Frequency and time dependent viscoelastic characterization of pediatric porcine brain tissue in compression

Weiqi Li1, Duncan E T Shepherd2, Daniel M Espino2

  • 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China. liweiqi1010@163.com.

Insights

Pediatric brain tissue shows complex viscoelastic properties crucial for understanding child head injuries. This study characterized its behavior under various loads, providing vital data for improving head protection systems.

Area of Science:

  • Biomechanical Engineering
  • Pediatric Traumatology
  • Materials Science

Background:

  • Understanding pediatric brain tissue mechanics is vital for accurate head injury simulations.
  • Limited data on pediatric brain tissue viscoelasticity hinders the biofidelity of computational models.
  • Characterizing these properties is essential for developing effective pediatric head protection.

Purpose of the Study:

  • To investigate the viscoelastic behavior of pediatric porcine brain tissue under compression.
  • To determine frequency-dependent and time-dependent viscoelastic properties.
  • To identify suitable constitutive models for pediatric brain tissue.

Main Methods:

  • Dynamic mechanical analysis was used to assess frequency-dependent properties (0.1–40 Hz).
  • Compression tests and stress relaxation were performed at varying strain rates (0.01/s, 1/s, 10/s) up to 0.3 strain.
  • Pediatric porcine brain tissue was utilized for experimental characterization.

Main Results:

  • The loss modulus increased continuously above 20 Hz, while the storage modulus plateaued.
  • Increasing strain rate significantly elevated mean stress at different strain levels (0.1, 0.2, 0.3).
  • Pediatric brain tissue's compressive response demonstrated sensitivity to both strain rate and frequency.

Conclusions:

  • The characterized viscoelastic properties offer valuable insights into pediatric brain injury mechanisms.
  • This data is crucial for enhancing the biofidelity of computational models for pediatric head injuries.
  • Findings will aid in the development of advanced head protection systems for children.

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