An improved algorithm for electrohysterogram envelope extraction_Journal of Biomedical Engineering

Authors：

 LU Yaosheng , PAN Jie , CHEN Zhaoxia

Department of Electronic Engineering, Jinan University, Guangzhou 510632, P.R.China;

Corresponding author：

LU Yaosheng, Email: tluys@jnu.edu.cn

Keywords：

uterine electromyogram; zero-crossing detection; smoothing; envelope extraction

DOI：

10.7507/1001-5515.201605025

Video：

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Abstract Full text Figures/Tables Video References Cited by

Extraction uterine contraction signal from abdominal uterine electromyogram (EMG) signal is considered as the most promising method to replace the traditional tocodynamometer (TOCO) for detecting uterine contractions activity. The traditional root mean square (RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram (IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value (PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values (0.859 and 0.847) of the first comparison algorithm, but also higher than the values (0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

Citation： LUYaosheng, PANJie, CHENZhaoxia. An improved algorithm for electrohysterogram envelope extraction. Journal of Biomedical Engineering, 2017, 34(1): 92-98. doi: 10.7507/1001-5515.201605025 Copy

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2.	MAUL H, MANER W L, OLSON G, et al. Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. J Matern Fetal Neonatal Med, 2004, 15(5): 297-301.
3.	BUHIMSCHI C, BOYLE M B, GARFIELD R E. Electrical activity of the human uterus during pregnancy as recorded from the abdominal surface. Obstet Gynecol, 1997, 90(1): 102-111.
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6.	EULIANO T, SKOWRONSKI M, MAROSSERO D, et al. Prediction of intrauterine pressure waveform from transabdominal electrohysterography. J Matern Fetal Neonatal Med, 2006, 19(12): 811-816.
7.	HASSAN M, BOUDAOUD S, TERRIEN J, et al. Combination of canonical correlation analysis and empirical mode decomposition applied to denoising the labor electrohysterogram. IEEE Trans Biomed Eng, 2011, 58(9): 2441-2447.
8.	ALBEROLA-RUBIO J, PRATS-BOLUDA G, YE-LIN Y, et al. Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. Med Eng Phys, 2013, 35(12): 1736-1743.
9.	JACOD B C, GRAATSMA E M, VAN HAGEN E, et al. A validation of electrohysterography for uterine activity monitoring during labour. J Matern Fetal Neonatal Med, 2010, 23(1): 17-22.
10.	MANER W L, MACKAY L B, SAADE G R, et al. Characterization of abdominally acquired uterine electrical signals in humans, using a non-linear analytic method. Med Biol Eng Comput, 2006, 44(1/2): 117-123.
11.	RADHAKRISHNAN N, WILSON J D, LOWERY C, et al. A fast algorithm for detecting contractions in uterine electromyography. IEEE Eng Med Biol Mag, 2000, 19(2): 89-94.
12.	BHATTAD, TZOUN, WELLS J W, et al. Incoherent undersampling-based waveform reconstruction using a time-domain zero-crossing metric. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2015, 23(11): 2357-2370.
13.	MOLINARO A, SERGEYEV Y D. An efficient algorithm for the zero crossing detection in digitized measurement signal. Measurement, 2001, 30(3): 187-196.
14.	刘国宏, 郭文明. 改进的中值滤波去噪算法应用分析. 计算机工程与应用, 2010, 46(10): 187-189.
15.	DONG Y Q, XU S F. A new directional weighted median filter for removal of random-valued impulse noise. IEEE Signal Processing Letters, 2007, 14(3): 193-196.
16.	PAN Meisen, TANG Jingtian, YANG Xiaoli. An adaptive median filter algorithm based on B-spline function. International Journal of Automation and Computing, 2011, 8(1): 92-99.
17.	蔡坤. 围产期子宫活动监护新方法的研究. 广州: 暨南大学, 2004.

1. GARFIELD R E, MANER W L. Uterine electromyography in humans–contractions, labor, and delivery// 2007 11th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON 2007). Ljubljana, 2007: 128-130.
2. MAUL H, MANER W L, OLSON G, et al. Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. J Matern Fetal Neonatal Med, 2004, 15(5): 297-301.
3. BUHIMSCHI C, BOYLE M B, GARFIELD R E. Electrical activity of the human uterus during pregnancy as recorded from the abdominal surface. Obstet Gynecol, 1997, 90(1): 102-111.
4. SHULGIN V, SHEPEL O. Electrohysterographic signals processing for uterine activity detection and characterization// 2014 34th IEEE International Conference on Electronics and Nanotechnology (ELNANO). Kyiv, 2014: 269-272.
5. HOROBA K, JEZEWSKI J, WROBEL J, et al. Algorithm for detection of uterine contractions from electrohysterogram// 2001 23rd Annual International Conference of the IEEE Engineeringin Medicineand Biology Society. Istanbul, 2001: 2161-2164.
6. EULIANO T, SKOWRONSKI M, MAROSSERO D, et al. Prediction of intrauterine pressure waveform from transabdominal electrohysterography. J Matern Fetal Neonatal Med, 2006, 19(12): 811-816.
7. HASSAN M, BOUDAOUD S, TERRIEN J, et al. Combination of canonical correlation analysis and empirical mode decomposition applied to denoising the labor electrohysterogram. IEEE Trans Biomed Eng, 2011, 58(9): 2441-2447.
8. ALBEROLA-RUBIO J, PRATS-BOLUDA G, YE-LIN Y, et al. Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. Med Eng Phys, 2013, 35(12): 1736-1743.
9. JACOD B C, GRAATSMA E M, VAN HAGEN E, et al. A validation of electrohysterography for uterine activity monitoring during labour. J Matern Fetal Neonatal Med, 2010, 23(1): 17-22.
10. MANER W L, MACKAY L B, SAADE G R, et al. Characterization of abdominally acquired uterine electrical signals in humans, using a non-linear analytic method. Med Biol Eng Comput, 2006, 44(1/2): 117-123.
11. RADHAKRISHNAN N, WILSON J D, LOWERY C, et al. A fast algorithm for detecting contractions in uterine electromyography. IEEE Eng Med Biol Mag, 2000, 19(2): 89-94.
12. BHATTAD, TZOUN, WELLS J W, et al. Incoherent undersampling-based waveform reconstruction using a time-domain zero-crossing metric. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2015, 23(11): 2357-2370.
13. MOLINARO A, SERGEYEV Y D. An efficient algorithm for the zero crossing detection in digitized measurement signal. Measurement, 2001, 30(3): 187-196.
14. 刘国宏, 郭文明. 改进的中值滤波去噪算法应用分析. 计算机工程与应用, 2010, 46(10): 187-189.
15. DONG Y Q, XU S F. A new directional weighted median filter for removal of random-valued impulse noise. IEEE Signal Processing Letters, 2007, 14(3): 193-196.
16. PAN Meisen, TANG Jingtian, YANG Xiaoli. An adaptive median filter algorithm based on B-spline function. International Journal of Automation and Computing, 2011, 8(1): 92-99.
17. 蔡坤. 围产期子宫活动监护新方法的研究. 广州: 暨南大学, 2004.

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An improved algorithm for electrohysterogram envelope extraction

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