Study on the accuracy of cardiopulmonary physiological measurements by a wearable physiological monitoring system under different activity conditions_Journal of Biomedical Engineering

Authors：

XU Haoran ¹ , CHU Wenya ² , LIU Xiaoli ³ , ZHANG Shasha ⁴ , YANG Zhicheng ⁵ , ZHENG Jiewen ² , GAO Xiaolin ⁶ ,  ZHANG Zhengbo ^7,8 , CAO Desen ^7,8

1. Medical School of Chinese PLA, Beijing 100853, P.R.China;
2. Beijing Health Regulation Co.,Ltd, Beijing 100853, P.R.China;
3. School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, P.R.China;
4. Library of the Academy of Military Sciences, Beijing 100039, P.R.China;
5. UC Davis, Davis, California USA, 95616;
6. Institute of Sports Science, General Administration of Sport of China, Beijing 100061, P.R.China;
7. Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing 100853, P.R.China;
8. Center for Research and Evaluation of Medical Devices, Chinese PLA General Hospital, Beijing 100853, P.R.China;

Corresponding author：

ZHANG Zhengbo, Email: zhengbozhang@126.com

Keywords：

wearable device; sport; heart rate; breathing rate

DOI：

10.7507/1001-5515.201903061

Video：

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This paper aims to study the accuracy of cardiopulmonary physiological parameters measurement under different exercise intensity in the accompanying (wearable) physiological parameter monitoring system. SensEcho, an accompanying physiological parameter monitoring system, and CORTEX METALYZER 3B, a cardiopulmonary function testing system, were used to simultaneously collect the cardiopulmonary physiological parameters of 28 healthy volunteers (17 males and 11 females) in various exercise states, such as standing, lying down and Bruce treadmill exercise. Bland-Altman analysis, correlation analysis and other methods, from the perspective of group and individual, were used to contrast and analyze the two types of equipment to measure parameters of heart rate and breathing rate. The results of group analysis showed that the heart rate and respiratory rate data box charts collected by the two devices were highly consistent. The heart rate difference was (−0.407 ± 3.380) times/min, and the respiratory rate difference was (−0.560 ± 7.047) times/min. The difference was very small. The Bland-Altman plot of the heart rate and respiratory rate in each experimental stage showed that the proportion of mean ± 2SD was 96.86% and 95.29%, respectively. The results of individual analysis showed that the correlation coefficients of the whole-process heart rate and respiratory rate data were all greater than 0.9. In conclusion, SensEcho, as an accompanying physiological parameter monitoring system, can accurately measure the human heart rate, respiration rate and other key cardiopulmonary physiological parameters under various sports conditions. It can maintain good stability under various sports conditions and meet the requirements of continuous physiological signal collection and analysis application under sports conditions.

Citation： XU Haoran, CHU Wenya, LIU Xiaoli, ZHANG Shasha, YANG Zhicheng, ZHENG Jiewen, GAO Xiaolin, ZHANG Zhengbo, CAO Desen. Study on the accuracy of cardiopulmonary physiological measurements by a wearable physiological monitoring system under different activity conditions. Journal of Biomedical Engineering, 2020, 37(1): 119-128. doi: 10.7507/1001-5515.201903061 Copy

1.	徐令仪, 汪长岭, 毛靖宁, 等. 可穿戴技术在生理信号监测中的应用和发展. 中国医疗设备, 2018, 33(3): 118-120, 135.
2.	韦哲, 薛翔, 吕克难. 可穿戴设备在医院诊疗中的应用研究进展. 中国医学装备, 2017, 14(8): 170-173.
3.	孙爱华, 孙咏晖, 齐芳. 可穿戴智能运动设备发展的局限性因素及对策研究. 山东体育科技, 2017, 39(3): 27-30.
4.	蒋小梅, 张俊然, 赵斌, 等. 可穿戴式设备分类及其相关技术进展. 生物医学工程学杂志, 2016, 33(1): 42-48.
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6.	Taffoni F, Rivera D, La Camera A, et al. A wearable system for real-time continuous monitoring of physical activity. J Healthc Eng, 2018, 2018: 1878354.
7.	潘良凤, 文艳红. 可穿戴设备在慢性病高危人群管理模式中的应用. 中国热带医学, 2016, 16(7): 685-687.
8.	张政波, 王卫东, 刘延武, 等. 穿戴式 COPD 肺康复装置及方法. 医疗卫生装备, 2008, 29(1): 14-15, 23.
9.	McNaney R, Vines J, Roggen D, et al. Exploring the acceptability of Google Glass as an everyday assistive device for people with Parkinson's// Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Toronto: Association for Computing Machinery, 2014: 2551-2554.
10.	韩子鹏, 敖国政, 吉长东. 一种可穿戴快速运动强度检测方法研究. 中国体育科技, 2016, 52(6): 115-121.
11.	谢凌钦, 石萍, 蔡文杰. 可穿戴式智能设备关键技术及发展趋势. 生物医学工程与临床, 2015, 19(6): 635-640.
12.	杨小帆, 郭雅萍. 运动可穿戴设备的发展趋势研究. 福建体育科技, 2018, 37(3): 19-21, 39.
13.	Liu Y, Zhu S H, Wang G H, et al. Validity and reliability of multiparameter physiological measurements recorded by the Equivital LifeMonitor during activities of various intensities. J Occup Environ Hyg, 2013, 10(2): 78-85.
14.	Benfante A, Di Marco F, Terraneo S, et al. Dynamic hyperinflation during the 6-min walk test in severely asthmatic subjects. ERJ Open Res, 2018, 4(2). pii: 00143-2017.
15.	Elliot C A, Hamlin M J, Lizamore C A. Validity and reliability of the Hexoskin^® wearable biometric vest during maximal aerobic power testing in elite cyclists. J Str Condit Res, 2017: 1-8.
16.	Villar R, Beltrame T, Hughson R L. Validation of the Hexoskin wearable vest during lying, sitting, standing, and walking activities. Appl Physiol Nutr Metab, 2015, 40(10): 1019-1024.
17.	张政波, 俞梦孙, 赵显亮, 等. 穿戴式、多参数协同监测系统设计. 航天医学与医学工程, 2008, 21(1): 66-69.
18.	曹德森, 李德玉, 张政波, 等. 随行生理监护系统设计及性能初步验证. 生物医学工程学杂志, 2019, 36(1): 121-130.
19.	Li Peiyao, Yang Zhicheng, Yan Wei, et al. MobiCardio: A clinical-grade mobile health system for cardiovascular disease management// 2019 IEEE International Conference on Healthcare Informatics (ICHI). Xi’an: IEEE, 2019: 1-6.
20.	Lan Ke, Liu Xiaoli, Xu Haoran, et al. DeePTOP: Personalized tachycardia onset prediction using bi-directional LSTM in wearable embedded systems// 2019 International Conference on Embedded Wireless Systems and Networks (EWSN). Beijing: ACM, 2019: 216-217.
21.	Zhang Yuezhou, Yang Zhicheng, Zhang Zhengbo, et al. Automated sleep period estimation in wearable multi-sensor systems// Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. Shenzhen: ACM, 2018: 305-306.
22.	尚文元. 采用CORTEX Metalyzer 3B-R3 及 3B 型心肺功能测试系统进行最大摄氧量测试的对比研究//第四届(2016)全国运动生理与生物化学学术会议——运动·体质·健康论文摘要汇编. 无锡: 中国体育科学学会, 2016: 96-97.
23.	乔德才, 焦蕾, 刘晓莉, 等. 可用于我国学生心肺功能评价的一种实验仪器的可行性研究. 北京体育大学学报, 2013, 36(7): 58-61.
24.	王成浩. 适用于普通人心肺功能测评的一种新型便携测试仪的可行性研究//2018年中国生理学会运动生理学专业委员会会议暨科技创新与运动生理学学术研讨会论文集. 新乡: 中国生理学会运动生理学专业委员会, 2018: 214-215.
25.	冯静. 极量与定量负荷试验中评价大学生心脏功能指标的筛选. 北京: 北京体育大学, 2012.
26.	王冬梅. 力竭运动后疲劳干预的研究现状分析. 当代体育科技, 2017, 7(36): 17, 19.
27.	彭莉. 置疑最大摄氧量——测试方法与判定标准. 体育科学, 2011, 31(7): 85-91.
28.	沈仲元, Shin L, 等. 调节呼吸频率对心率变异的影响. 实用心电学杂志, 2009, 18(5): 323-325.
29.	杜吟. 呼吸频率对心率变异性和情绪状态的影响. 北京: 首都体育学院, 2011.
30.	王兰爽, 吴艳霞, 王海民, 等. 腹式呼吸训练对心率变异性影响的研究. 中国康复医学杂志, 2006, 21(6): 542-544.
31.	孙聪聪, 张政波, 王步青, 等. 呼吸性窦性心律不齐定量分析研究进展. 生物医学工程学杂志, 2011, 28(6): 1227-1231.
32.	李新胜, 白净, 崔树起, 等. 心肺交互作用的心血管系统模型及仿真研究. 中国生物医学工程学报, 2003, 22(3): 241-249.
33.	邓威, 张德彬. 智能可穿戴设备军事应用与发展趋势. 国防科技, 2016, 37(1): 57-60.

1. 徐令仪, 汪长岭, 毛靖宁, 等. 可穿戴技术在生理信号监测中的应用和发展. 中国医疗设备, 2018, 33(3): 118-120, 135.
2. 韦哲, 薛翔, 吕克难. 可穿戴设备在医院诊疗中的应用研究进展. 中国医学装备, 2017, 14(8): 170-173.
3. 孙爱华, 孙咏晖, 齐芳. 可穿戴智能运动设备发展的局限性因素及对策研究. 山东体育科技, 2017, 39(3): 27-30.
4. 蒋小梅, 张俊然, 赵斌, 等. 可穿戴式设备分类及其相关技术进展. 生物医学工程学杂志, 2016, 33(1): 42-48.
5. Fernando S, Wang W, Kirenko I, et al. Feasibility of contactless pulse rate monitoring of neonates using google glass// MOBIHEALTH'15: Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare. London: ICST, 2015: 198-201.
6. Taffoni F, Rivera D, La Camera A, et al. A wearable system for real-time continuous monitoring of physical activity. J Healthc Eng, 2018, 2018: 1878354.
7. 潘良凤, 文艳红. 可穿戴设备在慢性病高危人群管理模式中的应用. 中国热带医学, 2016, 16(7): 685-687.
8. 张政波, 王卫东, 刘延武, 等. 穿戴式 COPD 肺康复装置及方法. 医疗卫生装备, 2008, 29(1): 14-15, 23.
9. McNaney R, Vines J, Roggen D, et al. Exploring the acceptability of Google Glass as an everyday assistive device for people with Parkinson's// Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Toronto: Association for Computing Machinery, 2014: 2551-2554.
10. 韩子鹏, 敖国政, 吉长东. 一种可穿戴快速运动强度检测方法研究. 中国体育科技, 2016, 52(6): 115-121.
11. 谢凌钦, 石萍, 蔡文杰. 可穿戴式智能设备关键技术及发展趋势. 生物医学工程与临床, 2015, 19(6): 635-640.
12. 杨小帆, 郭雅萍. 运动可穿戴设备的发展趋势研究. 福建体育科技, 2018, 37(3): 19-21, 39.
13. Liu Y, Zhu S H, Wang G H, et al. Validity and reliability of multiparameter physiological measurements recorded by the Equivital LifeMonitor during activities of various intensities. J Occup Environ Hyg, 2013, 10(2): 78-85.
14. Benfante A, Di Marco F, Terraneo S, et al. Dynamic hyperinflation during the 6-min walk test in severely asthmatic subjects. ERJ Open Res, 2018, 4(2). pii: 00143-2017.
15. Elliot C A, Hamlin M J, Lizamore C A. Validity and reliability of the Hexoskin^® wearable biometric vest during maximal aerobic power testing in elite cyclists. J Str Condit Res, 2017: 1-8.
16. Villar R, Beltrame T, Hughson R L. Validation of the Hexoskin wearable vest during lying, sitting, standing, and walking activities. Appl Physiol Nutr Metab, 2015, 40(10): 1019-1024.
17. 张政波, 俞梦孙, 赵显亮, 等. 穿戴式、多参数协同监测系统设计. 航天医学与医学工程, 2008, 21(1): 66-69.
18. 曹德森, 李德玉, 张政波, 等. 随行生理监护系统设计及性能初步验证. 生物医学工程学杂志, 2019, 36(1): 121-130.
19. Li Peiyao, Yang Zhicheng, Yan Wei, et al. MobiCardio: A clinical-grade mobile health system for cardiovascular disease management// 2019 IEEE International Conference on Healthcare Informatics (ICHI). Xi’an: IEEE, 2019: 1-6.
20. Lan Ke, Liu Xiaoli, Xu Haoran, et al. DeePTOP: Personalized tachycardia onset prediction using bi-directional LSTM in wearable embedded systems// 2019 International Conference on Embedded Wireless Systems and Networks (EWSN). Beijing: ACM, 2019: 216-217.
21. Zhang Yuezhou, Yang Zhicheng, Zhang Zhengbo, et al. Automated sleep period estimation in wearable multi-sensor systems// Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. Shenzhen: ACM, 2018: 305-306.
22. 尚文元. 采用CORTEX Metalyzer 3B-R3 及 3B 型心肺功能测试系统进行最大摄氧量测试的对比研究//第四届(2016)全国运动生理与生物化学学术会议——运动·体质·健康论文摘要汇编. 无锡: 中国体育科学学会, 2016: 96-97.
23. 乔德才, 焦蕾, 刘晓莉, 等. 可用于我国学生心肺功能评价的一种实验仪器的可行性研究. 北京体育大学学报, 2013, 36(7): 58-61.
24. 王成浩. 适用于普通人心肺功能测评的一种新型便携测试仪的可行性研究//2018年中国生理学会运动生理学专业委员会会议暨科技创新与运动生理学学术研讨会论文集. 新乡: 中国生理学会运动生理学专业委员会, 2018: 214-215.
25. 冯静. 极量与定量负荷试验中评价大学生心脏功能指标的筛选. 北京: 北京体育大学, 2012.
26. 王冬梅. 力竭运动后疲劳干预的研究现状分析. 当代体育科技, 2017, 7(36): 17, 19.
27. 彭莉. 置疑最大摄氧量——测试方法与判定标准. 体育科学, 2011, 31(7): 85-91.
28. 沈仲元, Shin L, 等. 调节呼吸频率对心率变异的影响. 实用心电学杂志, 2009, 18(5): 323-325.
29. 杜吟. 呼吸频率对心率变异性和情绪状态的影响. 北京: 首都体育学院, 2011.
30. 王兰爽, 吴艳霞, 王海民, 等. 腹式呼吸训练对心率变异性影响的研究. 中国康复医学杂志, 2006, 21(6): 542-544.
31. 孙聪聪, 张政波, 王步青, 等. 呼吸性窦性心律不齐定量分析研究进展. 生物医学工程学杂志, 2011, 28(6): 1227-1231.
32. 李新胜, 白净, 崔树起, 等. 心肺交互作用的心血管系统模型及仿真研究. 中国生物医学工程学报, 2003, 22(3): 241-249.
33. 邓威, 张德彬. 智能可穿戴设备军事应用与发展趋势. 国防科技, 2016, 37(1): 57-60.

Journal of Biomedical Engineering

Study on the accuracy of cardiopulmonary physiological measurements by a wearable physiological monitoring system under different activity conditions

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