Appl. Electron. 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