A RESPIRATORY MECHANICAL PARAMETERS ESTIMATION TECHNOLOGY BASED ON EXTENDED LEAST SQUARES

被引:2
|
作者
Shi, Yan [1 ,2 ]
Niu, Jinglong [1 ]
Cai, Maolin [1 ]
Xu, Weiqing [1 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Zhejiang Univ, State Key Lab Fluid Power Transmiss & Control, Hangzhou 310058, Zhejiang, Peoples R China
关键词
Respiratory mechanical parameters; simulation; experimental study; extended least-squares; estimation; MODEL;
D O I
10.1142/S0219519416500287
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Respiratory mechanical parameters of ventilated patients are usually referred in the respiratory diagnosis and treatment. However, the effectiveness of the modern estimation methods is limited. To estimate the overall breathing resistance, overall respiratory compliance, and residual volume simultaneously, a new mathematical model of mechanical ventilation system was proposed. Furthermore, to improve the estimation accuracy, the noise model of mechanical ventilation system was taken into consideration. Based on the mathematical model, a respiratory mechanical parameters estimation method based on extended least squares (ELS) algorithm was derived. Finally, to test the respiratory mechanical parameters estimation method, it was studied experimentally and numerically, and it was approved that the proposed method is effective to estimate the three respiratory mechanical parameters simultaneously and precisely. The estimated values of the parameters can be adopted in the clinical practice. The study provides a new method to estimate respiratory mechanical parameters.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Online Estimation of Vehicle Driving Resistance Parameters with Recursive Least Squares and Recursive Total Least Squares
    Rhode, Stephan
    Gauterin, Frank
    2013 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2013, : 269 - 276
  • [22] WAMS based Dynamic States and Parameters Estimation using Least Squares Estimation and Unscented Kalman Filter
    Jha, Rajiv
    Senroy, Nilanjan
    2017 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 2017, : 725 - 730
  • [23] Recursive-Least-Squares-Based Real-Time Estimation of Supercapacitor Parameters
    Reichbach, Noam
    Kuperman, Alon
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2016, 31 (02) : 810 - 812
  • [24] Frequency-domain-based least-squares estimation of multifrequency signal parameters
    Carbone, P
    Nunzi, E
    Petri, D
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2000, 49 (03) : 555 - 558
  • [25] Estimation of parameters in a generalized GMANOVA model based on an outer product analogy and least squares
    Hu, Jianhua
    Liu, Fuxiang
    You, Jinhong
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2012, 142 (07) : 2017 - 2031
  • [26] Frequency-domain based least-squares estimation of multifrequency signal parameters
    Carbone, P
    Nunzi, E
    Petri, D
    IMTC/99: PROCEEDINGS OF THE 16TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS. 1-3, 1999, : 917 - 921
  • [27] Least Squares Estimation of Dynamic System Parameters using LabVIEW
    Turner, Jonathan G.
    Samanta, Biswanath
    2013 PROCEEDINGS OF IEEE SOUTHEASTCON, 2013,
  • [28] Least squares estimation of Doppler and polarimetric parameters for weather targets
    del Rio, V. Santalla
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2007, 45 (11): : 3760 - 3772
  • [29] Least Squares Estimation Method for Polarization Parameters of Radar Signals
    Zeng, Yonghu
    Dai, Huanyao
    Han, Hui
    Xu, Xiong
    Liu, Wenzhao
    2017 18TH INTERNATIONAL RADAR SYMPOSIUM (IRS), 2017,
  • [30] Estimation of parameters of the Gompertz distribution using the least squares method
    Wu, JW
    Hung, WL
    Tsai, CH
    APPLIED MATHEMATICS AND COMPUTATION, 2004, 158 (01) : 133 - 147