Continually rising cost of healthcare and side-effects of drugs, such as opioid addiction, could be reduced through remote health monitoring systems and closed-loop electroceuticals, which rely on large amount of data continuously traveling around human body from low-energy wearable and implantable sensors to an on-body hub then to the cloud. Today's standard technologies rely on electromagnetic wave for communication around the human body, which is not physically secure and consume orders of magnitude more power than needed by a typical sensor node, making the communication link the energy bottleneck for ultra-low-power body sensor nodes. This research project will lead to a fundamentally new way of thinking about using human body as a "wire" to achieve orders of magnitude lower energy used for communication around the human body while being physically secure (i.e., signals cannot be snooped without physical contact). In addition, this project will use edge-analytics to reduce data volume for efficient Human-Intranet smart sensor nodes. The project will develop the fundamental understanding for designing the smallest (less than one cubic millimeter) body-connected node for connected healthcare. With simulation tools and hardware verification, backed by concrete mathematical model development, this work will open new research directions in Human-Intranet for Healthcare, Human-Computer Interaction and Brain-Machine Interfaces. The outcome of this research will be integrated with undergraduate and graduate courses on Digital Design and Mixed-Signal Design. Mathematical models representing circuit/system level information and energy trade-off will be disseminated through research website. Such experimentally verified models are expected to provide significant impact by serving a broad community of students, researchers, and engineers. Educational prototypes of the research will be used to engage students in educational workshops. The strong engagement through undergraduate research mentorship and minority student mentorship will strengthen the interest of science and technology from underrepresented students.
The objective of this research is to transform data communication around the human body by using the human body as a wire to achieve orders of magnitude reduction in communication energy in the body area network and combining it with in-sensor analytics to reduce data volume without significant reduction in information to further improve energy/information efficiency. The project will develop the foundations of energy-efficient and physically secured network of energy-sparse sensor nodes for Human-Intranet. The research exploits the low-loss human body channel itself to power the sensor, perform edge-analytics to compress the data and extract information before transferring the compressed data using the same low-loss human body channel. The body-wire research is expected to solve the problem of high data traffic by achieving >1000x reduction in energy/information, allowing longer-lasting, smarter, smaller (new form-factors, better patient compliance), and lower cost healthcare. The energy reduction and improved physical security (in addition to encryption) will open possibilities of many new sensor nodes with new form factors (e.g., connected patch) for human-centered healthcare networks. Along with developing bio-physical circuit models for human body as a communication medium, optimized transceiver circuits and systems for lossy broadband electro-quasistatic human body channel will be developed and demonstrated through integrated circuit fabrication and measurement. A system-on-chip with sensing, in-sensor analytics, and human-body-communication transceiver will be designed, fabricated, and measured to demonstrate the end-to-end improvement in energy/information efficiency. The project will develop mathematical models verified by experiments for future design space exploration and information/energy analysis for Human-Intranet. If successful, the project will develop the fundamental understanding of designing the smallest body-connected node for connected healthcare.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
