Ultrasound imaging technology has undergone a revolution during the last decade due to two primary innovations: advances in ultrasonic transducers that can operate over a broad range of frequencies and progress in high-speed, high-resolution analog-to-digital converters and signal processors. Existing clinical and FDA approved bench-top, and portable ultrasound systems can generate real-time high-resolution images at frame rates as high as 10000 frames per second. This dissertation’s fundamental hypothesis is to leverage the massive data acquisition and computational bandwidth afforded on these portable devices to establish energy-efficient bio-telemetry links with multiple in-vivo implanted devices.
In this regard, I investigated using a commercial off-the-shelf (COTS) diagnostic ultrasound reader to establish a reliable in-vivo wireless telemetry with millimeter-sized piezoelectric crystal transducers. I proposed multi-access biotelemetry methods in which several of these crystals simultaneously transmit the data using conventional modulation and coding schemes. I validated the feasibility of in-vivo operation using two piezoelectric crystals tethered to the tricuspid valve and the skin’s surface in a live ovine model. I demonstrated data rates close to 800 Kbps while consuming microwatts of power even in the presence of respiratory and cardiac motion artifacts.
In this research, I also investigated the feasibility of energy harvesting from cardiac valvular perturbations to self-power the wireless implantable device. I explored the use of piezoelectric sutures implanted in proximity to the valvular regions to exploit nonlinearity in the valvular dynamics and self-power the implanted device. My study showed that power harvested from different annular planes of the tricuspid valve could range from nano-watts to milli-watts.
Finally, I investigated the use of beamforming in B-scan ultrasound imaging to reduce the biotelemetry energy-budget further. In this context, I explored variance-based informatics in which the information is captured by the change in signal variance rather than signal mean for logic encoding and decoding. Using monte-carlo simulations, I showed that compared to the conventional signal representation schemes, the proposed variance-based representation could theoretically achieve a superior performance trade-off (in terms of energy dissipation) when operating at fundamental limits imposed by thermal-noise. I also showed that the minimum power-dissipation requirements could be reduced to 100 pW while interrogating at depths greater than 10 cm in a water medium.
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