Decomposition of the Cardiac and Respiratory Components from Impedance Pneumography Signals

被引:13
|
作者
Mlynczak, Marcel [1 ]
Cybulski, Gerard [1 ,2 ]
机构
[1] Warsaw Univ Technol, Fac Mechatron, Inst Metrol & Biomed Engn, Boboli 8, PL-02525 Warsaw, Poland
[2] Polish Acad Sci, Mossakowski Med Res Ctr, Dept Appl Physiol, Pawinskiego 5, PL-02106 Warsaw, Poland
来源
PROCEEDINGS OF THE 10TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 4: BIOSIGNALS | 2017年
关键词
Ambulatory Monitoring; Impedance Pneumography; Cardiorespiratory Activity; Decomposition; CARDIOGENIC OSCILLATIONS; SPLINE FUNCTIONS;
D O I
10.5220/0006107200260033
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Impedance pneumography (IP) measures changes of thoracic electrical impedance connected with change of the air volume in the lungs. The electrode configuration used in IP applications causes that electrical heart activity is visible in the IP signals. The aim of this paper is to assess the opportunity to decompose both respiratory and cardiac components and its quality using various methods. Ten students performed static breathing sequences, intended both for calibration and testing. Our prototype, Pneumonitor 2, and the reference pneumotachometer, were used. The accuracy of calculating tidal volume and heart rate, the calibration procedure and the time of analysis, were considered. Mean 86.5% accuracy of tidal volume calculating and only 2.7% error of heart rate estimation were obtained using moving average smoothing filters, for simple short recording of free breathing calibration procedure, in three body positions. More sophisticated adaptive filtering also provided good accuracy, however the processing time was 100-times higher, compared to simple methods. It seems impedance pneumography, without ECG, could be enough for measuring basic cardiorespiratory activity, particularly during ambulatory recordings, in which the least disturbing equipment is desirable.
引用
收藏
页码:26 / 33
页数:8
相关论文
共 50 条
  • [31] Bio-impedance signal decomposer (BISD) as an adaptive signal model based separator of cardiac and respiratory components
    Krivoshei, Andrei
    Kukk, Vello
    Birjukov, Andrei
    13TH INTERNATIONAL CONFERENCE ON ELECTRICAL BIOIMPEDANCE AND THE 8TH CONFERENCE ON ELECTRICAL IMPEDANCE TOMOGRAPHY 2007, 2007, 17 : 209 - +
  • [32] Towards Estimation of Tidal Volume and Respiratory Timings via Wearable-Patch-Based Impedance Pneumography in Ambulatory Settings
    Berkebile, John A.
    Mabrouk, Samer A.
    Ganti, Venu G.
    Srivatsa, Adith, V
    Sanchez-Perez, Jesus Antonio
    Inan, Omer T.
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2022, 69 (06) : 1909 - 1919
  • [33] SPECTRUM-ADAPTED EXCITATION SIGNALS IN MEASURING RESPIRATORY IMPEDANCE
    FARRE, R
    NAVAJAS, D
    ROTGER, MM
    BULLETIN EUROPEEN DE PHYSIOPATHOLOGIE RESPIRATOIRE-CLINICAL RESPIRATORY PHYSIOLOGY, 1987, 23 : S324 - S324
  • [34] Apnea duration: Respiratory Inductance Plethysmography (RIP) and Transthoracic Impedance (TTI) Pneumography vs. Polysomnography (PSG) † 1791
    Michael J Corwin
    D E Weese-Mayer
    M R Neuman
    D Crowell
    S Davidson Ward
    L Brooks
    C E Hunt
    G Lister
    M Willinger
    Pediatric Research, 1997, 41 (Suppl 4) : 301 - 301
  • [35] Cardiac interference in myographic signals from different respiratory muscles and levels of activity
    Mañanas, MA
    Romero, S
    Topor, ZL
    Bruce, EN
    Houtz, P
    Caminal, P
    PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE, 2001, 23 : 1115 - 1118
  • [36] Decomposition Scheme for Wideband Signals Containing Deterministic Components and Stochastic Noise Components
    Jin Z.
    Zhang H.
    Shi F.
    Liu S.
    Fang C.
    Liu J.
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2019, 43 (04): : 70 - 78
  • [37] RESOLUTION OF BALLISTOGRAPHIC RECORDS INTO CARDIAC AND RESPIRATORY COMPONENTS
    RAUTAHAR.PM
    JOSENHAN.WT
    CANADIAN JOURNAL OF PHYSIOLOGY AND PHARMACOLOGY, 1966, 44 (05) : 691 - &
  • [38] Empirical Modal Decomposition applied to cardiac signals analysis
    Beya, O.
    Jalil, B.
    Fauvet, E.
    Laligant, O.
    WAVELET APPLICATIONS IN INDUSTRIAL PROCESSING VII, 2010, 7535
  • [39] Morphological modeling of cardiac signals based on signal decomposition
    Roonizi, Ebadollah Kheirati
    Sameni, Reza
    COMPUTERS IN BIOLOGY AND MEDICINE, 2013, 43 (10) : 1453 - 1461
  • [40] Flow Parameters Derived from Impedance Pneumography after Nonlinear Calibration based on Neural Networks
    Mlynczak, Marcel
    Cybulski, Gerard
    PROCEEDINGS OF THE 10TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 4: BIOSIGNALS, 2017, : 70 - 77