基于心冲击信号的心率检测方法

针对现有基于心冲击描记图进行心率检测存在的抗干扰性不足问题，提出一种鲁棒的心率检测模型，首先对原始信号中受干扰的片段进行补偿重构，然后将J峰作为特征波形，通过基于J峰频段的滤波与差分增强处理放大特征，并设计改进的峰值提取算法定位心跳点，进而得到心率估计值。实验结果表明，所用模型对于不同情形下的心冲击描记图信号均表现出良好的适应性，逐拍检测平均覆盖率为98.3%，平均准确率为98.4%。心率输出结果与金标准一致性高，误差范围控制在[±]5%以内，且运算实时性好，可以为临床或家庭保健提供良好的心率检测方案。

Heart rate detection based on ballistocardiogram signals

Abstract: In view of the lack of anti-interference in existing heart rate detection based on ballistocardiograms, a robust heart rate detection model is proposed. After compensating the interfered fragments in the original signal, J-peak is taken as feature waveform, and J-wave features are amplified based on the filtering of J-peak frequency band and enhanced differential processing. Finally, an improved peak extraction algorithm is designed to locate the heartbeat and then obtain the estimation of heart rate. The experimental results show that the model used in the study has good adaptability to ballistocardiogram signals in different situations. The average coverage rate of beat by beat detection is 98.3%, and the average accuracy reached 98.4%. The heart rate output is in high consistency with gold standard, with an error controlled within ±5%. Moreover, the real-time operation is satisfactory. The proposed method can provide an appropriate heart rate detection scheme for clinical or family health care.