According to the precise
blood pressure measuring method based on the portable
pulse diagnosis instrument, the pulse and
blood pressure data of the subject are collected, and systematic
data processing and analysis are carried out, so that precise prediction of the
blood pressure is achieved. The method comprises the following steps: collecting left and right hand pulse data by using a portable
pulse diagnosis instrument, and synchronously collecting blood
pressure data to establish a mapping relation between pulse and blood pressure; the
data processing step comprises data cleaning, Shannon sampling and
wavelet threshold
denoising algorithm, and accuracy and reliability of pulse signals are ensured. By constructing a
machine learning regression model improved based on Hunter Prey Optimization (HPO) and combining an XGBoost
algorithm for prediction, the generalization ability and stability of the model are improved. According to the model, a
mean square error (MSE) is adopted as a
loss function, iterative optimization is performed through an
adaptive learning rate adjustment strategy,
overfitting is effectively reduced, and prediction precision is improved. Finally, blood pressure prediction is conducted on the pulse data of the subject through the model,
error analysis is conducted, and the clinical application effect of the model is verified. The
system has high efficiency, accuracy and stability, and a non-contact and convenient technical scheme is provided for portable blood
pressure measurement.