SBIR Phase I: Ultra Power-Efficient Analog and Bio-inspired Integrated Circuits for Wearable Computing

Mavric Semiconductor Inc, Santa Cruz CA

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to solve critical power budget issues in next generation wearable computing applications. Candidate applications require ultra-low power, require massive context-awareness computation, and need to perform in the noisy real world. A large gap exists between consumer expectation and what can be realized using conventional circuit techniques. Reconfigurable and biologically inspired classifiers use proprietary mixed signal approaches that uniquely close wearable computing's power/performance gap. Our Phase I deliverables focus on completing a minimum viable product (MVP) that will use gesture recognition to wake up/control behavior of a wearable device with a power budget in the low micro-watt range. The demonstration would use programmable neural classifier engines acting on sensor stimulus to perform gesture recognition. This important step will allow the further development of the technology portfolio for a broader range of applications. The proposed project's central innovation lies in the mixed-signal approach to embedded computing to shatter the energy efficiency barrier of traditional digital systems. The Field Programmable Analog Array (FPAA) approach incorporates neuromorphic circuits which approach 5GMAC/uW processing efficiency for high-level classification tasks. The Long-term vision is to address a broad range of end applications through a family of mixed signal integrated circuits based on a novel and programmable architecture that operates at 2 orders of magnitude less power than a comparable digital implementation; to deliver solutions that are the world's most energy efficient implementation. When classification tasks which formerly required at least 10mW to perform can be accomplished within 100uW, a vast range of applications become possible. The impact will be most profoundly felt in the design of next generation portable devices- in particular complex event tracking functions in wireless sensor motes (enabling the Internet-of-Things (IoT)), next generation devices for wearable computing.