Data fusion of single-Tag RFID measurements for respiratory rate monitoring

W. Mongan, R. Ross, I. Rasheed, Y. Liu, K. Ved, E. Anday, K. Dandekar, G. Dion, T. Kurzweg, A. Fontecchio

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

Abstract

Using wireless, passive, wearable, knitted, smart garment devices, we monitor biofeedback that can be observed via strain gauge sensors. This biofeedback includes respiratory activity, uterine monitoring during labor and delivery, and regular movements to prevent Deep Vein Thrombosis (DVT). Due to noise artifacts present in a wireless strain gauge monitor and the possibly non-stationary nature of the signal itself, signal analysis beyond the Fourier transform is needed to extract the properties of the observed motion artifacts. We improve the utility of a single Radio Frequency Identification (RFID) tag by fusing multiple features of the tag, in order to precisely determine the frequency and magnitude of motion artifacts. In this paper, we motivate the need for a multi-feature approach to RFID-based strain gauge analysis, correct raw RFID interrogator measurements into features, fuse those features using a Gaussian Mixture Model and expectation maximization, and improve respiratory rate detection from 9 to 6 mean squared error over prior work.

Original languageEnglish (US)
Title of host publication2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538648735
DOIs
StatePublished - Jul 1 2017
Event2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Philadelphia, United States
Duration: Dec 2 2017 → …

Publication series

Name2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings
Volume2018-January

Other

Other2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017
CountryUnited States
CityPhiladelphia
Period12/2/17 → …

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All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Clinical Neurology
  • Signal Processing
  • Cardiology and Cardiovascular Medicine

Cite this

Mongan, W., Ross, R., Rasheed, I., Liu, Y., Ved, K., Anday, E., Dandekar, K., Dion, G., Kurzweg, T., & Fontecchio, A. (2017). Data fusion of single-Tag RFID measurements for respiratory rate monitoring. In 2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings (pp. 1-6). (2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPMB.2017.8257028