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Sabino received his B.Sc. in electrical engineering from the University of Michigan – Ann Arbor in 2008. From 2008 – 2010, he was assistant technical staff at MIT Lincoln Laboratory, where he was a recipient of the Lincoln Scholars Fellowship and co-recipient of R&D Magazine’s R&D 100 Award. He received his S.M. in 2012 from MIT, where he is currently a Ph.D. candidate in electrical engineering. His principal research interests include the design of medical electronics, blood flow characterization methods, mathematical modeling of biological systems, and RF integrated circuit design.
Transcranial Doppler (TCD) sonography is a specialized ultrasound technique that enables measurement of blood flow velocity from the basal intracerebral vessels. Use of TCD sonography is highly compelling as a diagnostic modality due to its safety in prolonged studies, high temporal resolution, and relative portability. Although TCD methods have been clinically indicated in a variety of cerebrovascular diagnostic applications, general acceptance by the medical community has been impeded by several critical deficiencies – including the need for a highly-trained TCD operator, operator dependent measurement results, and severe patient movement restrictions.
This work seeks to mitigate such limitations through the development of a wearable TCD ultrasound system, permitting untethered cerebrovascular monitoring with limited operator interaction. The prototype system incorporates a custom two-dimensional transducer array and multi-channel transceiver electronics, thereby facilitating acoustic focusing via phased array operation. Algorithmic vessel location and tracking further reduce operator dependencies by expediting vessel localization, systematizing vessel identification, and dynamically adapting to relative vessel position.
Validation of the prototype hardware and embedded signal processing implementations under flow phantom and human subject testing yields high correlation with accepted velocimetry methods. Vessel search and tracking functionality are also verified experimentally. Circuit integration is explored to further reduce instrumentation dimensions and power consumption.