The cardiac systolic mechanical axis: Optimizing multi-axial cardiac vibrations by projecting along a physiological reference frame

Abstract Multi-axial accelerometers are invaluable for the analysis of anisotropic cardiac vibrations during the first-heart-sound (S1). However, most studies simply consider the multi-axial accelerometer components independently along the different anatomical axes and rarely properly account for this anisotropy. The objective of this study was to evaluate a simple method, intended for chronically implanted medical devices, to identify a physiological reference frame maximizing S1 vibrations in the transverse plane. We attached a tri-axial accelerometer on the tip of a cardiac pacing lead to the chest of 10 human volunteers and implanted it subcutaneously in one pig. The volunteers and pig underwent separate experimental protocols capturing a wide range of conditions. The acceleration components of the tri-axial accelerometer were projected along the identified reference frame and a frame perpendicular to this. These were denoted the cardiac systolic mechanical axis and perpendicular axis, respectively. Results showed that projection along the mechanical axis tended to maximize signal-to-noise ratio and minimize cycle-to-cycle morphological variability. Significant differences were also observed between the mechanical and perpendicular axes projections, demonstrating sensibility to orientation. Along the mechanical axis, signal-to-noise-ratio was up to 21.72 dB greater, and cycle-to-cycle variability was up to 7.47 dB smaller, than along the perpendicular axis. The transverse plane angle defining the reference frame was relatively similar throughout the volunteers (28.5–44.0° from the medial-lateral axis), demonstrating inter-subject homogeneity. Also, it varied little across the different conditions (15.6° mean standard deviation across the volunteers), demonstrating stability. In conclusion, the proposed algorithm optimized signal quality at low computational cost.

[1]  Pierre-Yves Joubert,et al.  Cardiac Hemodynamic Monitoring in the Subcutaneous Space : A pre-clinical proof-of-concept , 2018, 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[2]  Kouhyar Tavakolian,et al.  Myocardial contractility: A seismocardiography approach , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  J. Cohn,et al.  Cardiac remodeling--concepts and clinical implications: a consensus paper from an international forum on cardiac remodeling. Behalf of an International Forum on Cardiac Remodeling. , 2000, Journal of the American College of Cardiology.

[4]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[5]  Mireia Calvo,et al.  Evaluation of Three-Dimensional Accelerometers for the Study of Left Ventricular Contractility , 2018, 2018 Computing in Cardiology Conference (CinC).

[6]  C. Menon,et al.  Precordial acceleration signals improve the performance of diastolic timed vibrations. , 2013, Medical engineering & physics.

[7]  M. O. Poliac,et al.  Seismocardiography: waveform identification and noise analysis , 1991, [1991] Proceedings Computers in Cardiology.

[8]  F. Lombardi,et al.  Postinfarct Left Ventricular Remodelling: A Prevailing Cause of Heart Failure , 2016, Cardiology research and practice.

[9]  Bozena Kaminska,et al.  Estimation of hemodynamic parameters from seismocardiogram , 2010, 2010 Computing in Cardiology.

[10]  Xavier Neyt,et al.  Three dimensional ballisto- and seismo-cardiography: HIJ wave amplitudes are poorly correlated to maximal systolic force vector , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  John M. Zanetti,et al.  Seismocardiography: a technique for recording precordial acceleration , 1991, [1991] Computer-Based Medical Systems@m_Proceedings of the Fourth Annual IEEE Symposium.

[12]  R. Shave,et al.  Exercise-Induced Cardiac Remodeling: Lessons from Humans, Horses, and Dogs , 2017, Veterinary sciences.

[13]  P H Gregson,et al.  Sternal acceleration ballistocardiography and arterial pressure wave analysis to determine stroke volume. , 1999, Clinical and investigative medicine. Medecine clinique et experimentale.

[14]  Andreas Espinoza,et al.  Assessment of 3D motion increases the applicability of accelerometers for monitoring left ventricular function. , 2015, Interactive cardiovascular and thoracic surgery.

[15]  E. Fosse,et al.  Detection of myocardial ischaemia by epicardial accelerometers in the pig. , 2009, British journal of anaesthesia.

[16]  B. Hill,et al.  Metabolic Mechanisms of Exercise-Induced Cardiac Remodeling , 2018, Front. Cardiovasc. Med..

[17]  G. Parati,et al.  Wearable Seismocardiography , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  Lars Hoff,et al.  Feasibility of a three-axis epicardial accelerometer in detecting myocardial ischemia in cardiac surgical patients. , 2008, The Journal of thoracic and cardiovascular surgery.

[19]  Lotfi Senhadji,et al.  Endocardial acceleration (sonR) vs. ultrasound-derived time intervals in recipients of cardiac resynchronization therapy systems. , 2011, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[20]  Bozena Kaminska,et al.  Infrasonic cardiac signals: Complementary windows to cardiovascular dynamics , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[21]  Kouhyar Tavakolian,et al.  Ballistocardiography and Seismocardiography: A Review of Recent Advances , 2015, IEEE Journal of Biomedical and Health Informatics.

[22]  S. Cappelli,et al.  The Entirely Subcutaneous Defibrillator (S-Icd): State of the Art and Selection of the Ideal Candidate , 2014, Current cardiology reviews.

[23]  Kasper Sørensen,et al.  Definition of Fiducial Points in the Normal Seismocardiogram , 2018, Scientific Reports.

[24]  Fjodors Tjulkins,et al.  Continuous monitoring of cardiac function by 3-dimensional accelerometers in a closed-chest pig model. , 2015, Interactive cardiovascular and thoracic surgery.

[25]  A. Elliott,et al.  Determination of left ventricular long‐axis orientation using MRI: changes during the respiratory and cardiac cycles in normal and diseased subjects , 2005, Clinical physiology and functional imaging.

[26]  A. Baggish,et al.  Exercise-induced cardiac remodeling. , 2012, Progress in cardiovascular diseases.

[27]  K. Radermacher,et al.  Simplified detection of myocardial ischemia by seismocardiography , 2013, Herz.

[28]  R. Tuttle,et al.  Dobutamine: DEVELOPMENT OF A NEW CATECHOLAMINE TO SELECTIVELY INCREASE CARDIAC CONTRACTILITY , 1975, Circulation research.

[29]  S. Paiva,et al.  Cardiac Remodeling: Concepts, Clinical Impact, Pathophysiological Mechanisms and Pharmacologic Treatment , 2016, Arquivos brasileiros de cardiologia.

[30]  Omer T. Inan,et al.  Automatic Detection of Seismocardiogram Sensor Misplacement for Robust Pre-Ejection Period Estimation in Unsupervised Settings , 2017, IEEE Sensors Journal.

[31]  Raimo Sepponen,et al.  Unified frame of reference improves inter-subject variability of seismocardiograms , 2015, BioMedical Engineering OnLine.