基于光纖傳感的生理參數(shù)監(jiān)測系統(tǒng)研究
doi: 10.11999/JEIT170894
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中國科學(xué)院電子學(xué)研究所傳感技術(shù)國家重點(diǎn)實(shí)驗(yàn)室 ??北京 ??100080
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中國科學(xué)院大學(xué) ??北京 ??100049
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中國科學(xué)院信息工程研究所 ??北京 ??100093
Research of Physiological Monitoring System Based on Optical Fiber Sensor
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State Key Laboratory of Transducer Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100080, China
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2.
University of Chinese Academy of Sciences, Beijing 100049, China
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Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
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摘要: 常規(guī)生理參數(shù)監(jiān)測系統(tǒng)由于測量時接觸皮膚,因此舒適感差、個體依從性差。為解決上述問題,該文基于生理的微弱運(yùn)動可致光纖微彎曲變形進(jìn)而致光強(qiáng)度發(fā)生變化的原理,研制了新型的基于光纖傳感的生理參數(shù)監(jiān)測系統(tǒng)。該系統(tǒng)通過光探測器自適應(yīng)地檢測細(xì)小的光強(qiáng)變化獲得心沖擊圖(BCG)信號,利用信號處理算法獲取心率、呼吸率和體動等信息;把光纖嵌入床墊或坐墊設(shè)計(jì)為三明治結(jié)構(gòu),既保護(hù)了光纖又增強(qiáng)了系統(tǒng)的可靠性和穩(wěn)定性;采用蛇形返折走線將光纖均勻地分布在墊子中間,使系統(tǒng)具有高靈敏度。通過多家醫(yī)院臨床標(biāo)準(zhǔn)方法對比測試可得在95%的置信區(qū)間(±1.96SD)內(nèi)該系統(tǒng)心率均值誤差為–0.26±2.80次/min,與標(biāo)準(zhǔn)值之間的相關(guān)性為0.9984;呼吸率均值誤差為0.41±1.49次/min,與標(biāo)準(zhǔn)值之間的相關(guān)性為0.9971。實(shí)驗(yàn)表明,研制的系統(tǒng)可在零負(fù)荷的狀態(tài)下無感進(jìn)行生理參數(shù)測量,在健康醫(yī)療領(lǐng)域具有廣泛的應(yīng)用前景。Abstract: Conventionally, the physiological monitoring system obtains singnal by electrode or bandage which is connected with skins and has disadvantages such as: uncomfortable and bad compliance to users. In order to overcome those problems, a new physiological monitoring system, which is based on the principle that micro bend of optical-fiber induced by weak movement of physiology can change the light intensity to get BallistoCardioGram (BCG) signal, is developed. In such system, the respiration rate, heart rate and body movement are obtained by self-adaption detecting the tiny variation of light intensity. In order to protect fiber and enhance the stability and reliability of system, the fiber is embedded into mattress or cushion with a sandwich structure. Simultaneously, it makes the system have high sensitivity that the fiber is uniformly routed with serpentine-curve shape in the middle of mattress or cushion. It is illustrated by the measurement in several hospitals that the mean error of heart rate is –0.26±2.80 times/min within 95% the confidence interval (±1.96SD) with a correlation 0.9984 to the standard values. It is exhibited as well that the mean error respiration rate is 0.41±1.49 times/min within 95% the confidence interval (±1.96SD) with a correlation 0.9971 to the standard values. It is suggested that the developed system can be senselessly used under zero load and is promised in future.
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Key words:
- Fiber optic sensor /
- Ballistocardiogram /
- Heart rate /
- Respiration rate
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DOVSKY V, et al. Smart helmet: Wearable multichannel ECG and EEG[J]. IEEE Journal of Translational Engineering in Health and Medicine, 2016: 270011 doi: 10.1109/JTEHM.2016.2609927VROSENBERG W V, CHANWIMALUEANG T, GOVER doi: 10.1109/JTEHM.2016.2609927 HASSAN M A, MALIK A S, FOFI D, et al. Heart rate estimation using facial video: A review[J]. Biomedical Signal Processing and Control, 2017, 38(8): 346–360 doi: 10.1016/j.bspc.2017.07.004 LIU M, JIANG F, JIANG H, et al. Low-power, noninvasive measurement system for wearable ballistocardiography in sitting and standing positions[J]. Computers in Industry, 2017, 91(10): 24–32 doi: 10.1016/j.compind.2017.05.005 FAUSTMAN D L. Methods of treating and diagnosing disease using biomarkers for bcg therapy: WIPO, WO2017059132A1[P]. 2017-04-06. PETRINI V P, MATTIA V D M D, LEO A D L D, et al. Contactless Monitoring of Respiratory Activity Using Electromagnetic Waves for Ambient Assisted Living Framework: Feasibility Study and Prototype Realization[M]. London, UK, The Institution of Engineering and Technology, 2017: 30–40. CHEN Z, LAU D, TEO J T, et al. Simultaneous measurement of breathing rate and heart rate using a microbend multimode fiber optic sensor[J]. Journal of Biomedical Optics, 2014, 19(5): 057001 doi: 10.1117/1.JBO.19.5.057001 YANG X, CHEN Z, ELVIN C S M, et al. Textile fiber optic microbend sensor used for heartbeat and respiration monitoring[J]. Sensors Journal IEEE, 2015, 15(2): 757–761 doi: 10.1109/JSEN.2014.2353640 DEEPU C J, CHEN Z, JU T T, et al. A smart cushion for real-time heart rate monitoring[C]. 2012 IEEE Biomedical Circuits and Systems Conference, Hsinchu, China, 2012: 53–56. ZHU Y, ZHANG H, JAYACHANDRAN M, et al. Ballistocardiography with fiber optic sensor in headrest position: A feasibility study and a new processing algorithm[C]. Engineering in Medicine and Biology Society (EMBC), 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 2013: 5203–5206. CHEN Zhihao, TEO J T, NG S H, et al. Monitoring respiration and cardiac activity during sleep using microbend fiber sensor: A clinical study and new algorithm[C]. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, USA, 2014: 5377–5380. NI Hongbo, HE Mingjie, XU Guxing, et al. Extracting heartbeat intervals using self-adaptive method based on ballistocardiography(BCG)[C]. International Conference on Smart Homes and Health Telematics, Paris, France, 2017: 37–47. 肖玲, 李仁發(fā), 羅娟. 體域網(wǎng)中一種基于壓縮感知的人體動作識別方法[J]. 電子與信息學(xué)報, 2013, 35(1): 119–125 doi: 10.3724/SP.J.1146.2012.00936XIAO Ling, LI Renfa, and LUO Juan. Recognition of human activity based on compressed sensing in body sensor networks[J]. Journal of Electronics&Information Technology, 2013, 35(1): 119–125 doi: 10.3724/SP.J.1146.2012.00936 高發(fā)榮, 王佳佳, 席旭剛, 等. 基于粒子群優(yōu)化-支持向量機(jī)方法的下肢肌電信號步態(tài)識別[J]. 電子與信息學(xué)報, 2015, 37(5): 1154–1159 doi: 10.11999/JEIT141083GAO Farong, WANG Jiajia, XI Xugang, et al. Gait recognition for lower extremity electromyographic signals based on PSO-SVM method[J]. Journal of Electronics&Information Technology, 2015, 37(5): 1154–1159 doi: 10.11999/JEIT141083 ZHAO W, NI H, ZHOU X, et al. Identifying sleep apnea syndrome using heart rate and breathing effort variation analysis based on ballistocardiography[C]. Engineering in Medicine and Biology Society, Milan, Italia, 2015: 4536–4539. JOSE S K, SHAMBHARKAR C M, and CHUNKATH J. HRV analysis using ballistocardiogram with LabVIEW[C]. 2015 International Conference on Computing and Communications Technologies, Chennai, India, 2015: 128–132. ROSALES L, SU B Y, SKUBIC M, et al. Heart rate monitoring using hydraulic bed sensor ballistocardiogram[J]. Journal of Ambient Intelligence&Smart Environments, 2017, 9(2): 193–207 doi: 10.3233/AIS-170423 SHIN J H, HWANG S H, CHANG M H, et al. Heart rate variability analysis using a ballistocardiogram during Valsalva manoeuvre and post exercise[J]. Physiological Measurement, 2011, 32(8): 1239–1264 doi: 10.1088/0967-3334/32/8/015 NISHYAMA M, MIYAMOTO M, and WATANABE K. Respiration and body movement analysis during sleep in bed using hetero-core fiber optic pressure sensors without constraint to human activity[J]. Journal of Biomedical Optics, 2011, 16(1): 017002 doi: 10.1117/1.3528008 -