近红外可穿戴设备中脉搏波的呼吸率检测

陈星池; 赵海; 李晗; 郑换霞

doi:10.3788/OPE.20162406.1297

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近红外可穿戴设备中脉搏波的呼吸率检测

现代应用光学 | 更新时间：2020-08-13

- 近红外可穿戴设备中脉搏波的呼吸率检测
- Detection of respiratory rate using pulse wave on near infrared wearable devices
- 光学精密工程 2016年24卷第6期页码：1297-1306
- 作者机构：
  
  东北大学计算机科学与工程学院,辽宁沈阳,110819
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（No.60973022）();国家科技支撑计划资助项目（No.2012BAH82F04）();辽宁省科学技术计划项目（No.201540103
- DOI：10.3788/OPE.20162406.1297
  中图分类号： O657.33
- 收稿日期：2016-01-18，
  
  修回日期：2016-03-04，
  
  纸质出版日期：2016-06-25
- 稿件说明：
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陈星池, 赵海, 李晗等. 近红外可穿戴设备中脉搏波的呼吸率检测[J]. 光学精密工程, 2016,24(6): 1297-1306

CHEN Xing-chi, ZHAO Hai, LI Han etc. Detection of respiratory rate using pulse wave on near infrared wearable devices[J]. Editorial Office of Optics and Precision Engineering, 2016,24(6): 1297-1306
陈星池, 赵海, 李晗等. 近红外可穿戴设备中脉搏波的呼吸率检测[J]. 光学精密工程, 2016,24(6): 1297-1306 DOI： 10.3788/OPE.20162406.1297.

CHEN Xing-chi, ZHAO Hai, LI Han etc. Detection of respiratory rate using pulse wave on near infrared wearable devices[J]. Editorial Office of Optics and Precision Engineering, 2016,24(6): 1297-1306 DOI： 10.3788/OPE.20162406.1297.

摘要

针对可穿戴设备中光电容积脉搏波检测呼吸速率准确性不高和实时性不够的问题，提出了一种基于时频谱的自适应信号分解算法。该算法采用瞬时中心频率估计方法获得脉搏波时频谱和瞬时心率估计值，对脉搏信号进行相干解调提取呼吸信号成分，进而利用呼吸信号成分检测呼吸速率。实验结果表明，与传统连续小波变换方法相比，本文提出的自适应信号分解算法的呼吸速率计算时间提高了84.68%。通过中位数误差及四分位距误差的方差分析，表明该算法比连续小波分解算法和自回归模型算法具有更好的计算精度，中位数误差均值分别提高了96.001%和97.978%，四分位距误差均值分别提高了75.014%和52.732%。

Abstract

Aiming at the problems of the inaccuracy and insufficient instantaneity in estimation of respiratory rate from photoplethysmography(PPG) on the wearable devices

an Adaptive Signal Decomposition(ASD) algorithm based on time-frequency spectra was put forward. This algorithm adopted the instantaneous center frequency to obtain the pulse wave time-frequency spectra and instant heart rate estimated values

and the breath signal ingredient was extracted through coherent demodulation on the pulse signals

then the respiration signals can be used to detect the respiratory rate. The result indicates that in comparison with the conventional Continuous Wavelet Transform(CWT)

the respiratory rate calculation time of ASD algorithm has been increased by 84.68%. The variance analyses of the median error and the interquartile range error indicate that the ASD algorithm has the better calculation accuracy than the CWT algorithm and the autoregression model algorithm

with the median error means compared to which increased by 96.001% and 97.978% respectively and the interquartile range error means increased by 75.014% and 52.732% respectively.

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references

LE T Q , CHENG C Q, SANGASOONGSONG A, et al.. Prediction of sleep apnea episodes from a wireless wearable mutisensor suite[C]. Proceedings of IEEE Point-of-Care Healthcare Technologies, Bangalore, India. PHT, 2013: 152-155.

KANMAKAR C, KHANDOKER A, PENZEL T, et al.. Detection of respiratory arousals using Photoplethysmography (PPG) signal in sleep apnea patients[J]. IEEE Journal of Biomedical and Health Informatics, 2015,18(3): 1065-1073.

ZEMB P, GONCALVES H, BELLEC J Y, et al.. Prenatal observation of heart rate sequences presenting entropic analogies with sudden infant death syndrome: preliminary report[C]. Proceedings of IEEE the 26th International Symposium on Computer-Based Medical Systems, Porto, Portugal, CBMS, 2013: 421-424.

FEKR A R, RADECKA K, ZILLC Z. Design and evaluation of an intelligent remote tidal volume variability monitoring system in e-health applications[J]. IEEE Journal of Biomedical and Health Informatics, 2015,19(5): 1532-1548.

MIELOSZYK R J, VERGHESE G C, DEITCH K, et al..Automated quantitative analysis of capnogram shape for COPD-normal and COPD-CHF classification[J]. IEEE Transactions on Biomedical Engineering, 2014, 61(12): 2882-2890.

ORPHANIDOU C, FLEMING S, SHAH S A, et al.. Data fusion for estimating respiratory rate from a single-lead ECG[J]. Biomedical Signal Processing and Control, 2013, 8(1): 98-105.

ZHANG Z L. Photoplethysmography-based heart rate monitoring in physical activities via joint sparse spectrum reconstruction[J]. IEEE Transactions on Biomedical Engineering, 2015, 62(8): 1902-1910.

LOSSLESS G R. Compression technique for real-time photoplethysmographic measurements[J]. IEEE Transactions on Instrumentation and Measurement, 2015, 64(4): 308-316.

王蒙军,王楠,王霞,等. 由可见光谱视频中提取心率的对角累积量法[J]. 光学精密工程, 2015, 23(9): 2698-2707. WANG M J, WANG N, WANG X, et al.. Extracting heart rate from visible spectrum video based on diagonal cumulant algorithm[J].Opt. Precision Eng., 2015, 23(9): 2698-2707.(in Chinese)

LIU J J, HUANG M C, XU W Y, et al.. Breathsens: a continuous on-bed respiratory monitoring system with torso localization using an unobtrusive pressure sensing array[J]. IEEE Journal of Biomedical and Health Informatics, 2015, 19(5): 1682-1688.

吕扬,刘杰. 基于面部图像的心率测量系统[J]. 光学精密工程, 2015, 23(10z): 651-659. LV Y, LIU J. Heart rate acquisition system on facial image[J]. Opt. Precision Eng., 2015, 23(10z):651-659.(in Chinese)

刘通,司玉娟,臧睦君,等. 基于核主元分析和支持向量机的心拍识别[J]. 光学精密工程, 2015, 23(10z): 744-751. LIU T, SI Y J, ZANG M J, et al.. Electrocardiogram beat classification based on kernel principal component analysis and support vector machine[J].Opt. Precision Eng., 2015, 23(10z): 744-751.(in Chinese)

YANG Y H, TANG K T. A pulse oximetry system with motion artifact reduction based on Fourier analysis[C]. Proceedings of 2014 IEEE International Symposium on Bioelectronics and Bioinformatics, Chung Li, China Tai Wan:ISBB, 2014: 1-4.

MISRA S, SARKAR S. Priority-based time-slot allocation in wireless body area networks during medical emergency situations: an evolutionary game-theoretic perspective[J]. IEEE Journal of Biomedical and Health Informatics, 2015, 19(2): 541-548.

MATSUBARA M, OBA T, KADONE H. Wearable auditory biofeedback device for blind and sighted individuals[J]. IEEE MultiMedia, 2015, 22(1): 68-73.

邹滋润,陈真诚,朱健铭. 基于光电容积脉搏波的呼吸波提取[J]. 中国生物医学工程学报, 2013, 22(4): 508-512. ZOU Z R, CHEN ZH CH, ZHU J M. Extraction of respiratory wave from photoplethysmography signals[J]. Chinese Journal of Biomedical Engineering, 2013, 22(4): 508-512.(in Chinese)

LEIER M, JERVAN G, STORK W. Respiration signal extraction from photoplethysmogram using pulse wave amplitude variation[C]. Proceedings of IEEE International Conference on Communications, Sydney: NSW, ICC, 2014: 3535-3540.

DEHKORDI P, GARDE A, MOLAVI B. Estimating instantaneous respiratory rate from the photoplethysmogram[C]. Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan:EMBC, 2015:6150-6153.

ADDISON P S, WATSON W J, MESTEK M L. Pulse oximetry-derived respiratory rate in general care floor patients[J]. Journal of Clinical Monitoring and Computing, 2015, 29(1): 113-120.

SHAHA S A, FLEMING S, THOMPSON M. Respiratory rate estimation during triage of children in hospitals[J]. Journal of Medical Engineering & Technology, 2015, 39(8): 514-524.

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