A 1.2-0.55V general-purpose biomedical processor with configurable machine-learning accelerators for high-order, patient-adaptive monitoring

Kyong Ho Lee, Naveen Verma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

Machine learning offers powerful advantages in sensing systems, enabling the creation and adaptation of highorder signal models by exploiting the sensed data. We present a general-purpose processor that employs configurable machine-learning accelerators to analyze physiological signals at low energy levels for a broad range of biomedical applications. Implemented in 130nm LP CMOS, the processor operates from 1.2V-0.55V (logic). It achieves real-time EEG-based seizure detection at 273μW (at 0.85V) and patient-adaptive ECG-based cardiac-arrhythmia detection at 124μW (at 0.75V), yielding overall energy savings of 62.4× and 144.7× thanks to the accelerators.

Original languageEnglish (US)
Title of host publication2012 Proceedings of the European Solid State Circuits Conference, ESSCIRC 2012
Pages285-288
Number of pages4
DOIs
StatePublished - Dec 14 2012
Event38th European Solid State Circuits Conference, ESSCIRC 2012 - Bordeaux, France
Duration: Sep 17 2012Sep 21 2012

Publication series

NameEuropean Solid-State Circuits Conference
ISSN (Print)1930-8833

Other

Other38th European Solid State Circuits Conference, ESSCIRC 2012
CountryFrance
CityBordeaux
Period9/17/129/21/12

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A 1.2-0.55V general-purpose biomedical processor with configurable machine-learning accelerators for high-order, patient-adaptive monitoring'. Together they form a unique fingerprint.

  • Cite this

    Lee, K. H., & Verma, N. (2012). A 1.2-0.55V general-purpose biomedical processor with configurable machine-learning accelerators for high-order, patient-adaptive monitoring. In 2012 Proceedings of the European Solid State Circuits Conference, ESSCIRC 2012 (pp. 285-288). [6341275] (European Solid-State Circuits Conference). https://doi.org/10.1109/ESSCIRC.2012.6341275