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为提高在母体腹壁信号中胎儿心电信号微弱、基线漂移和噪声干扰较大的情况下匹配滤波法进行胎儿心电检测的能力，提出了基于聚类分析和模糊数学的胎儿心电检测方法：首先采取聚类分析的方法进行胎儿心电模板的提取，以提高胎儿心电模板和初始胎儿心电标准周期的准确度；而后用模糊模式识别的方法检测胎儿心电。提高了检测成功率和准确率，并使早搏的检测成为可能。
In order to improve the ability of matched filtering method to detect fetal ECG in the case of maternal abdominal signal with weak fetal ECG signal, baseline drift and large noise interference, a fetal ECG detection method based on clustering analysis and fuzzy mathematics is proposed. Firstly, the method of cluster analysis was used to extract the fetal ECG template to improve the accuracy of fetal ECG template and initial fetal ECG standard cycle. Then, the fetal ECG was detected by fuzzy pattern recognition. Improve the detection success rate and accuracy, and make the detection of premature beats possible.