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使用深度相机对老年人进行非接触式呼吸测量

Non-Contact Respiratory Measurement Using a Depth Camera for Elderly People.

作者信息

Imano Wakana, Kameyama Kenichi, Hollingdal Malene, Refsgaard Jens, Larsen Knud, Topp Cecilie, Kronborg Sissel Højsted, Gade Josefine Dam, Dinesen Birthe

机构信息

Biomedical Engineering Laboratories, Teijin Pharma Ltd., Tokyo 191-8512, Japan.

Cardiology Ward, Regional Hospital Viborg, 8800 Sondersoparken, Denmark.

出版信息

Sensors (Basel). 2020 Dec 3;20(23):6901. doi: 10.3390/s20236901.

Abstract

Measuring respiration at home for cardiac patients, a simple method that can detect the patient's natural respiration, is needed. The purpose of this study was to develop an algorithm for estimating the tidal volume (TV) and respiratory rate (RR) from the depth value of the chest and/or abdomen, which were captured using a depth camera. The data of two different breathing patterns (normal and deep) were acquired from both the depth camera and the spirometer. The experiment was performed under two different clothing conditions (undressed and wearing a T-shirt). Thirty-nine elderly volunteers (male = 14) were enrolled in the experiment. The TV estimation algorithm for each condition was determined by regression analysis using the volume data from the spirometer as the objective variable and the depth motion data from the depth camera as the explanatory variable. The RR estimation was calculated from the peak interval. The mean absolute relative errors of the estimated TV for males were 14.0% under undressed conditions and 10.7% under T-shirt-wearing conditions; meanwhile, the relative errors for females were 14.7% and 15.5%, respectively. The estimation error for the RR was zero out of a total of 206 breaths under undressed conditions and two out of a total of 218 breaths under T-shirt-wearing conditions for males. Concerning females, the error was three out of a total of 329 breaths under undressed conditions and five out of a total of 344 breaths under T-shirt-wearing conditions. The developed algorithm for RR estimation was accurate enough, but the estimated occasionally TV had large errors, especially in deep breathing. The cause of such errors in TV estimation is presumed to be a result of the whole-body motion and inadequate setting of the measurement area.

摘要

需要一种在家中为心脏病患者测量呼吸的简单方法,该方法能够检测患者的自然呼吸。本研究的目的是开发一种算法,用于根据使用深度相机捕获的胸部和/或腹部深度值来估计潮气量(TV)和呼吸频率(RR)。从深度相机和肺活量计获取了两种不同呼吸模式(正常呼吸和深呼吸)的数据。实验在两种不同的着装条件下进行(裸体和穿着T恤)。三十九名老年志愿者(男性 = 14名)参与了实验。通过回归分析确定每种条件下的TV估计算法,将肺活量计的体积数据作为目标变量,将深度相机的深度运动数据作为解释变量。RR估计值根据峰值间隔计算得出。男性在裸体条件下估计TV的平均绝对相对误差为14.0%,在穿着T恤条件下为10.7%;同时,女性的相对误差分别为14.7%和15.5%。男性在裸体条件下206次呼吸中RR估计误差为零,在穿着T恤条件下218次呼吸中有两次误差。对于女性,在裸体条件下总共329次呼吸中有三次误差,在穿着T恤条件下总共344次呼吸中有五次误差。所开发的RR估计算法足够准确,但估计的TV偶尔会有较大误差,尤其是在深呼吸时。TV估计中出现这种误差的原因推测是全身运动和测量区域设置不当的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/7730632/4c88f4363158/sensors-20-06901-g001.jpg

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