Research on sleeping posture recognition method based on flexible pressure sensor

LIU Jinyue; ZHOU Zhiwen; JIA Xiaohui; GUO Shijie

doi:10.13873/J.1000-9787(2021)09-0010-04

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Research on sleeping posture recognition method based on flexible pressure sensor

更新时间：2025-09-11

- Research on sleeping posture recognition method based on flexible pressure sensor
- Issue 9, Pages: 10-13(2021)
- 作者机构：
  
  1. 河北工业大学机械工程学院
  2. 河北省机器人感知与人机融合重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2021)09-0010-04
  CLC： R318.6;TP212
- Published：2021
- 稿件说明：
移动端阅览
LIU Jinyue, ZHOU Zhiwen, JIA Xiaohui, et al. Research on sleeping posture recognition method based on flexible pressure sensor[J]. 2021, (9): 10-13.
DOI：

LIU Jinyue, ZHOU Zhiwen, JIA Xiaohui, et al. Research on sleeping posture recognition method based on flexible pressure sensor[J]. 2021, (9): 10-13. DOI： 10.13873/J.1000-9787(2021)09-0010-04.

摘要

目前使用的睡姿识别系统存在泄露隐私、束缚人体以及识别精度不高等问题

难以实现临床应用。为了提高睡姿识别的实用性

使用自主开发的柔性压力传感器无束缚采集六种睡姿图像

提出了一种基于支持向量机(SVM)并使用遗传算法(GA)进行关键参数优化的睡姿识别方法。实验表明:提出的方法能准确识别人体睡姿

平均识别准确率可达93.3%

在临床护理领域具有良好的应用前景。

Abstract

Current recognition system have some problems

such as divulging privacy

binding human body and low recognition precision

which make it difficult to achieve clinical application.In order to improve the practicability of sleeping posture recognition

a method based on support vector machine（SVM）is proposed to classify six sleeping posture images which collected by flexible pressure sensor without restriction.The genetic algorithm（GA）is applied to optimize the critical parameters of SVM.The experimental results show that the method can accurately recognize the sleeping postures with an average recognition accuracy of 93.3 %

which means it has a good application prospect in the field of clinical nursing.

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