期刊文献+

腕戴式低功耗无线心率监测装置的研制 被引量:18

Low power,wireless,wrist-worn device for HR monitoring based on double channels of pulse sensing
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摘要 研制新型的基于双通道脉搏传感的腕戴式无线低功耗心率实时监测装置.根据人体腕部生理解剖的特点,提出桡动脉、尺动脉双通道脉搏波及差分信号同步检测的新方法.研制了集传感器、调理电路、微处理器、通讯、自动增益算法和心率算法等软、硬件部件于一体的小型化装置.电路系统测试表明:在待机和工作模式下的平均工作电流分别约为10和300μA;对10名男性在休憩状态下的心率进行3h的连续动态监测,将测试结果与标准动态心电图记录的数据进行比较,结果表明,心率测量的算术平均误差约为0.3BPM. A new low‐power wrist‐worn miniature device used for real‐time wireless heart rate (HR) monitoring was presented . A novel pulse signal detection method based on double channels of pulse sensing of the radial artery and ulnar artery as well as their differential signal was proposed .A miniature device consisting of sensors ,signal condition system was fabricated .The micro‐controller is responsible for power administration ,and calculation of auto gain control algorithm and heart rate algorithms .The average currents are about 10μA and 300μA in standby and active modes ,respectively .Ten male subjects were selected to test the performance of the device through a three‐hour continuous test in their resting condition with the reference of a Holter monitor .The HR of the device was compared with the HR from the ECG signal recorded by the Holter monitor .The experimental results indicate that the arithmetical average error is about 0 .3 BPM .
出处 《浙江大学学报(工学版)》 EI CAS CSCD 北大核心 2015年第4期798-805,共8页 Journal of Zhejiang University:Engineering Science
基金 "十一五"全军重大专项资助项目(W08Z008) 国家"863"高科技支撑计划资助项目(2012BAH06F00) 国家科技支撑计划课题(2012BAI14B06)
关键词 心率监测 腕戴式 无线监测 双通道 低功耗 heart-rate monitoring wrist-worn wireless monitoring double channels low-power con-sumption
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参考文献23

  • 1GABRIEI. H. Reappraisal of the importance of heart rate as a risk factor for cardiovascular morbidity and mortality ~J]. Clinical Therapeutics, 1997, 19(1) : 39 - 52,.
  • 2FOX K, BORERJ S, CAMM A J, et al. Resting heart rate in cardiovascular disease [J~. Journal of the Ameri- can College of Cardiology, 2007, 50 (9) : 823 - 830.
  • 3CHRISTINE P G,LAURE J, ATHANASE B. Hearl rate as a risk factor for cardiovascular disease [J]. Pro- gress in Cardiovascular Diseases, 2009, 52(1) : 6 10.
  • 4PAOLO P. Elevated heart rate: a "new" cardiovascular risk factor [-J ]. Progress in Cardiovascular Diseases, 2009, 52(1): 1-5.
  • 5FOSBOL E L, SEIBAEK M, BENTE B, et al. Long- term prognostic importance of resting heart rate in pa- tients with left ventricular dysfunction in connection with either heart failure or myocardial infarction: theDIAMOND study l-J]. International Journal of Cardiolo- gy, 2010, 140(3): 279-286.
  • 6LIPINSKI M J, VETROVEC G W, GORELIK D, et al. The importance of heart rate recovery in patients with heart failure or left ventricular systolic dysfunction [J]. Journal of Cardiac Failure, 2005, 11(8) : 624 - 630.
  • 7MADDOX T M, ROSS C, MASOUDIET F A, et al. The prognostic importance of abnormal heart rate recov- ery and chronotropic response among exercise treadmill test patients EJ]. American Heart Journal, 2008, 156 (4) : 736 - 744.
  • 8GROFF C P, MULVANEY P L. Vital sign monitoring system of e. g. body temperature of in-patient, has CPU which statistically analyzes detected vital signs data and determines abnormal vital sign condition from normal condition: US6102856-A [P]. 2000-08-15.
  • 9ANH D, DANIEL T, LI C, et al. A wearable device for physical activity monitoring with built in heart rate variability [C]// 3rd International Conference on Bioin- formatics and Biomedical Engineering. Beijing: Is. n. ], 2009 : 1 - 4.
  • 10HASHEM M M A, SHAMS R, KADER M A, et al. Design and development of a heart rate measuring de- vice using fingertip [C] ff 2010 International Confer- ence on Computer and Communication Engineering (IC- CCE). Kuala Lumpur: Is. n.], 2010: 1-5.

二级参考文献12

  • 1Tsien CL and Fackler JC. Poor prognosis for existing monitors in the intensive care unit[J]. Crit Care Med, 1997,25(4):614-619.
  • 2Kohler BU, Hennig C and Orglmeister R. The principles of software QRS detection[J]. IEEE Eng. Med. Biol. Mag. 2002,21:42-57.
  • 3Jakob S, Korhonen I, Ruokonen E, et al. Detection of artifacts in monitored trends in intensive care [J]. Comput. Methods Programs Biomed, 2000,63:203-209.
  • 4Tsien C L Kohans I S and Mclntosh N. Building ICU artifact detection models with more data in less time [M]. Proc. AMIA Symp. 2001,706-710.
  • 5Sittig D F and Factor M. Physiologic trend detection and artifact rejection: a parallel implementation of a multi-state Kalman faltering algorithm[J]. Comput. Methods Programs Biomed. 1990, 31:1-10.
  • 6Allen J and Murray A. Assessing ECG signal quality on a coronary care unit[J]. Physiol. Meas. 1996,17:249-58.
  • 7Zong W, Moody GB and Mark RG. Reduction of false arterial blood pressure alarms using signal quality assessment and relationships between the electrocardiogram and arterial blood pressure [J]. Med. Biol. Eng. Comput. 2004,42:698-706.
  • 8Saeed M, Lieu C, Raber G, et al. MIMIC Ⅱ: a massive temporal ICU patient database to support research in intelligent patient monitoring [J]. Comput in Cardiol, 2002,29:641-644.
  • 9Hamilton PS and Tompkins WJ. Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database [J]. IEEE Trans on BME, 1986,33(12):1157-1165.
  • 10Zong W, Moody GB and Jiang D. A robust open-source algorithm to detect onset and duration of QRS complexes [J]. Comput in Cardiol, 2003,30:737-740.

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