Biomechanics and Modeling in Mechanobiology

, Volume 17, Issue 1, pp 235–247 | Cite as

Propagation of errors from skull kinematic measurements to finite element tissue responses

  • Calvin Kuo
  • Lyndia Wu
  • Wei Zhao
  • Michael Fanton
  • Songbai Ji
  • David B. Camarillo
Original Paper

Abstract

Real-time quantification of head impacts using wearable sensors is an appealing approach to assess concussion risk. Traditionally, sensors were evaluated for accurately measuring peak resultant skull accelerations and velocities. With growing interest in utilizing model-estimated tissue responses for injury prediction, it is important to evaluate sensor accuracy in estimating tissue response as well. Here, we quantify how sensor kinematic measurement errors can propagate into tissue response errors. Using previous instrumented mouthguard validation datasets, we found that skull kinematic measurement errors in both magnitude and direction lead to errors in tissue response magnitude and distribution. For molar design instrumented mouthguards susceptible to mandible disturbances, 150–400% error in skull kinematic measurements resulted in 100% error in regional peak tissue response. With an improved incisor design mitigating mandible disturbances, errors in skull kinematics were reduced to <50%, and several tissue response errors were reduced to <10%. Applying 30\(^{\circ }\) rotations to reference kinematic signals to emulate sensor transformation errors yielded below 10% error in regional peak tissue response; however, up to 20% error was observed in peak tissue response for individual finite elements. These findings demonstrate that kinematic resultant errors result in regional peak tissue response errors, while kinematic directionality errors result in tissue response distribution errors. This highlights the need to account for both kinematic magnitude and direction errors and accurately determine transformations between sensors and the skull.

Keywords

Brain tissue response Finite element Wearable head impact sensors Mild traumatic brain injury 

Notes

Acknowledgements

This study was supported by the National Institutes of Health (NIH), National Institute of Biomedical Imaging and Bioengineering (NIBIB) 3R21EB01761101S1, the Stanford Child Health Research Institute Transdisciplinary Initiatives Program, and the Stanford Bio-X Graduate Research Fellowship Program. Additional funding was provided by the NIH Grants R01 NS092853 and R21 NS088781.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringStanford UniversityStanfordUSA
  2. 2.Department of Bio-EngineeringStanford UniversityStanfordUSA
  3. 3.Department of Biomedical EngineeringWorcester Polytechnic InstituteWorcesterUSA

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