Annals of Biomedical Engineering

, Volume 45, Issue 6, pp 1520–1533 | Cite as

Acoustic Emission Signatures During Failure of Vertebra and Long Bone

  • Brian D. Goodwin
  • Frank A. Pintar
  • Narayan Yoganandan


Clinical classification of an injury has traditionally involved medical imaging, patient history, and physical examination. The pathogenesis or process of injury has been viewed as a crucial component to estimating fracture stability and direct treatment. However, injury classification systems generally exclude pathogenesis and injury mechanisms because these components are often difficult to elucidate. Furthermore, the development of bone damage relative to the mechanical response is difficult to quantify, which limits the ability to define injury and develop injury criteria. Past advents of new knowledge about the mechanisms and progression of fracture have refined safety standards and engineering design for limiting injury. Post-hoc methodologies for identifying and classifying injuries for post-mortem human surrogate (PMHS) research are well established. Though bone fractures can be classified post hoc, questions remain. Surface acoustic sensing (SAS) is an effective approach to augment PMHS experimentation. The objective was to develop and validate an acoustic-emission-based method to characterize bone fractures during injurious loading conditions using acoustic emissions (AEs) in two bone types: vertebral body (VB) and long bone (LB). The newly developed method incorporated the Stockwell transform to estimate the relative energy release rate (RERR) from bone fracture using acoustic signal processing. Fractures were characterized through AE burst durations and frequency content. Results indicated that VB fractures from compression are prolonged processes compared to LB fracture, which was staccato in nature. Significant (p < 0.01) differences between burst duration and frequency content were identified between the two bone types.


Biomechanics Post-mortem human surrogate Fracture detection Fracture timing Fracture mechanics Vertebral body 



This research was supported in part by the Biomechanics Product Team led by the Johns Hopkins Applied Physics Laboratory for the WIAMan Project under Contract Number N00024-13-D-6400, U.S. Army Research, Development and Engineering Command, and the Department of Veterans Affairs Medical Research and by the Cooperative Agreement: W81XWH-12-2-0041. Experimental data were obtained under Office of Naval Research N00421-10-C-0049 and LB experimental data were obtained using MCW Department of Neurosurgery funds. The MCW authors are part time employees of the Zablocki VA Medical Center (Milwauke, WI). Any views expressed are those of the authors and do not necessarily represent the funding organizations.


  1. 1.
    Agcaoglu, S., and O. Akkus. Acoustic emission based monitoring of the microdamage evolution during fatigue of human cortical bone. J. Biomech. Eng. 135:81005, 2013.CrossRefPubMedGoogle Scholar
  2. 2.
    Aggelis, D. G., M. Strantza, O. Louis, F. Boulpaep, D. Polyzos, and D. van Hemelrijck. Fracture of human femur tissue monitored by acoustic emission sensors. Sensors (Switzerland) 15:5803–5819, 2015.CrossRefGoogle Scholar
  3. 3.
    Allsop, D. L., C. Y. Warner, M. G. Wille, D. C. Schneider, and A. M. Nahum. Facial impact response—a comparison of the {Hybrid} {III} dummy and human cadaver. SAE Pap. No.881719, Proc. 32th Stapp Car Crash Conf. 781–797, 1988. doi: 10.4271/881719.
  4. 4.
    Arun, M. W. J., N. Yoganandan, B. D. Stemper, and F. A. Pintar. A methodology to condition distorted acoustic emission signals to identify fracture timing from human cadaver spine impact tests. J. Mech. Behav. Biomed. Mater. 40:156–160, 2014.CrossRefPubMedGoogle Scholar
  5. 5.
    Breuer, L., J. Dammers, T. P. L. Roberts, and N. J. Shah. A constrained ICA approach for real-time cardiac artifact rejection in magnetoencephalography. IEEE Trans. Biomed. Eng. 61:405–414, 2014.CrossRefPubMedGoogle Scholar
  6. 6.
    Buehler, M. J. Nanomechanics of collagen fibrils under varying cross-link densities: atomistic and continuum studies. J. Mech. Behav. Biomed. Mater. 1:59–67, 2008.CrossRefPubMedGoogle Scholar
  7. 7.
    Cormier, J., S. Manoogian, J. Bisplinghoff, C. McNally, and S. Duma. The use of acoustic emission in facial fracture detection. Biomed. Sci. Instrum. 44:147–152, 2008.PubMedGoogle Scholar
  8. 8.
    Cormier, J., S. Manoogian, J. Bisplinghoff, S. Rowson, A. Santago, C. McNally, S. Duma, and J. Bolte. The tolerance of the frontal bone to blunt impact. J. Biomech. Eng. 133:21004, 2011.CrossRefGoogle Scholar
  9. 9.
    Denis, F. The three columns of the spine and its significance in the classification of acute thoracolumbar spine injuries. Spine (Phila. Pa. 1976). 8:817–831, 1983.Google Scholar
  10. 10.
    Donnelly, E., R. M. Williams, S. A. Downs, M. E. Dickinson, S. P. Baker, and M. C. H. van der Meulen. Quasistatic and dynamic nanomechanical properties of cancellous bone tissue relate to collagen content and organization. J. Mater. Res. 21:2106–2117, 2006.CrossRefGoogle Scholar
  11. 11.
    Fischer, R. A., S. W. Arms, M. H. Pope, and D. Seligson. Analysis of the effect of using two different strain rates on the acoustic emission in bone. J. Biomech. 19:119–127, 1986.CrossRefPubMedGoogle Scholar
  12. 12.
    Funk, J. R., J. R. Crandall, L. J. Tourret, C. B. MacMahon, C. R. Bass, J. T. Patrie, N. Khaewpong, and R. H. Eppinger. The axial injury tolerance of the human foot/ankle complex and the effect of Achilles tension. J. Biomech. Eng. 124:750–757, 2002.CrossRefPubMedGoogle Scholar
  13. 13.
    Funk, J. R., J. R. Kerrigan, and J. R. Crandall. Dynamic bending tolerance and elastic-plastic material properties of the human femur. Annu. Proc. Assoc. Adv. Automot. Med. 48:215–233, 2004.PubMedPubMedCentralGoogle Scholar
  14. 14.
    Gautieri, A., M. J. Buehler, and A. Redaelli. Deformation rate controls elasticity and unfolding pathway of single tropocollagen molecules. J. Mech. Behav. Biomed. Mater. 2:130–137, 2009.CrossRefPubMedGoogle Scholar
  15. 15.
    Gibson, P. C., M. P. Lamoureux, and G. F. Margrave. Letter to the editor: stockwell and wavelet transforms. J. Fourier Anal. Appl. 12:713–721, 2006.CrossRefGoogle Scholar
  16. 16.
    Goff, M. G., C. R. Slyfield, S. R. Kummari, E. V. Tkachenko, S. E. Fischer, Y. H. Yi, M. G. Jekir, T. M. Keaveny, and C. J. Hernandez. Three-dimensional characterization of resorption cavity size and location in human vertebral trabecular bone. Bone 51:28–37, 2012.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Goodyear, B. G., H. Zhu, R. A. Brown, and J. R. Mitchell. Removal of phase artifacts from fMRI data using a stockwell transform filter improves brain activity detection. Magn. Reson. Med. 51:16–21, 2004.CrossRefPubMedGoogle Scholar
  18. 18.
    Hasegawa, K., H. E. Takahashi, Y. Koga, T. Kawashima, T. Hara, Y. Tanabe, and S. Tanaka. Mechanical properties of osteopenic vertebral bodies monitored by acoustic emission. Bone 14:737–743, 1993.CrossRefPubMedGoogle Scholar
  19. 19.
    Kent, R., S. Stacey, and C. Parenteau. Dynamic pinch tolerance of the phalanges and interphalangeal joints. Traffic Inj. Prev. 9:83–88, 2008.CrossRefPubMedGoogle Scholar
  20. 20.
    Liu, X. S., E. M. Stein, B. Zhou, C. A. Zhang, T. L. Nickolas, A. Cohen, V. Thomas, D. J. McMahon, F. Cosman, J. Nieves, E. Shane, and X. E. Guo. Individual trabecula segmentation (ITS)-based morphological analyses and microfinite element analysis of HR-pQCT images discriminate postmenopausal fragility fractures independent of DXA measurements. J. Bone Miner. Res. 27:263–272, 2012.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Magerl, F., M. Aebi, S. D. Gertzbein, J. Harms, and S. Nazarian. A comprehensive classification of thoracic and lumbar injuries. Eur. Spine J. 3:184–201, 1994.CrossRefPubMedGoogle Scholar
  22. 22.
    Mauch, M., J. D. Currey, and A. J. Sedman. Creep fracture in bones with different stiffnesses. J. Biomech. 25:11–16, 1992.CrossRefPubMedGoogle Scholar
  23. 23.
    McCormack, T., E. Karaikovic, and R. W. Gaines. The load sharing classification of spine fractures. Spine (Phila. Pa. 1976) 19:1741–1744, 1994.Google Scholar
  24. 24.
    McKay, B. J., and C. A. Bir. Lower extremity injury criteria for evaluating military vehicle occupant injury in underbelly blast events. Stapp Car Crash J. 53:229–249, 2009.PubMedGoogle Scholar
  25. 25.
    Newitt, D. C., S. Majumdar, B. Van Rietbergen, G. Von Ingersleben, S. T. Harris, H. K. Genant, C. Chesnut, P. Garnero, and B. MacDonald. In vivo assessment of architecture and micro-finite element analysis derived indices of mechanical properties of trabecular bone in the radius. Osteoporos. Int. 13:6–17, 2002.CrossRefPubMedGoogle Scholar
  26. 26.
    Ni, Q. Q., and M. Iwamoto. Wavelet transform of acoustic emission signals in failure of model composites. Eng. Fract. Mech. 69:717–728, 2002.CrossRefGoogle Scholar
  27. 27.
    Ohno, K., and M. Ohtsu. Crack classification in concrete based on acoustic emission. Constr. Build. Mater. 24:2339–2346, 2010.CrossRefGoogle Scholar
  28. 28.
    Oth, A., S. Parolai, and D. Bindi. Spectral analysis of K-NET and KiK-net data in Japan, Part I: Database compilation and peculiarities. Bull. Seismol. Soc. Am. 101(2):652–666, 2011. doi: 10.1785/0120100134.CrossRefGoogle Scholar
  29. 29.
    Pinnegar, C. R., and L. Mansinha. The S-transform with windows of arbitrary and varying shape. Geophysics 68:381, 2003.CrossRefGoogle Scholar
  30. 30.
    R Core Team. R: A Language and Environment for Statistical Computing, Vienna, Austria, 2015.
  31. 31.
    Ruff, C. B., and C. W. Hayes. Bone-mineral content in the lower limb. Relationship to cross-sectional geometry. J. Bone Joint Surg. Am. 66-A(7):1024–1031, 1984.CrossRefGoogle Scholar
  32. 32.
    Sanders, R., P. Fortin, T. DiPasquale, and A. Walling. Operative treatment in 120 displaced intraarticular calcaneal fractures. Results using a prognostic computed tomography scan classification. Clin. Orthop. Relat. Res. 1993. doi: 10.1097/00003086-199305000-00012.Google Scholar
  33. 33.
    Shridharani, J. K., A. L. Schmidt, C. A. Cox, B. R. Bigler, A. E. Knight, R. Cameron, and D. Bass. Dynamic Failure Localization in Spinal Specimens using Acoustic Emissions. In: IRCOBI Conference 2014, Berlin, Germany, pp. 166–175, 2014.
  34. 34.
    Slyfield, C. R., E. V. Tkachenko, S. E. Fischer, K. M. Ehlert, I. H. Yi, M. G. Jekir, R. G. O’Brien, T. M. Keaveny, and C. J. Hernandez. Mechanical failure begins preferentially near resorption cavities in human vertebral cancellous bone under compression. Bone 50:1281–1287, 2012.CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Stockwell, R. G. A basis for efficient representation of the S-transform. Digit. Signal Process. 17:371–393, 2007.CrossRefGoogle Scholar
  36. 36.
    Stockwell, R. G. Why use the S-transform? Pseudo Differ. Oper. Partial Differ. Equ. Time-Freq. Anal. 52:279–309, 2007.Google Scholar
  37. 37.
    Stockwell, R. G., L. Mansinha, and R. P. Lowe. Localization of the complex spectrum: The S transform. IEEE Trans. Signal Process. 44:998–1001, 1996.CrossRefGoogle Scholar
  38. 38.
    Szabo, T. L., and J. Wu. A model for longitudinal and shear wave propagation in viscoelastic media. J. Acoust. Soc. Am. 107:2437–2446, 2000.CrossRefPubMedGoogle Scholar
  39. 39.
    Trebacz, H., and A. Zdunek. Three-point bending and acoustic emission study of adult rat femora after immobilization and free remobilization. J. Biomech. 39:237–245, 2006.CrossRefPubMedGoogle Scholar
  40. 40.
    Van Toen, C., J. Street, T. R. Oxland, and P. A. Cripton. Acoustic emission signals can discriminate between compressive bone fractures and tensile ligament injuries in the spine during dynamic loading. J. Biomech. 45:1643–1649, 2012.CrossRefPubMedGoogle Scholar
  41. 41.
    Wang, J., B. Zhou, X. S. Liu, A. J. Fields, A. Sanyal, X. Shi, M. Adams, T. M. Keaveny, and X. E. Guo. Trabecular plates and rods determine elastic modulus and yield strength of human trabecular bone. Bone 72:71–80, 2015.CrossRefPubMedGoogle Scholar
  42. 42.
    Wang, M. C., F. Pintar, N. A. Yoganandan, and D. J. Maiman. The continued burden of spine fractures after motor vehicle crashes. J. Neurosurg. Spine 10:86–92, 2009.PubMedGoogle Scholar
  43. 43.
    Whang, P. G., and A. R. Vaccaro. Thoracolumbar spine fractures and dislocations. In: Fractures in Adults, edited by R. W. Bucholz, C. M. Court-Brown, J. D. Heckman, and P. I. Tornetta. Philadelphia: Lippincott Williams & Wilkins, 2010, pp. 1377–1411.Google Scholar
  44. 44.
    Zioupos, P., J. D. Currey, and A. J. Sedman. An examination of the micromechanics of failure of bone and antler by acoustic emission tests and Laser Scanning Confocal Microscopy. Med. Eng. Phys. 16:203–212, 1994.CrossRefPubMedGoogle Scholar
  45. 45.
    Zwipp, H., H. Tscherne, H. Thermann, and T. Weber. Osteosynthesis of displaced intraarticular fractures of the calcaneus. Results in 123 cases. Clin. Orthop. Relat. Res. 290:76–86, 1993.Google Scholar
  46. 46.

Copyright information

© Biomedical Engineering Society 2017

Authors and Affiliations

  • Brian D. Goodwin
    • 1
  • Frank A. Pintar
    • 1
  • Narayan Yoganandan
    • 1
  1. 1.Medical College of Wisconsin, Neuroscience Research Labs - Research 151, Zablocki VA Medical CenterMilwaukeeUSA

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