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Research Article
Bowel sound analysis using a common vector approach
Halil Güvenç1
Ümit Deniz Uluşar2
Güner Öğünç3
Murat Canpolat4
1Department of Electrical and Electronics Engineering, Akdeniz University, Turkey. 2Prof, Computer Engineering, Akdeniz University, Turkey. 3Prof, Surgical Medical Sciences, Akdeniz University, Turkey. 4Prof, Basic Medical Sciences of Akdeniz University, Turkey.
Published Online: January-February 2023
Pages: 37-47
Cite this article
No DOIReferences
[1] W. B. Cannon, “Auscultation of the rhythmic sounds produced by the stomach and intestines,” American Journal of Physiology-Legacy
Content, vol. 14, no. 4, pp. 339–353, Oct. 1905, doi: 10.1152/ajplegacy.1905.14.4.339.
[2] B. Georgoulis, “Bowel sounds,” Proc. R. Soc. Med., vol. 60, no. 9, pp. 917–920, Sep. 1967.
[3] W. C. Watson and E. C. Knox, “Phonoenterography: the recording and analysis of bowel sounds,” Gut, vol. 8, no. 1, pp. 88–94, Feb.
1967.
[4] D. Dalle, G. Devroede, R. Thibault, and J. Perrault, “Computer analysis of bowel sounds,” Computers in Biology and Medicine, vol. 4,
no. 3, pp. 247–256, Feb. 1975, doi: 10.1016/0010-4825(75)90036-0.
[5] C. Vasseur, G. Devroede, D. Dalle, N. Van Houtte, E. Bastin, and R. Thibault, “Postprandial bowel sounds,” IEEE Trans Biomed Eng,
vol. 22, no. 5, pp. 443–448, Sep. 1975.
[6] E. Arnbjörnsson, “Normal and pathological bowel sound patterns,” Ann Chir Gynaecol, vol. 75, no. 6, pp. 314–318, 1986.
[7] G. Vantrappen, J. Janssens, G. Coremans, and R. Jian, “Gastrointestinal motility disorders,” Dig. Dis. Sci., vol. 31, no. 9 Suppl, pp. 5S-
25S, Sep. 1986.
[8] H. A. Mansy and R. H. Sandler, “Bowel-sound signal enhancement using adaptive filtering,” IEEE Eng Med Biol Mag, vol. 16, no. 6,
pp. 105–117, Dec. 1997.
[9] L. J. Hadjileontiadis and S. M. Panas, “On modeling impulsive bioacoustic signals with symmetric /spl alpha/-stable distributions:
application in discontinuous adventitious lung sounds and explosive bowel sounds,” in Proceedings of the 20th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and
Beyond (Cat. No.98CH36286), Nov. 1998, pp. 13–16 vol.1. doi: 10.1109/IEMBS.1998.745810.
[10] Z. Xizheng, Y. Ling, and W. Weixiong, “An New Filtering Methods in the Wavelet Domain for Bowel Sounds,” International Journal of
Advanced Computer Science and Applications (IJACSA), vol. 1, no. 5, 2010, doi: 10.14569/IJACSA.2010.010505.
[11] L. J. Hadjileontiadis, T. P. Kontakos, C. N. Liatsos, C. C. Mavrogiannis, T. A. Rokkas, and S. M. Panas, “Enhancement of the
diagnostic character of bowel sounds using higher-order crossings,” in Proceedings of the First Joint BMES/EMBS Conference. 1999
IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering
Society (Cat. N, Oct. 1999, vol. 2, p. 1027 vols.2-. doi: 10.1109/IEMBS.1999.804180.
[12] L. J. Hadjileontiadis, C. N. Liatsos, C. C. Mavrogiannis, T. A. Rokkas, and S. M. Panas, “Enhancement of bowel sounds by wavelet-
based filtering,” IEEE Trans Biomed Eng, vol. 47, no. 7, pp. 876–886, Jul. 2000, doi: 10.1109/10.846681.
[13] L. J. Hadjileontiadis and I. T. Rekanos, “Detection of explosive lung and bowel sounds by means of fractal dimension,” IEEE Signal
Processing Letters, vol. 10, no. 10, pp. 311–314, Oct. 2003, doi: 10.1109/LSP.2003.817171.
[14] L. J. Hadjileontiadis and I. T. Rekanos, “Enhancement of explosive bowel sounds using Kurtosis-based filtering,” in Proceedings of the
25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), Sep.
2003, vol. 3, pp. 2479-2482 Vol.3. doi: 10.1109/IEMBS.2003.1280418.
[15] L. J. Hadjileontiadis, “Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding--Part I:
methodology,” IEEE Trans Biomed Eng, vol. 52, no. 6, pp. 1143–1148, Jun. 2005, doi: 10.1109/TBME.2005.846706.
[16] L. J. Hadjileontiadis, “Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding-part II: application
results,” IEEE Transactions on Biomedical Engineering, vol. 52, no. 6, pp. 1050–1064, Jun. 2005, doi: 10.1109/TBME.2005.846717.
[17] I. T. Rekanos and L. J. Hadjileontiadis, “An iterative kurtosis-based technique for the detection of nonstationary bioacoustic signals,”
Signal Processing, vol. 86, no. 12, pp. 3787–3795, Dec. 2006, doi: 10.1016/j.sigpro.2006.03.020.
[18] R. Ranta, C. Heinrich, V. Louis-Dorr, D. Wolf, and F. Guillemin, “Wavelet-based bowel sounds denoising, segmentation and
characterization,” in 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine
and Biology Society, Oct. 2001, vol. 2, pp. 1903–1906 vol.2. doi: 10.1109/IEMBS.2001.1020598.
[19] R. Ranta, V. Louis-Dorr, C. Heinrich, D. Wolf, and F. Guillemin, “Principal component analysis and interpretation of bowel sounds,”
in The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Sep. 2004, vol. 1, pp. 227–230.
doi: 10.1109/IEMBS.2004.1403133.
[20] O. Sakata, Y. Suzuki, K. Matsuda, and T. Satake, “Temporal changes in occurrence frequency of bowel sounds both in fasting state and
after eating,” J Artif Organs, vol. 16, no. 1, pp. 83–90, Mar. 2013, doi: 10.1007/s10047-012-0666-0.
[21] R. Sato, T. Emoto, Y. Gojima, and M. Akutagawa, “Automatic Bowel Motility Evaluation Technique for Noncontact Sound Recordings,”
Applied Sciences, vol. 8, no. 6, p. 999, Jun. 2018, doi: 10.3390/app8060999.
[22] Y. Yin et al., “Bowel sound recognition using SVM classification in a wearable health monitoring system,” Sci. China Inf. Sci., vol. 61,
no. 8, p. 084301, Jun. 2018, doi: 10.1007/s11432-018-9395-5.
[23] Y. Huang, I. Song, P. Rana, and G. Koh, “Fast diagnosis of bowel activities,” in 2017 International Joint Conference on Neural
Networks (IJCNN), May 2017, pp. 3042–3049. doi: 10.1109/IJCNN.2017.7966234.
[24] K. Kölle, A. Fougner, R. Ellingsen, S. Carlsen, and Ø. Stavdahl, “Feasibility of early meal detection based on abdominal sound,” IEEE
Journal of Translational Engineering in Health and Medicine, vol. PP, Sep. 2019, doi: 10.1109/JTEHM.2019.2940218.
[25] Y. Yin, H. Jiang, W. Yang, and Z. Wang, “Intestinal motility assessment based on Legendre fitting of logarithmic bowel sound
spectrum,” Electronics Letters, vol. 52, no. 16, pp. 1364–1366, 2016, doi: 10.1049/el.2016.1880.
[26] Z. Longfu, S. Yi, H. Sun, L. Zheng, H. Dapeng, and H. Yonghe, “Identification of bowel sound signal with spectral entropy method,” in
2015 12th IEEE International Conference on Electronic Measurement Instruments (ICEMI), Jul. 2015, vol. 02, pp. 798–802. doi:
10.1109/ICEMI.2015.7494333.
[27] Y. Yin, W. Yang, H. Jiang, and Z. Wang, “Bowel sound based digestion state recognition using artificial neural network,” in 2015 IEEE
Biomedical Circuits and Systems Conference (BioCAS), Oct. 2015, pp. 1–4. doi: 10.1109/BioCAS.2015.7348364.
[28] M. Li, J. Yang, and X. Wang, “Research on auto-identification method to the typical bowel sound signal,” in 2011 4th International
Conference on Biomedical Engineering and Informatics (BMEI), Oct. 2011, vol. 2, pp. 845–849. doi: 10.1109/BMEI.2011.6098435.
[29] B. Lin, M. Sheu, C. Chuang, K. Tseng, and J. Chen, “Enhancing Bowel Sounds by Using a Higher Order Statistics-Based Radial Basis
Function Network,” IEEE Journal of Biomedical and Health Informatics, vol. 17, no. 3, pp. 675–680, May 2013, doi:
10.1109/JBHI.2013.2244097.
[30] M. Sheu, P. Lin, J. Chen, C. Lee, and B. Lin, “Higher-Order-Statistics-Based Fractal Dimension for Noisy Bowel Sound Detection,”
IEEE Signal Processing Letters, vol. 22, no. 7, pp. 789–793, Jul. 2015, doi: 10.1109/LSP.2014.2369856.
[31] R. Ranta, V. Louis-Dorr, C. Heinrich, D. Wolf, and F. Guillemin, “AUTOMATIC SEGMENTATION AND CLASSIFICATION OF
BOWEL SOUNDS,” IEEE Signal Processing Letters, vol. 10, no. 8, p. 277, 2002.
[32] R. Ranta, V. Louis-Dorr, C. Heinrich, D. Wolf, and F. Guillemin, “Digestive activity evaluation by multichannel abdominal sounds
analysis,” IEEE Trans Biomed Eng, vol. 57, no. 6, pp. 1507–1519, Jun. 2010, doi: 10.1109/TBME.2010.2040081.
[33] T. Emoto et al., “ARMA-based spectral bandwidth for evaluation of bowel motility by the analysis of bowel sounds,” Physiol Meas, vol.
34, no. 8, pp. 925–936, Aug. 2013, doi: 10.1088/0967-3334/34/8/925.
[34] B. L. Craine, M. L. Silpa, and C. J. O’Toole, “Two-dimensional positional mapping of gastrointestinal sounds in control and functional
bowel syndrome patients,” Dig. Dis. Sci., vol. 47, no. 6, pp. 1290–1296, Jun. 2002.
[35] C. Dimoulas, G. Kalliris, G. Papanikolaou, and A. Kalampakas, “Novel wavelet domain Wiener filtering de-noising techniques:
Application to bowel sounds captured by means of abdominal surface vibrations,” Biomedical Signal Processing and Control, vol. 1,
no. 3, pp. 177–218, Jul. 2006, doi: 10.1016/j.bspc.2006.08.004.
[36] C. Dimoulas, G. Kalliris, G. Papanikolaou, and A. Kalampakas, “Long-term signal detection, segmentation and summarization using
wavelets and fractal dimension: a bioacoustics application in gastrointestinal-motility monitoring,” Comput. Biol. Med., vol. 37, no. 4,
pp. 438–462, Apr. 2007, doi: 10.1016/j.compbiomed.2006.08.013.
[37] C. Dimoulas, G. Kalliris, G. Papanikolaou, V. Petridis, and A. Kalampakas, “Bowel-sound pattern analysis using wavelets and neural
networks with application to long-term, unsupervised, gastrointestinal motility monitoring,” Expert Systems with Applications, vol. 34,
no. 1, pp. 26–41, Jan. 2008, doi: 10.1016/j.eswa.2006.08.014.
[38] C. A. Dimoulas, G. V. Papanikolaou, and V. Petridis, “Pattern classification and audiovisual content management techniques using
hybrid expert systems: A video-assisted bioacoustics application in Abdominal Sounds pattern analysis,” Expert Systems with
Applications, vol. 38, no. 10, pp. 13082–13093, Sep. 2011, doi: 10.1016/j.eswa.2011.04.115.
[39] C. A. Dimoulas, “Audiovisual Spatial-Audio Analysis by Means of Sound Localization and Imaging: A Multimedia Healthcare
Framework in Abdominal Sound Mapping,” IEEE Transactions on Multimedia, vol. 18, no. 10, pp. 1969–1976, Oct. 2016, doi:
10.1109/TMM.2016.2594148.
[40] O. Sakata and Y. Suzuki, “Optimum Unit Time on Calculating Occurrence Frequency of Bowel Sounds for Real-Time Monitoring of
Bowel Peristalsis,” International Journal of Signal Processing Systems, pp. 465–468, Dec. 2016, doi: 10.18178/ijsps.4.6.465-468.
[41] A. T. Delfini, L. E. A. Troncon, O. Baffa, R. B. Oliveira, and E. R. Moraes, “Digital Auscultation and Processing of Abdominal
Sounds,” in World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2010, pp.
1400–1402.
[42] C. Tsai, T. Wu, and Y. Chao, “Labview based bowel-sounds monitoring system in realtime,” in 2011 International Conference on
Machine Learning and Cybernetics, Jul. 2011, vol. 4, pp. 1815–1818. doi: 10.1109/ICMLC.2011.6017026.
[43] K.-S. Kim, J.-H. Seo, and C.-G. Song, “Non-invasive algorithm for bowel motility estimation using a back-propagation neural network
model of bowel sounds,” Biomed Eng Online, vol. 10, p. 69, Aug. 2011, doi: 10.1186/1475-925X-10-69.
[44] K. S. Kim, J. H. Seo, S. H. Ryu, M. H. Kim, and C. G. Song, “Estimation algorithm of the bowel motility based on regression analysis of
the jitter and shimmer of bowel sounds,” Comput Methods Programs Biomed, vol. 104, no. 3, pp. 426–434, Dec. 2011, doi:
10.1016/j.cmpb.2011.02.014.
[45] K.-S. Kim, H.-J. Park, H. S. Kang, and C.-G. Song, “Awareness system for bowel motility estimation based on artificial neural network
of bowel sounds,” in 4th International Conference on Awareness Science and Technology, Aug. 2012, pp. 185–188. doi:
10.1109/iCAwST.2012.6469611.
[46] K. Kölle, M. F. Aftab, L. E. Andersson, A. L. Fougner, and Ø. Stavdahl, “Data driven filtering of bowel sounds using multivariate
empirical mode decomposition,” BioMedical Engineering OnLine, vol. 18, no. 1, p. 28, Mar. 2019, doi: 10.1186/s12938-019-0646-1.
[47] C.-H. Chien, H.-T. Huang, C.-Y. Wang, and F.-C. Chong, “Two-dimensional static and dynamic display system of bowel sound
magnitude map for evaluation of intestinal motility,” Biomed. Eng. Appl. Basis Commun., vol. 21, no. 05, pp. 333–342, Oct. 2009, doi:
10.4015/S1016237209001428.
[48] F. Wang et al., “A flexible skin-mounted wireless acoustic device for bowel sounds monitoring and evaluation,” Sci. China Inf. Sci., vol.
62, no. 10, p. 202402, Sep. 2019, doi: 10.1007/s11432-019-9906-1.
[49] U. D. Ulusar, M. Canpolat, M. Yaprak, S. Kazanir, and G. Ogunc, “Real-time monitoring for recovery of gastrointestinal tract motility
detection after abdominal surgery,” in 2013 7th International Conference on Application of Information and Communication
Technologies, Oct. 2013, pp. 1–4. doi: 10.1109/ICAICT.2013.6722654.
[50] U. D. Ulusar, “Recovery of gastrointestinal tract motility detection using Naive Bayesian and minimum statistics,” Comput. Biol. Med.,
vol. 51, pp. 223–228, Aug. 2014, doi: 10.1016/j.compbiomed.2014.05.013.
[51] A. S. Öztaş et al., “Bioacoustic sensor system for automatic detection of bowel sounds,” in 2015 Medical Technologies National
Conference (TIPTEKNO), Oct. 2015, pp. 1–4. doi: 10.1109/TIPTEKNO.2015.7374601.
[52] E. Türk et al., “Wireless bioacoustic sensor system for automatic detection of bowel sounds,” in 2015 19th National Biomedical
Engineering Meeting (BIYOMUT), Nov. 2015, pp. 1–4. doi: 10.1109/BIYOMUT.2015.7369458.
[53] F. Al-Turjman, Ed., Edge Computing: From Hype to Reality. Springer International Publishing, 2019. Accessed: Jan. 20, 2019.
[Online]. Available: //www.springer.com/us/book/9783319990606
[54] H. Güvenç, “Wireless ECG Device with Arduino,” in 2020 Medical Technologies Congress (TIPTEKNO), Nov. 2020, pp. 1–4. doi:
10.1109/TIPTEKNO50054.2020.9299248.
[55] X. Du et al., “A mathematical model of bowel sound generation,” The Journal of the Acoustical Society of America, vol. 144, no. 6, pp.
EL485–EL491, Dec. 2018, doi: 10.1121/1.5080528.
[56] H. Cevikalp, M. Neamtu, M. Wilkes, and A. Barkana, “Discriminative common vectors for face recognition,” IEEE Trans. Pattern Anal.
Machine Intell., vol. 27, no. 1, pp. 4–13, Jan. 2005, doi: 10.1109/TPAMI.2005.9.
[57] H. Güvenç, “Ortak vektör yöntemiyle öznitelik çıkarımı,” 2009, Accessed: Jul. 17, 2022. [Online]. Available:
https://earsiv.anadolu.edu.tr/xmlui/handle/11421/4836
[58] M. J. Katz, “Fractals and the analysis of waveforms,” Computers in Biology and Medicine, vol. 18, no. 3, pp. 145–156, Jan. 1988, doi:
10.1016/0010-4825(88)90041-8.
Content, vol. 14, no. 4, pp. 339–353, Oct. 1905, doi: 10.1152/ajplegacy.1905.14.4.339.
[2] B. Georgoulis, “Bowel sounds,” Proc. R. Soc. Med., vol. 60, no. 9, pp. 917–920, Sep. 1967.
[3] W. C. Watson and E. C. Knox, “Phonoenterography: the recording and analysis of bowel sounds,” Gut, vol. 8, no. 1, pp. 88–94, Feb.
1967.
[4] D. Dalle, G. Devroede, R. Thibault, and J. Perrault, “Computer analysis of bowel sounds,” Computers in Biology and Medicine, vol. 4,
no. 3, pp. 247–256, Feb. 1975, doi: 10.1016/0010-4825(75)90036-0.
[5] C. Vasseur, G. Devroede, D. Dalle, N. Van Houtte, E. Bastin, and R. Thibault, “Postprandial bowel sounds,” IEEE Trans Biomed Eng,
vol. 22, no. 5, pp. 443–448, Sep. 1975.
[6] E. Arnbjörnsson, “Normal and pathological bowel sound patterns,” Ann Chir Gynaecol, vol. 75, no. 6, pp. 314–318, 1986.
[7] G. Vantrappen, J. Janssens, G. Coremans, and R. Jian, “Gastrointestinal motility disorders,” Dig. Dis. Sci., vol. 31, no. 9 Suppl, pp. 5S-
25S, Sep. 1986.
[8] H. A. Mansy and R. H. Sandler, “Bowel-sound signal enhancement using adaptive filtering,” IEEE Eng Med Biol Mag, vol. 16, no. 6,
pp. 105–117, Dec. 1997.
[9] L. J. Hadjileontiadis and S. M. Panas, “On modeling impulsive bioacoustic signals with symmetric /spl alpha/-stable distributions:
application in discontinuous adventitious lung sounds and explosive bowel sounds,” in Proceedings of the 20th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and
Beyond (Cat. No.98CH36286), Nov. 1998, pp. 13–16 vol.1. doi: 10.1109/IEMBS.1998.745810.
[10] Z. Xizheng, Y. Ling, and W. Weixiong, “An New Filtering Methods in the Wavelet Domain for Bowel Sounds,” International Journal of
Advanced Computer Science and Applications (IJACSA), vol. 1, no. 5, 2010, doi: 10.14569/IJACSA.2010.010505.
[11] L. J. Hadjileontiadis, T. P. Kontakos, C. N. Liatsos, C. C. Mavrogiannis, T. A. Rokkas, and S. M. Panas, “Enhancement of the
diagnostic character of bowel sounds using higher-order crossings,” in Proceedings of the First Joint BMES/EMBS Conference. 1999
IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering
Society (Cat. N, Oct. 1999, vol. 2, p. 1027 vols.2-. doi: 10.1109/IEMBS.1999.804180.
[12] L. J. Hadjileontiadis, C. N. Liatsos, C. C. Mavrogiannis, T. A. Rokkas, and S. M. Panas, “Enhancement of bowel sounds by wavelet-
based filtering,” IEEE Trans Biomed Eng, vol. 47, no. 7, pp. 876–886, Jul. 2000, doi: 10.1109/10.846681.
[13] L. J. Hadjileontiadis and I. T. Rekanos, “Detection of explosive lung and bowel sounds by means of fractal dimension,” IEEE Signal
Processing Letters, vol. 10, no. 10, pp. 311–314, Oct. 2003, doi: 10.1109/LSP.2003.817171.
[14] L. J. Hadjileontiadis and I. T. Rekanos, “Enhancement of explosive bowel sounds using Kurtosis-based filtering,” in Proceedings of the
25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), Sep.
2003, vol. 3, pp. 2479-2482 Vol.3. doi: 10.1109/IEMBS.2003.1280418.
[15] L. J. Hadjileontiadis, “Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding--Part I:
methodology,” IEEE Trans Biomed Eng, vol. 52, no. 6, pp. 1143–1148, Jun. 2005, doi: 10.1109/TBME.2005.846706.
[16] L. J. Hadjileontiadis, “Wavelet-based enhancement of lung and bowel sounds using fractal dimension thresholding-part II: application
results,” IEEE Transactions on Biomedical Engineering, vol. 52, no. 6, pp. 1050–1064, Jun. 2005, doi: 10.1109/TBME.2005.846717.
[17] I. T. Rekanos and L. J. Hadjileontiadis, “An iterative kurtosis-based technique for the detection of nonstationary bioacoustic signals,”
Signal Processing, vol. 86, no. 12, pp. 3787–3795, Dec. 2006, doi: 10.1016/j.sigpro.2006.03.020.
[18] R. Ranta, C. Heinrich, V. Louis-Dorr, D. Wolf, and F. Guillemin, “Wavelet-based bowel sounds denoising, segmentation and
characterization,” in 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine
and Biology Society, Oct. 2001, vol. 2, pp. 1903–1906 vol.2. doi: 10.1109/IEMBS.2001.1020598.
[19] R. Ranta, V. Louis-Dorr, C. Heinrich, D. Wolf, and F. Guillemin, “Principal component analysis and interpretation of bowel sounds,”
in The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Sep. 2004, vol. 1, pp. 227–230.
doi: 10.1109/IEMBS.2004.1403133.
[20] O. Sakata, Y. Suzuki, K. Matsuda, and T. Satake, “Temporal changes in occurrence frequency of bowel sounds both in fasting state and
after eating,” J Artif Organs, vol. 16, no. 1, pp. 83–90, Mar. 2013, doi: 10.1007/s10047-012-0666-0.
[21] R. Sato, T. Emoto, Y. Gojima, and M. Akutagawa, “Automatic Bowel Motility Evaluation Technique for Noncontact Sound Recordings,”
Applied Sciences, vol. 8, no. 6, p. 999, Jun. 2018, doi: 10.3390/app8060999.
[22] Y. Yin et al., “Bowel sound recognition using SVM classification in a wearable health monitoring system,” Sci. China Inf. Sci., vol. 61,
no. 8, p. 084301, Jun. 2018, doi: 10.1007/s11432-018-9395-5.
[23] Y. Huang, I. Song, P. Rana, and G. Koh, “Fast diagnosis of bowel activities,” in 2017 International Joint Conference on Neural
Networks (IJCNN), May 2017, pp. 3042–3049. doi: 10.1109/IJCNN.2017.7966234.
[24] K. Kölle, A. Fougner, R. Ellingsen, S. Carlsen, and Ø. Stavdahl, “Feasibility of early meal detection based on abdominal sound,” IEEE
Journal of Translational Engineering in Health and Medicine, vol. PP, Sep. 2019, doi: 10.1109/JTEHM.2019.2940218.
[25] Y. Yin, H. Jiang, W. Yang, and Z. Wang, “Intestinal motility assessment based on Legendre fitting of logarithmic bowel sound
spectrum,” Electronics Letters, vol. 52, no. 16, pp. 1364–1366, 2016, doi: 10.1049/el.2016.1880.
[26] Z. Longfu, S. Yi, H. Sun, L. Zheng, H. Dapeng, and H. Yonghe, “Identification of bowel sound signal with spectral entropy method,” in
2015 12th IEEE International Conference on Electronic Measurement Instruments (ICEMI), Jul. 2015, vol. 02, pp. 798–802. doi:
10.1109/ICEMI.2015.7494333.
[27] Y. Yin, W. Yang, H. Jiang, and Z. Wang, “Bowel sound based digestion state recognition using artificial neural network,” in 2015 IEEE
Biomedical Circuits and Systems Conference (BioCAS), Oct. 2015, pp. 1–4. doi: 10.1109/BioCAS.2015.7348364.
[28] M. Li, J. Yang, and X. Wang, “Research on auto-identification method to the typical bowel sound signal,” in 2011 4th International
Conference on Biomedical Engineering and Informatics (BMEI), Oct. 2011, vol. 2, pp. 845–849. doi: 10.1109/BMEI.2011.6098435.
[29] B. Lin, M. Sheu, C. Chuang, K. Tseng, and J. Chen, “Enhancing Bowel Sounds by Using a Higher Order Statistics-Based Radial Basis
Function Network,” IEEE Journal of Biomedical and Health Informatics, vol. 17, no. 3, pp. 675–680, May 2013, doi:
10.1109/JBHI.2013.2244097.
[30] M. Sheu, P. Lin, J. Chen, C. Lee, and B. Lin, “Higher-Order-Statistics-Based Fractal Dimension for Noisy Bowel Sound Detection,”
IEEE Signal Processing Letters, vol. 22, no. 7, pp. 789–793, Jul. 2015, doi: 10.1109/LSP.2014.2369856.
[31] R. Ranta, V. Louis-Dorr, C. Heinrich, D. Wolf, and F. Guillemin, “AUTOMATIC SEGMENTATION AND CLASSIFICATION OF
BOWEL SOUNDS,” IEEE Signal Processing Letters, vol. 10, no. 8, p. 277, 2002.
[32] R. Ranta, V. Louis-Dorr, C. Heinrich, D. Wolf, and F. Guillemin, “Digestive activity evaluation by multichannel abdominal sounds
analysis,” IEEE Trans Biomed Eng, vol. 57, no. 6, pp. 1507–1519, Jun. 2010, doi: 10.1109/TBME.2010.2040081.
[33] T. Emoto et al., “ARMA-based spectral bandwidth for evaluation of bowel motility by the analysis of bowel sounds,” Physiol Meas, vol.
34, no. 8, pp. 925–936, Aug. 2013, doi: 10.1088/0967-3334/34/8/925.
[34] B. L. Craine, M. L. Silpa, and C. J. O’Toole, “Two-dimensional positional mapping of gastrointestinal sounds in control and functional
bowel syndrome patients,” Dig. Dis. Sci., vol. 47, no. 6, pp. 1290–1296, Jun. 2002.
[35] C. Dimoulas, G. Kalliris, G. Papanikolaou, and A. Kalampakas, “Novel wavelet domain Wiener filtering de-noising techniques:
Application to bowel sounds captured by means of abdominal surface vibrations,” Biomedical Signal Processing and Control, vol. 1,
no. 3, pp. 177–218, Jul. 2006, doi: 10.1016/j.bspc.2006.08.004.
[36] C. Dimoulas, G. Kalliris, G. Papanikolaou, and A. Kalampakas, “Long-term signal detection, segmentation and summarization using
wavelets and fractal dimension: a bioacoustics application in gastrointestinal-motility monitoring,” Comput. Biol. Med., vol. 37, no. 4,
pp. 438–462, Apr. 2007, doi: 10.1016/j.compbiomed.2006.08.013.
[37] C. Dimoulas, G. Kalliris, G. Papanikolaou, V. Petridis, and A. Kalampakas, “Bowel-sound pattern analysis using wavelets and neural
networks with application to long-term, unsupervised, gastrointestinal motility monitoring,” Expert Systems with Applications, vol. 34,
no. 1, pp. 26–41, Jan. 2008, doi: 10.1016/j.eswa.2006.08.014.
[38] C. A. Dimoulas, G. V. Papanikolaou, and V. Petridis, “Pattern classification and audiovisual content management techniques using
hybrid expert systems: A video-assisted bioacoustics application in Abdominal Sounds pattern analysis,” Expert Systems with
Applications, vol. 38, no. 10, pp. 13082–13093, Sep. 2011, doi: 10.1016/j.eswa.2011.04.115.
[39] C. A. Dimoulas, “Audiovisual Spatial-Audio Analysis by Means of Sound Localization and Imaging: A Multimedia Healthcare
Framework in Abdominal Sound Mapping,” IEEE Transactions on Multimedia, vol. 18, no. 10, pp. 1969–1976, Oct. 2016, doi:
10.1109/TMM.2016.2594148.
[40] O. Sakata and Y. Suzuki, “Optimum Unit Time on Calculating Occurrence Frequency of Bowel Sounds for Real-Time Monitoring of
Bowel Peristalsis,” International Journal of Signal Processing Systems, pp. 465–468, Dec. 2016, doi: 10.18178/ijsps.4.6.465-468.
[41] A. T. Delfini, L. E. A. Troncon, O. Baffa, R. B. Oliveira, and E. R. Moraes, “Digital Auscultation and Processing of Abdominal
Sounds,” in World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2010, pp.
1400–1402.
[42] C. Tsai, T. Wu, and Y. Chao, “Labview based bowel-sounds monitoring system in realtime,” in 2011 International Conference on
Machine Learning and Cybernetics, Jul. 2011, vol. 4, pp. 1815–1818. doi: 10.1109/ICMLC.2011.6017026.
[43] K.-S. Kim, J.-H. Seo, and C.-G. Song, “Non-invasive algorithm for bowel motility estimation using a back-propagation neural network
model of bowel sounds,” Biomed Eng Online, vol. 10, p. 69, Aug. 2011, doi: 10.1186/1475-925X-10-69.
[44] K. S. Kim, J. H. Seo, S. H. Ryu, M. H. Kim, and C. G. Song, “Estimation algorithm of the bowel motility based on regression analysis of
the jitter and shimmer of bowel sounds,” Comput Methods Programs Biomed, vol. 104, no. 3, pp. 426–434, Dec. 2011, doi:
10.1016/j.cmpb.2011.02.014.
[45] K.-S. Kim, H.-J. Park, H. S. Kang, and C.-G. Song, “Awareness system for bowel motility estimation based on artificial neural network
of bowel sounds,” in 4th International Conference on Awareness Science and Technology, Aug. 2012, pp. 185–188. doi:
10.1109/iCAwST.2012.6469611.
[46] K. Kölle, M. F. Aftab, L. E. Andersson, A. L. Fougner, and Ø. Stavdahl, “Data driven filtering of bowel sounds using multivariate
empirical mode decomposition,” BioMedical Engineering OnLine, vol. 18, no. 1, p. 28, Mar. 2019, doi: 10.1186/s12938-019-0646-1.
[47] C.-H. Chien, H.-T. Huang, C.-Y. Wang, and F.-C. Chong, “Two-dimensional static and dynamic display system of bowel sound
magnitude map for evaluation of intestinal motility,” Biomed. Eng. Appl. Basis Commun., vol. 21, no. 05, pp. 333–342, Oct. 2009, doi:
10.4015/S1016237209001428.
[48] F. Wang et al., “A flexible skin-mounted wireless acoustic device for bowel sounds monitoring and evaluation,” Sci. China Inf. Sci., vol.
62, no. 10, p. 202402, Sep. 2019, doi: 10.1007/s11432-019-9906-1.
[49] U. D. Ulusar, M. Canpolat, M. Yaprak, S. Kazanir, and G. Ogunc, “Real-time monitoring for recovery of gastrointestinal tract motility
detection after abdominal surgery,” in 2013 7th International Conference on Application of Information and Communication
Technologies, Oct. 2013, pp. 1–4. doi: 10.1109/ICAICT.2013.6722654.
[50] U. D. Ulusar, “Recovery of gastrointestinal tract motility detection using Naive Bayesian and minimum statistics,” Comput. Biol. Med.,
vol. 51, pp. 223–228, Aug. 2014, doi: 10.1016/j.compbiomed.2014.05.013.
[51] A. S. Öztaş et al., “Bioacoustic sensor system for automatic detection of bowel sounds,” in 2015 Medical Technologies National
Conference (TIPTEKNO), Oct. 2015, pp. 1–4. doi: 10.1109/TIPTEKNO.2015.7374601.
[52] E. Türk et al., “Wireless bioacoustic sensor system for automatic detection of bowel sounds,” in 2015 19th National Biomedical
Engineering Meeting (BIYOMUT), Nov. 2015, pp. 1–4. doi: 10.1109/BIYOMUT.2015.7369458.
[53] F. Al-Turjman, Ed., Edge Computing: From Hype to Reality. Springer International Publishing, 2019. Accessed: Jan. 20, 2019.
[Online]. Available: //www.springer.com/us/book/9783319990606
[54] H. Güvenç, “Wireless ECG Device with Arduino,” in 2020 Medical Technologies Congress (TIPTEKNO), Nov. 2020, pp. 1–4. doi:
10.1109/TIPTEKNO50054.2020.9299248.
[55] X. Du et al., “A mathematical model of bowel sound generation,” The Journal of the Acoustical Society of America, vol. 144, no. 6, pp.
EL485–EL491, Dec. 2018, doi: 10.1121/1.5080528.
[56] H. Cevikalp, M. Neamtu, M. Wilkes, and A. Barkana, “Discriminative common vectors for face recognition,” IEEE Trans. Pattern Anal.
Machine Intell., vol. 27, no. 1, pp. 4–13, Jan. 2005, doi: 10.1109/TPAMI.2005.9.
[57] H. Güvenç, “Ortak vektör yöntemiyle öznitelik çıkarımı,” 2009, Accessed: Jul. 17, 2022. [Online]. Available:
https://earsiv.anadolu.edu.tr/xmlui/handle/11421/4836
[58] M. J. Katz, “Fractals and the analysis of waveforms,” Computers in Biology and Medicine, vol. 18, no. 3, pp. 145–156, Jan. 1988, doi:
10.1016/0010-4825(88)90041-8.
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