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Phonographic signal with a fractional-order chaotic system: a novel and simple algorithm for analyzing residual arteriovenous access stenosis

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Abstract

To detect the early developmental stages of arteriovenous access (AVA) stenosis in hemodialysis patients, this study explored a stenosis detector based on the Burg method and the fractional-order chaos system (FOCS). The bruit developed by the blood flowing through AVA can be a viable noninvasive strategy for monitoring AVA functions. We used the Burg method of the autoregressive model to estimate the frequency spectra of phonographic signals recorded by an electronic stethoscope in patients’ AVAs and to identify the spectral peaks in the region of 25–800 Hz. The frequency spectra differed significantly between normal and stenosis statuses in AVA. We found that the frequency and amplitude in power spectra analysis varied in accordance with the severity of AVA stenosis. However, the correlation of these parameters for classifying the degree of stenosis is limited when only using the Burg method. Therefore, we used an FOCS to monitor the differing frequency spectra between the normal condition and AVA stenosis. The variances of these two conditions were dynamic errors that were the coupling variables that tracked the responses between the master system and the slave system. A total of 42 patients who had received percutaneous transluminal angioplasty (PTA) for their failing AVAs was recruited for this study. In this study, the dynamic error, Index Ψ, was used to calculate the frequency spectrum redistribution in patients undergoing PTA. In addition, ΔImp was the index used to evaluate improvements in the luminal diameter between pre- and post-PTA. Therefore, we used linear regression to model the relationship between ΔImp and Index Ψ. The findings indicate that the proposed method has enhanced efficiency, especially in the venous anastomosis (V-site). The FOCS is a novel and simple algorithm for analyzing the residual AVA stenosis of PTA treatment.

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Acknowledgments

This study was supported and conducted by the Multidisciplinary Centre of Excellence for Clinical Trials and Research at National Cheng Kung University Hospital. In addition, this study was supported by the research grant DOH99-TD-B-111-002. We are grateful to Wei-Ming Wang for providing the statistical consulting services from the Biostatistics Consulting Center, National Cheng Kung University Hospital.

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Authors and Affiliations

  1. Department of Biomedical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City, 701, Taiwan, ROC

    Wei-Ling Chen & Tainsong Chen

  2. Medical Device Innovation Center, National Cheng Kung University, No. 1, University Road, Tainan City, 701, Taiwan, ROC

    Wei-Ling Chen

  3. Department of Electrical Engineering, Kao-Yuan University, No. 1821, Jhongshan Rd., Lujhu District, Kaohsiung City, 82151, Taiwan, ROC

    Chia-Hung Lin

  4. Department of Electrical Engineering, Southern Taiwan University, No. 1, Nan-Tai Street, Yungkang District, Tainan City, 710, Taiwan, ROC

    Pei-Jarn Chen

  5. Department of Surgery, National Cheng Kung University Hospital, No. 138, Sheng Li Road, Tainan City, 704, Taiwan, ROC

    Chung-Dann Kan

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  1. Wei-Ling Chen
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  2. Tainsong Chen
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  3. Chia-Hung Lin
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  5. Chung-Dann Kan
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Correspondence to Chung-Dann Kan.

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Chen, WL., Chen, T., Lin, CH. et al. Phonographic signal with a fractional-order chaotic system: a novel and simple algorithm for analyzing residual arteriovenous access stenosis. Med Biol Eng Comput 51, 1011–1019 (2013). https://doi.org/10.1007/s11517-013-1077-y

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  • DOI: https://doi.org/10.1007/s11517-013-1077-y

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