Real-time Detection Method for Motion Artifact of Photoplethysmography Signals Based on Decision Trees
10.12455/j.issn.1671-7104.230552
- VernacularTitle:基于决策树的光电容积脉搏波干扰段实时检测方法
- Author:
Linqi HU
1
,
2
;
Yulin ZHANG
;
Yongxin CHOU
;
Haiping YANG
;
Xiao HE
Author Information
1. 淮阴工学院,淮安市,223003
2. 常熟理工学院,常熟市,215500
- Keywords:
photoplethysmography;
motion artifact;
decision trees
- From:
Chinese Journal of Medical Instrumentation
2024;48(3):285-292
- CountryChina
- Language:Chinese
-
Abstract:
PPG(photoplethysmography)holds significant application value in wearable and intelligent health devices.However,during the acquisition process,PPG signals can generate motion artifacts due to inevitable coupling motion,which diminishes signal quality.In response to the challenge of real-time detection of motion artifacts in PPG signals,this study analyzed the generation and significant features of PPG signal interference.Seven features were extracted from the pulse interval data,and those exhibiting notable changes were filtered using the dual-sample Kolmogorov-Smirnov test.The real-time detection of motion artifacts in PPG signals was ultimately based on decision trees.In the experimental phase,PPG signal data from 20 college students were collected to formulate the experimental dataset.The experimental results demonstrate that the proposed method achieves an average accuracy of(94.07±1.14)%,outperforming commonly used motion artifact detection algorithms in terms of accuracy and real-time performance.
