Can a Force Driven Harmonic Oscillator Model be Clinically Applied to ACL Reconstructed Patients?

M. J. Decker, J. B. Dingwell

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

The purpose of this study was to determine whether anterior cruciate ligament (ACL) reconstructed patients select a preferred stride period during walking that was consistent with the resonant period of their legs modeled as force driven harmonic oscillators (FDHO). Thirty-four ACL reconstructed patients, 6 weeks after surgery, performed treadmill walking at a self-selected speed. The FDHO model with different gravitational factors of n=1.5, 2 and 2.5 was used to determine the best-fit prediction of the patients preferred stride period. In addition, the elastic component of the model was empirically derived to determine its relationship with the models prediction accuracy. A gravitational factor of 1.5 applied to the resonance formula was found to be the best prediction of the patient's preferred stride period. The elastic component demonstrated a negative, linear relationship with the model's prediction error of the preferred stride period with a gravitational factor of 2. The results were interpreted to indicate that an adaptation in the elastic component represented a reduction in the global stiffness of the leg caused by a net reduction in active muscle tension. The FDHO model may have the clinical potential for determining the baseline and recovery status of ACL reconstructed patients.

Original languageEnglish (US)
Pages (from-to)1788-1791
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
StatePublished - 2003
EventA New Beginning for Human Health: Proceddings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico
Duration: Sep 17 2003Sep 21 2003

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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