心电仪器复杂电磁环境抗干扰与精度提升方法研究

Research on Anti-interference and Accuracy Improvement of ECG Instrument in Complex Electromagnetic Environment

摘要:

针对复杂电磁环境干扰导致心电诊断仪器信号失真、降低诊断精度的问题,本文提出基于波束赋形技术的抗干扰优化设计方案,结合S3C2410A处理器与ATmega16单片机构建双核协同硬件架构。通过优化硬件接口隔离、电源域分割及阻抗控制,同时利用波束赋形技术计算空域匹配权值并合成定向波束,辅以干扰识别与动态补偿算法,实现目标心电信号增强与干扰抑制。实验结果显示：在射频连续波、宽频噪声干扰下,该方案将心电信号信噪比提升至最大值0.2dB,信号波动范围分别控制在[-15dB,73dB]、[-16dB,73dB],与理想指标的误差仅为2dB、1dB；较传统方法(如变分模态分解、GNSS增强),信号波动偏差降低30dB以上。研究表明,该设计满足IEC60601医疗设备电磁兼容标准,可在复杂电磁环境下保障心电诊断的精准性,为极端场景下的可靠监护提供解决方案。

Abstract:

Aiming at the problem that the signal distortion of ECG diagnostic instrument is caused by the interference of complex electromagnetic environment, which reduces the diagnostic accuracy, this paper puts forward an anti-interference optimization design scheme based on beamforming technology, and constructs a dual-core collaborative hardware architecture by combining S3C2410A processor and ATmega16 single chip microcomputer. By optimizing hardware interface isolation, power domain division and impedance control, at the same time, using beamforming technology to calculate spatial matching weights and synthesize directional beams, supplemented by interference identification and dynamic compensation algorithms, the target ECG signal enhancement and interference suppression are realized. The experimental results show that under the interference of RF continuous wave and broadband noise, the signal-to-noise ratio of ECG signal is increased to the maximum value of 0.2dB, and the signal fluctuation range is controlled at [-15dB,73dB] and [-16dB,73dB] respectively, and the error from the ideal index is only 2dB and 1 dB. Compared with traditional methods (such as variational modal decomposition and GNSS enhancement), the signal fluctuation deviation is reduced by more than 30dB. The research shows that the design meets the electromagnetic compatibility standard of IEC60601 medical equipment, which can ensure the accuracy of ECG diagnosis in complex electromagnetic environment and provide a solution for reliable monitoring in extreme scenes.