Kwong, J. and Chandrakasan, A.P.

This paper presents an energy-efficient processing platform for wearable sensor nodes, designed to support diverse biological signals and algorithms. The platform features a 0.5 V‑1.0 V 16-bit microcontroller, SRAM, and accelerators for biomedical signal processing. Voltage scaling and block-level power gating allow optimizing energy efficiency under applications of varying complexity. Programmable accelerators support numerous usage scenarios and perform signal processing tasks at 133 to 215× lower energy than the general-purpose CPU. When running complete EEG and EKG applications using both CPU and accelerators, the platform achieves 10.2× and 11.5× energy reduction respectively compared to CPU-only implementations.

Related Links:

An Energy-Efficient Biomedical Signal Processing Platform (IEEE Journal of Solid-State Circuits)

Professor Anantha Chandrakasan

RLE Digital Integrated Circuits and Systems Group