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心电图机电磁干扰噪声对人工智能心电软件性能的影响研究 |
Study on the Influence of Electromagnetic Interference of ECG Device on the Performance of Artificial Intelligence ECG Software |
投稿时间:2019-06-24 修订日期:2019-08-05 |
DOI: |
中文关键词: 心电 人工智能 电磁干扰 数据集 |
英文关键词: ECG artificial intelligence electromagnetic susceptibility dataset |
基金项目:中国食品药品检定研究院中青年发展研究基金课题:人工智能医疗器械软件性能评价方法研究(2018C5) |
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中文摘要: |
目标:探索人工智能心电软件抵御心电图机电磁干扰噪声的能力,了解其准确性和鲁棒性。方法:本文选择个体心电图机为试验对象,在实验室内电磁兼容测试中采集心电导联上出现的电磁干扰波形。该波形与公开心电数据相叠加后由AI心电软件进行分析。比较AI心电软件分析原始数据和叠加噪声的数据的结果,分析心电图机上的电磁干扰噪声对AI心电软件分析结果准确性及鲁棒性的影响。结果:在本次试验中,射频传导干扰噪声对AI心电软件鲁棒性影响较大,工频干扰信号对于AI心电软件的性能影响较小。结论:AI心电软件的质量评价有必要关注心电图机等硬件设备中电磁干扰噪声的影响。 |
英文摘要: |
Objective:to explore the capability of artificial intelligence(AI) ECG software to tolerate electromagnetic noise from ECG device and understand its accuracy and robustness. Method: an individual ECG device is used to collect electromagnetic noise during a lab-based EMC test. The noise pattern is added into public ECG data and processed by an AI ECG software. The results before and after noise addition are compared, so as to evaluate the accuracy and robustness. Result: in this experiment, the impact of conduction noise appears more significant than power frequency noise on the performance of AI ECG software. Conclusion: the impact of electromagnetic noise on AI algorithm should be considered during the quality evaluation of AI ECG software. |
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