Automatical Assessment of Fetal Status Based on Fuzzy Theory and Euclidean Distance_Journal of Biomedical Engineering

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Department of Electronic Engineering, Jinan University, Guangzhou 510632, China;

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Keywords：

cardiotocography; fetal state; fuzzy set; Euclidean distance

DOI：

10.7507/1001-5515.20160074

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Computer analysis of cardiotocography (CTG) is very significant to evaluate fetal status. However, current computer analysis based on traditional classification criteria is not ideal. In order to improve the accuracy of fetal status assessment, we proposed a new method. The new method improves the classification criteria and uses fuzzy set to represent the CTG parameters. And then feature vector is formed by that set to represent the CTG signal. By calculating and comparing the Euclidean distance between the signal feature vector and the standard state feature vector, the corresponding fetal status of the signal can be determined. Experiments showed that compared to the results of the first expert, the accuracy rate of new method was 88.3% which was higher than that (69.9%) of the traditional method, and the false positive rate of new method was 7.2% which was much lower than that (34.9%) of traditional methods. While compared to the results of the second expert, the accuracy of new method was 90.3% which was higher than that (66.0%) of the traditional method, and the false positive rate of new method was 9.0% which was well below the 38.2% of the traditional method. Thus the new method is reliable and effective.

Citation： LUYaosheng, YOUQihang, LIXiaodong. Automatical Assessment of Fetal Status Based on Fuzzy Theory and Euclidean Distance. Journal of Biomedical Engineering, 2016, 33(3): 436-441,447. doi: 10.7507/1001-5515.20160074 Copy

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10.	GALAZIOS G, TRIPSIANIS G, TSIKOURAS P, et al. Fetal distress evaluation using and analyzing the variables of antepartum computerized cardiotocography[J]. Arch Gynecol Obstet, 2010, 281(2) :229-233.
11.	张珂,葛明珠,贺晶,等.胎心率短期变异的临床意义及其与围产儿结局的关系[J].中华妇产科杂志,2007,42(4) :233-235.
12.	CZABA AN'U SKI R, JE AZ·U EWSKI M, WRÓBEL J, et al. Fuzzy system for evaluation of fetal heart rate signals using FIGO criteria[J]. Studies, 2009, 1(5) :6.
13.	CZABA AN'U SKI R, JE AZ·U EWSKI J, HOROBA K, et al. Fetal state assessment using fuzzy analysis of fetal heart rate signals——Agreement with the neonatal outcome[J]. Biocybernetics and Biomedical Engineering, 2013, 33(3) :145-155.
14.	严绍宗,童裕孙.实变函数论与泛函分析[M].北京:经济科学出版社,1992:39-40.
15.	LI Jing, LU Baoliang. An adaptive image Euclidean distance[J]. Pattern Recognit, 2009, 42(3) :349-357.
16.	LIU Lilan, YUAN Zilong, LIU Xuewei, et al. RFID unreliable data filtering by integrating adaptive sliding window and Euclidean distance[J]. Advances in Manufacturing, 2014, 2(2) :121-129.
17.	陆尧胜,魏守一,秦如意,等.一种胎心率基线自动识别算法:中国,CN102940485A[P].2013-02-27.
18.	程志厚,宋树良.胎儿电子监护学[M].北京:人民卫生出版社,2001:106.
19.	王锋,张国煊,张怀相.模糊隶属度函数的遗传优化[J].杭州电子科技大学学报,2009,29(4) :34-37.
20.	宋宇辰,张玉英,孟海东.一种基于加权欧氏距离聚类方法的研究[J].计算机工程与应用,2007,43(4) :179-180, 226.

1. ALFIREVIC Z, DEVANE D, GYTE G. Continuous cardiotocography (CTG) as a form of electronic fetal monitoring (EFM) for fetal assessment during labour[J]. Cochrane Database Syst Rev, 2006, 3(3) :CD006066.
2. SINAI T ALAULIKAR V, ARULKUMARAN S. Medico-Legal Issues with CTG Interpretation[J]. Current Women's Health Reviews, 2013, 9(3) :145-157.
3. 胡雅毅,刘兴会.产时胎心宫缩监护的评估及分级处理[J].中国实用妇科与产科杂志,2010,(2) :95-97.
4. 叶海慧,葛明珠,王正平.胎心率监护计算机分析在临床的应用[J].中国妇幼保健,2007,22(7) :904-906.
5. LISTON R, SAWCHUCK D, YOUNG D; Society of Obstetrics and Gynaecologists of Canada; British Columbia Perinatal Health Program. Fetal health surveillance:antepartum and intrapartum consensus guideline[J]. J Obstet Gynaecol Can, 2007, 29(9 Suppl 4) :S3-S56.
6. 刘立卫,张爱群,谢佳.胎心基线变异的意义[J].临床合理用药杂志,2014,(26) :31.
7. Royal College of Obstetricians and Gynaecologists. The use of electronic fetal monitoring:The use and interpretation of cardiotocography in intrapartum fetal surveillance[M]. London:Royal College of Obstetricians and Gynaecologists Press, 2001.
8. 谢幸,苟文丽.妇产科学[M].北京:人民卫生出版社,2013:142-153.
9. GARCIA G S, MARIANI NETO C, ARAUJO JÚNIOR E, et al. Fetal acidemia prediction through short-term variation assessed by antepartum computerized cardiotocography in pregnant women with hypertension syndrome[J]. Arch Gynecol Obstet, 2008, 278(2) :125-128.
10. GALAZIOS G, TRIPSIANIS G, TSIKOURAS P, et al. Fetal distress evaluation using and analyzing the variables of antepartum computerized cardiotocography[J]. Arch Gynecol Obstet, 2010, 281(2) :229-233.
11. 张珂,葛明珠,贺晶,等.胎心率短期变异的临床意义及其与围产儿结局的关系[J].中华妇产科杂志,2007,42(4) :233-235.
12. CZABA AN'U SKI R, JE AZ·U EWSKI M, WRÓBEL J, et al. Fuzzy system for evaluation of fetal heart rate signals using FIGO criteria[J]. Studies, 2009, 1(5) :6.
13. CZABA AN'U SKI R, JE AZ·U EWSKI J, HOROBA K, et al. Fetal state assessment using fuzzy analysis of fetal heart rate signals——Agreement with the neonatal outcome[J]. Biocybernetics and Biomedical Engineering, 2013, 33(3) :145-155.
14. 严绍宗,童裕孙.实变函数论与泛函分析[M].北京:经济科学出版社,1992:39-40.
15. LI Jing, LU Baoliang. An adaptive image Euclidean distance[J]. Pattern Recognit, 2009, 42(3) :349-357.
16. LIU Lilan, YUAN Zilong, LIU Xuewei, et al. RFID unreliable data filtering by integrating adaptive sliding window and Euclidean distance[J]. Advances in Manufacturing, 2014, 2(2) :121-129.
17. 陆尧胜,魏守一,秦如意,等.一种胎心率基线自动识别算法:中国,CN102940485A[P].2013-02-27.
18. 程志厚,宋树良.胎儿电子监护学[M].北京:人民卫生出版社,2001:106.
19. 王锋,张国煊,张怀相.模糊隶属度函数的遗传优化[J].杭州电子科技大学学报,2009,29(4) :34-37.
20. 宋宇辰,张玉英,孟海东.一种基于加权欧氏距离聚类方法的研究[J].计算机工程与应用,2007,43(4) :179-180, 226.

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