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

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

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


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
Issue number6
Publication statusPublished - 2001

Bibliographical note

Funding Information:
Acknowledgments" This study was supported by a grant from the Korean Health R&D Project, Ministry of Health & Welfare, Republic of Korea (HMP-98-E-4-0016).

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Computer Science Applications


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