This manuscript investigates energy harvesting from arterial blood pressure via the piezoelectric effect for the purpose of powering embedded micro-sensors in the human brain. One of the major hurdles in recording and measuring electrical data in the human nervous system is the lack of implantable and long term interfaces that record neural activity for extended periods of time. Recently, some authors have proposed micro sensors implanted deep in the brain that measure local electrical and physiological data which is then communicated to an external interrogator. This paper proposes a way of powering such interfaces. The geometry of the proposed harvester consists of a piezoelectric, circular, curved bimorph that fits into the blood vessel (specifically, the Carotid artery) and undergoes bending motion because of blood pressure variation. In addition, the harvester thickness is constrained such that it does not modify arterial wall dynamics. This transforms the problem into a known strain problem and the integral form of Gauss’s law is used to obtain an equation relating arterial wall motion to the induced voltage. The theoretical model is validated by means of a Multiphysics 3D-FEA simulation comparing the harvested power at different load resistances. The peak harvested power achieved for the Carotid artery (proximal to Brain), with PZT-5H, was 11.7 μ W. The peak power for the Aorta was 203.4 μ W. Further, the variation of harvested power with variation in harvester width and thickness, arterial contractility and the pulse rate is investigated. Moreover, potential application of the harvester as a chronic, implantable and real-time Blood pressure sensor is considered. Energy harvested via this mechanism will also have applications in long-term, implantable Brain Micro-stimulation.
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Energy Harvesting From Arterial Blood Pressure for Powering Embedded Microsensors in Human Brain
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Nanda, A, & Karami, MA. "Energy Harvesting From Arterial Blood Pressure for Powering Embedded Microsensors in Human Brain." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies. Snowbird, Utah, USA. September 18–20, 2017. V001T07A012. ASME. https://doi.org/10.1115/SMASIS2017-3894
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