Abstract：Objective To design an algorithm to identify ECG rhythms under CPR interference as a way to reduce the ECG rhythm
identification error rate and shorten the analysis time. Methods 13 eigenvalues were utilized to construct the neural network, and
the algorithm was optimized based on machine learning to increase the accuracy of ECG rhythm recognition. Results The
designed algorithm had high accuracy rate in the recognition of ECG rhythm under interference, especially 100% accuracy in the
recognition of VT, even when the interference was strong (SNR =-12), the recognition accuracy of all types of rhythm was above
95%. Conclusion The proposed algorithm has strong robustness in ECG rhythm recognition. Through performance evaluation
based on disturbed ECG signal data, it is proved that the algorithm achieves accurately discrimination of ventricular fibrillation and
ventricular tachycardia rhythms even when the signal is subjected to particularly high levels of interference.
基金资助:国家重点研发计划（ 2 0 1 7 Y F C 0 8 0 6 4 0 6 丨
2017YFC0806404丨2017YFC0806402)丨天津市重大科技计划
（18ZXJMTG00060）。
通讯作者:
陈锋
E-mail: chenfeng62037@hotmail.com
引用本文:
余明，袁晶，张广，万宗明，陈锋. 基于机器学习的心肺复苏干扰下心电节律识别算法研究[J]. 中国医疗设备, 2021, 36(6): 31-34.
YU Ming, YUAN Jing, ZHANG Guang, WAN Zongming, CHEN Feng. Research on ECG Rhythm Recognition Algorithm Under the Disturbance of Cardiopulmonary
Resuscitation Based on Machine Learning. China Medical Devices, 2021, 36(6): 31-34.
