Journal of Medical Systems

, 41:20 | Cite as

A Novel Nonlinear Mathematical Model of Thoracic Wall Mechanics During Cardiopulmonary Resuscitation Based on a Porcine Model of Cardiac Arrest

  • Ali JalaliEmail author
  • Allan F. Simpao
  • Vinay M. Nadkarni
  • Robert A. Berg
  • C. Nataraj
Image & Signal Processing
Part of the following topical collections:
  1. Image & Signal Processing


Cardiopulmonary resuscitation (CPR) is used widely to rescue cardiac arrest patients, yet some physiological aspects of the procedure remain poorly understood. We conducted this study to characterize the dynamic mechanical properties of the thorax during CPR in a swine model. This is an important step toward determining optimal CPR chest compression mechanics with the goals of improving the fidelity of CPR simulation manikins and ideally chest compression delivery in real-life resuscitations. This paper presents a novel nonlinear model of the thorax that captures the complex behavior of the chest during CPR. The proposed model consists of nonlinear elasticity and damping properties along with frequency dependent hysteresis. An optimization technique was used to estimate the model coefficients for force-compression using data collected from experiments conducted on swine. To track clinically relevant, time-dependent changes of the chest’s properties, the data was divided into two time periods, from 1 to 10 min (early) and greater than 10 min (late) after starting CPR. The results showed excellent agreement between the actual and the estimated forces, and energy dissipation due to viscous damping in the late stages of CPR was higher when compared to the earlier stages. These findings provide insight into improving chest compression mechanics during CPR, and may provide the basis for developing CPR simulation manikins that more accurately represent the complex real world changes that occur in the chest during CPR.


Cardiopulmonary resuscitation Chest compression Biomechanical modeling Hysteresis Parameter estimation Chest wall properties 



The research reported in this paper was supported by a grant from the National Institutes of Health (No. 1 R01 NS 72338 01A1). The authors express their gratitude to Dr. Robert Sutton, Dr. Matthew Maltese, Mrs. Dana Niles, and Dr. George Bratinov at CHOP for their significant contributions.

Compliance with Ethical Standards

Conflict of Interest

Ali Jalali, PhD declares that he has no conflict of interest. Allan F. Simpao, MD, MBI declares that he has no conflict of interest. Vinay M. Nadkarni, MD declares that he has no conflict of interest. Robert A. Berg, MD declares that he has no conflict of interest. C. Nataraj, PhD declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Ali Jalali
    • 1
    • 3
    Email author
  • Allan F. Simpao
    • 2
  • Vinay M. Nadkarni
    • 2
  • Robert A. Berg
    • 2
  • C. Nataraj
    • 3
  1. 1.Department of Anesthesiology and Critical Care MedicineThe Children’s Hospital of PhiladelphiaPhiladelphiaUSA
  2. 2.Department of Anesthesiology and Critical Care MedicinePerelman School of Medicine at the University of Pennsylvania and The Children’s Hospital of PhiladelphiaPhiladelphiaUSA
  3. 3.Villanova Center for Analytics of Dynamic Systems (VCADS)Villanova UniversityVillanovaUSA

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