基于深度学习的自适应睡枕设计  

Design of Adaptive Pillow Based on Deep Learning

作　　者：余益臻 任佳[1] 刘瑜[1] 郭力宁 YU Yi-Zhen;REN Jia;LIU Yu;GUO Li-Ning(Faculty of Mechanical Engineering and Automation,Zhejiang Sci-Tech University,Hangzhou 310018,China;Shenzhen Shenzhijie Technology Co.Ltd.,Shenzhen 518102,China)

机构地区：[1]浙江理工大学机械与自动控制学院,杭州310018 [2]深圳市深智杰科技有限公司,深圳518102

出　　处：《计算机系统应用》2021年第7期117-123,共7页Computer Systems & Applications

基　　金：浙江省公益技术研究项目(LGG20F030007)。

摘　　要：睡眠质量是影响人体健康的因素之一,而一个高度合适的枕头能够有效地改善睡眠质量.大量研究表明,人在侧躺时所需的枕头高度应大于平躺时所需的枕头高度.本文提出了一种基于深度学习的自适应睡枕设计方案,可以识别人的睡姿,调节枕头高度,并给出了硬件平台设计、网络模型搭建和移植.由枕头内部的压力传感器和气压传感器,分别采集头部对枕头的压力和枕头气囊内的气压,生成时间序列数据帧,再通过一维卷积网络(1DCNN)和门控循环单元网络(GRU)结合的网络模型对睡姿进行识别分类,最后根据不同的分类结果调节枕头高度.Sleep quality,which influences human health,can be greatly enhanced by a pillow with proper height.Substantial studies have revealed that the pillow’s height for persons lying on their sides should be greater than that for them lying on their backs.This paper introduces an adaptive pillow based on deep learning,which can recognize human sleeping positions to adjust the pillow’s height.The paper also presents hardware platform design and the construction and transplantation of neural network models.First,the pressure sensor and the air pressure sensor embedded in the pillow respectively collect the pressure of the head on the pillow and the air pressure in the pillow airbag to generate a timeseries data frame.Then,the 1DCNN-GRU network model identifies and classifies the sleeping positions.Finally,the pillow’s height is adjusted according to classifications.

关 键 词：睡姿识别 时间序列 深度学习 1DCNN GRU 

分 类 号：TS941.75[轻工技术与工程—服装设计与工程] TP18[自动化与计算机技术—控制理论与控制工程]