Rate-adaptive pacemaker controlled by motion and respiratory rate using neuro-fuzzy algorithm

J. W. Shin, Junghan Yoon, Y. R. Yoon

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Rate-adaptive pacemakers use information from sensors to change the rate of heart stimulation. Until now, fuzzy-pacemaker algorithms have been used to combine inputs from sensors to improve heart rate control, but they have been difficult to implement. In this paper, a pacemaker algorithm which controlled heart rate adaptively by motion and respiratory rate was studied. After chronotropic assessment exercise protocol (CAEP) tests were performed to collect activity and respiratory rate signals, the intrinsic heart rate was inferred from these two signals by a neuro-fuzzy method. For 10 subjects the heart rate inference, using the neuro-fuzzy algorithm, gave 52.4% improved accuracy in comparison with the normal fuzzy table look-up method. The neuro-fuzzy method was applied to a real pacemaker by reduced mapping of the neuro-fuzzy look-up table.

Original languageEnglish
Pages (from-to)694-699
Number of pages6
JournalMedical and Biological Engineering and Computing
Volume39
Issue number6
DOIs
Publication statusPublished - 2001 Jan 1

Fingerprint

Pacemakers
Information use
Sensors

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Computer Science Applications

Cite this

@article{9538864a11434f80b4dc66e6b61bcdd3,
title = "Rate-adaptive pacemaker controlled by motion and respiratory rate using neuro-fuzzy algorithm",
abstract = "Rate-adaptive pacemakers use information from sensors to change the rate of heart stimulation. Until now, fuzzy-pacemaker algorithms have been used to combine inputs from sensors to improve heart rate control, but they have been difficult to implement. In this paper, a pacemaker algorithm which controlled heart rate adaptively by motion and respiratory rate was studied. After chronotropic assessment exercise protocol (CAEP) tests were performed to collect activity and respiratory rate signals, the intrinsic heart rate was inferred from these two signals by a neuro-fuzzy method. For 10 subjects the heart rate inference, using the neuro-fuzzy algorithm, gave 52.4{\%} improved accuracy in comparison with the normal fuzzy table look-up method. The neuro-fuzzy method was applied to a real pacemaker by reduced mapping of the neuro-fuzzy look-up table.",
author = "Shin, {J. W.} and Junghan Yoon and Yoon, {Y. R.}",
year = "2001",
month = "1",
day = "1",
doi = "10.1007/BF02345444",
language = "English",
volume = "39",
pages = "694--699",
journal = "Medical and Biological Engineering and Computing",
issn = "0140-0118",
publisher = "Springer Verlag",
number = "6",

}

Rate-adaptive pacemaker controlled by motion and respiratory rate using neuro-fuzzy algorithm. / Shin, J. W.; Yoon, Junghan; Yoon, Y. R.

In: Medical and Biological Engineering and Computing, Vol. 39, No. 6, 01.01.2001, p. 694-699.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Rate-adaptive pacemaker controlled by motion and respiratory rate using neuro-fuzzy algorithm

AU - Shin, J. W.

AU - Yoon, Junghan

AU - Yoon, Y. R.

PY - 2001/1/1

Y1 - 2001/1/1

N2 - Rate-adaptive pacemakers use information from sensors to change the rate of heart stimulation. Until now, fuzzy-pacemaker algorithms have been used to combine inputs from sensors to improve heart rate control, but they have been difficult to implement. In this paper, a pacemaker algorithm which controlled heart rate adaptively by motion and respiratory rate was studied. After chronotropic assessment exercise protocol (CAEP) tests were performed to collect activity and respiratory rate signals, the intrinsic heart rate was inferred from these two signals by a neuro-fuzzy method. For 10 subjects the heart rate inference, using the neuro-fuzzy algorithm, gave 52.4% improved accuracy in comparison with the normal fuzzy table look-up method. The neuro-fuzzy method was applied to a real pacemaker by reduced mapping of the neuro-fuzzy look-up table.

AB - Rate-adaptive pacemakers use information from sensors to change the rate of heart stimulation. Until now, fuzzy-pacemaker algorithms have been used to combine inputs from sensors to improve heart rate control, but they have been difficult to implement. In this paper, a pacemaker algorithm which controlled heart rate adaptively by motion and respiratory rate was studied. After chronotropic assessment exercise protocol (CAEP) tests were performed to collect activity and respiratory rate signals, the intrinsic heart rate was inferred from these two signals by a neuro-fuzzy method. For 10 subjects the heart rate inference, using the neuro-fuzzy algorithm, gave 52.4% improved accuracy in comparison with the normal fuzzy table look-up method. The neuro-fuzzy method was applied to a real pacemaker by reduced mapping of the neuro-fuzzy look-up table.

UR - http://www.scopus.com/inward/record.url?scp=0035695265&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0035695265&partnerID=8YFLogxK

U2 - 10.1007/BF02345444

DO - 10.1007/BF02345444

M3 - Article

C2 - 11804178

AN - SCOPUS:0035695265

VL - 39

SP - 694

EP - 699

JO - Medical and Biological Engineering and Computing

JF - Medical and Biological Engineering and Computing

SN - 0140-0118

IS - 6

ER -