Blood pressure measurement system based on internet of things and deep learning
10.3969/j.issn.1005-202X.2024.11.010
- VernacularTitle:基于物联网和深度学习的血压测量系统
- Author:
Xizhuang ZHANG
1
;
Hengyuan LIANG
;
Shimin YIN
;
Zhencheng CHEN
;
Yongbo LIANG
Author Information
1. 桂林电子科技大学电子工程与自动化学院,广西桂林 541004
- Keywords:
deep learning;
embedded;
blood pressure;
internet of things;
cloud computing
- From:
Chinese Journal of Medical Physics
2024;41(11):1383-1391
- CountryChina
- Language:Chinese
-
Abstract:
A blood pressure measurement system based on internet of things and deep learning is proposed for continuous data acquisition and blood pressure prediction.The system adopts a hybrid neural network structure for processing the collected data and accurately predicting blood pressure,and the model consists of ResNet18,GRU and 3 fully connected layers.The data of 82 individuals are collected for training and testing.The mean absolute errors and standard deviations are 2.16 mmHg and 3.09 mmHg for diastolic blood pressure,3.15 mmHg and 5.14 mmHg for systolic blood pressure,according with AAMI standard and BHS standard.
