基于脉搏波的呼吸频率计算方法

为了在可穿戴医疗领域中快速检测出人体的呼吸频率，提出一种基于光电容积脉搏波的呼吸频率计算方法。首 先，通过MIMIC Database数据集获取人体同时段的脉搏波信号与呼吸波信号；其次，通过对脉搏波信号运行经验模态分 解算法，从而获得脉搏波信号的有限个本征模态函数，再选取合适的本征模态函数重构呼吸波信号；最后，通过对重构的 呼吸波信号进行特征提取，计算出呼吸频率。结果表明:经过脉搏波分解得到的呼吸信号与原始呼吸信号的相对相干系 数在0.6以上，呼吸频率也十分接近，准确率高达0.9以上。说明通过光电容积脉搏波信号计算呼吸频率的可行性，这对于 可穿戴医疗领域、无创医疗诊断具有重要意义。

Calculation methods of respiratory rate based on PPG

A method of calculating respiratory rate based on photoplethysmography (PPG) is proposed for quickly detecting the human respiratory rate for wearable medical treatment. After that the PPG signals and the respiratory signals of the human body at the same time are selected from MIMIC Database, the PPG signals are processed by empirical mode decomposition algorithm, thereby obtaining a limited number of intrinsic mode functions of the PPG signals, and an appropriate intrinsic mode function is applied to reconstruct the respiratory signals. Finally, respiratory rate is calculated by extracting features from the reconstructed respiratory signal. The results show that the relative coherence coefficient of the respiratory signals obtained by PPG decomposition and the original respiratory signal is above 0.6, and that the reconstructed and original respiratory rates are also very close, with an accuracy rate up to 0.9. Using the PPG signals to calculate respiratory rate is proved to be feasible, which is of great significance to wearable medical treatment and non-invasive medical diagnosis.