Improved Auscultation with a Stethoscope Using Model Inversion for Unknown Input Estimation

被引:0
|
作者
Nelson, Garrett [1 ]
Rajamani, Rajesh [2 ]
机构
[1] Sandia Natl Labs, Albuquerque, NM 87111 USA
[2] Univ Minnesota, Dept Mech Engn, 111 Church St SE, Minneapolis, MN 55455 USA
基金
美国能源部;
关键词
MULTIVARIABLE LINEAR-SYSTEMS; DYNAMICAL-SYSTEMS; INVERTIBILITY;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a method for improved auscultation with an electronic stethoscope by estimating and removing the effects of unknown disturbance inputs. By replacing the single transducer in a stethoscope with a dual piezo transducer assembly, it is shown that an inverse dynamic mapping can be used to relate the two measured signals to original directional inputs acting on the stethoscope. Specifically, model inversion is used to estimate and remove physician handling noise from chest sound signals. An experimental test platform which uses a vibration shaker to simulate the desired auscultation signal is used to experimentally demonstrate the feasibility of the dual-piezo stethoscope approach in improving auscultation.
引用
收藏
页码:3970 / 3975
页数:6
相关论文
共 50 条
  • [21] Robust unknown input observer design for state estimation and fault detection using linear parameter varying model
    Li, Shanzhi
    Wang, Haoping
    Aitouche, Abdel
    Tian, Yang
    Christov, Nicolai
    13TH EUROPEAN WORKSHOP ON ADVANCED CONTROL AND DIAGNOSIS (ACD 2016), 2017, 783
  • [22] UNKNOWN INPUT AND STATE ESTIMATION FOR UNOBSERVABLE SYSTEMS
    Bejarano, Francisco J.
    Fridman, Leonid
    Poznyak, Alexander
    SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2009, 48 (02) : 1155 - 1178
  • [23] State and Input Estimation of an Anaerobic Digestion Reactor using a Continuous-discrete Unknown Input Observer
    Rocha-Cozatl, E.
    Sbarciog, M.
    Dewasme, L.
    Moreno, J. A.
    Vande Wouwer, A.
    IFAC PAPERSONLINE, 2015, 48 (08): : 129 - 134
  • [24] State Estimation with Unknown Input Signal.
    Engell, S.
    Konik, D.
    Automatisierungstechnik, 1986, 34 (01): : 38 - 42
  • [25] An Adaptive Control Framework for Unknown Input Estimation
    Griffith, Tristan D.
    Balas, Mark J.
    PROCEEDINGS OF ASME 2021 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION (IMECE2021), VOL 7A, 2021,
  • [26] On Joint Unknown Input and Sliding Mode Estimation
    Barboni, Angelo
    Yang, Guitao
    Rezaee, Hamed
    Parisini, Thomas
    2022 EUROPEAN CONTROL CONFERENCE (ECC), 2022, : 969 - 974
  • [27] Curvature and Force Estimation for a Soft Finger using an EKF with Unknown Input Optimization
    Loo, Junn Yong
    Ding, Ze Yang
    Davies, Evan
    Nurzaman, Surya Girinatha
    Tan, Chee Pin
    IFAC PAPERSONLINE, 2020, 53 (02): : 8506 - 8512
  • [28] Unknown Input and Sensor Fault Estimation Using Sliding-Mode Observers
    Kalsi, Karanjit
    Hui, Stefen
    Zak, Stanislaw H.
    2011 AMERICAN CONTROL CONFERENCE, 2011, : 1364 - 1369
  • [29] Simultaneous Estimation of Hidden State and Unknown Input Using Expectation Maximization Algorithm
    Khan, Mohammad Aminul Islam
    Imtiaz, Syed Ahmad
    Khan, Faisal
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, 58 (26) : 11553 - 11565
  • [30] Dynamic Generator State Estimation using PMU Measurements for Unknown Generator Input
    Joseph, Thomas
    Tyagi, Barjeev
    Kumar, Vishal
    2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2018,