A look at signal analysis in resource-constrained medical-sensor applications

Naveen Verma, Zhuo Wang, Jintao Zhang

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

1 Scopus citations

Abstract

Given the increasing emphasis on data-driven medicine, this overview paper explores how healthcare functions can be extended to on-patient sensor platforms. While the functions that will be of interest in this context are not precisely known, the approaches within data-driven medicine are becoming clear. This guides us to the algorithms that will be used for diagnosis, monitoring, and therapy. In particular, there is an emphasis on machine-learning algorithms, which enable the creation of robust models for signal analysis from data. Focusing on such algorithms, this paper looks first at digital platforms for signal analysis that provide adequate programmability while addressing computational energy. Then, it considers approaches to signal acquisition that focus on acquiring the specific information needed within algorithms for signal analysis, with the aim that such focus relaxes both the specifications for mixed-signal interfaces and the subsequent computations required. The ideas presented reference hardware prototype demonstrations.

Original languageEnglish (US)
Title of host publicationIEEE Biomedical Circuits and Systems Conference
Subtitle of host publicationEngineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479972333
DOIs
StatePublished - Dec 4 2015
Event11th IEEE Biomedical Circuits and Systems Conference, BioCAS 2015 - Atlanta, United States
Duration: Oct 22 2015Oct 24 2015

Publication series

NameIEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings

Other

Other11th IEEE Biomedical Circuits and Systems Conference, BioCAS 2015
CountryUnited States
CityAtlanta
Period10/22/1510/24/15

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Instrumentation
  • Biomedical Engineering
  • Electrical and Electronic Engineering

Keywords

  • biomedical electronics
  • machine learning
  • medical signal processing

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    Verma, N., Wang, Z., & Zhang, J. (2015). A look at signal analysis in resource-constrained medical-sensor applications. In IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings [7348312] (IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BioCAS.2015.7348312