Bowel sound recognition using SVM classification in a wearable health monitoring system

This is a preview of subscription content, access via your institution.


  1. 1

    Huang Y, Song I S, Rana P, et al. Fast diagnosis of bowel activities. In: Proceedings of International Joint Conference on Neural Networks, Anchorage, 2017. 3042–3049

    Google Scholar 

  2. 2

    Uluşar Ü D. Recovery of gastrointestinal tract motility detection using naive Bayesian and minimum statistics. Comput Biol Med, 2014, 51: 223–228

    Article  Google Scholar 

  3. 3

    Öztaş A S, Türk E, Uluşar Ü D, et al. Bioacoustic sensor system for automatic detection of bowel sounds. In: Proceedings of IEEE Medical Technologies National Conference (TIPTEKNO), Bodrum, 2015

    Google Scholar 

  4. 4

    Spiegel B M R, Kaneshiro M, Russell M M, et al. Validation of an acoustic gastrointestinal surveillance biosensor for postoperative ileus. J Gastrointest Surg, 2014, 18: 1795–1803

    Article  Google Scholar 

  5. 5

    Amon M, Jager F. Electrocardiogram ST-segment morphology delineation method using orthogonal transformations. PLoS ONE, 2016, 11: 0148814

    Article  Google Scholar 

  6. 6

    Khalil I, Khalil A, Rehman S U, et al. Classification of ECG signals using Legendre moments. Int J Bioinform Biomed Eng, 2015, 1: 284–291

    Google Scholar 

  7. 7

    Yin Y, Jiang H J, Yang W D, et al. Intestinal motility assessment based on Legendre fitting of logarithmic bowel sound spectrum. Electron Lett, 2016, 52: 1364–1366

    Article  Google Scholar 

  8. 8

    Yin Y, Yang W D, Jiang H J, et al. Bowel sound based digestion state recognition using artificial neural network. In: Proceedings of IEEE Biomedical Circuits and Systems Conference, Atlanta, 2015

    Google Scholar 

  9. 9

    Bray D, Reilly R B, Haskin L, et al. Assessing motility though abdominal sound monitoring. In: Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, 1997. 2398–2400

    Google Scholar 

  10. 10

    Sheu M J, Lin P Y, Chen J Y, et al. Higher-order-statistics-based fractal dimension for noisy bowel sound detection. IEEE Signal Process Lett, 2015, 22: 789–793

    Article  Google Scholar 

Download references


This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61474070, 61431166002, 61661166010), and Beijing Engineering Research Center (Grant No. BG0149). The authors would like to thank the doctors who contributed to the experiments, including Ms. Huili KAN from Department of Anesthesiology, Liaocheng People’s Hospital and Mr. Jianjun LI from Department of Gastrointestinal Surgery, Liaocheng People’s Hospital.

Author information



Corresponding author

Correspondence to Hanjun Jiang.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yin, Y., Jiang, H., Feng, S. et al. Bowel sound recognition using SVM classification in a wearable health monitoring system. Sci. China Inf. Sci. 61, 084301 (2018).

Download citation