computing dynamic stability of gait for the assessment of the effect of perturbation training of anterior cruciate ligament deficient patients

computing dynamic stability of gait for the assessment of the effect of perturbation training of anterior cruciate ligament deficient patients

;Mohammad Ali Sanjari;Ali Ashraf Jamshidi;Leila Abbasi;Saeedeh Seyyed-Mohseni;Mohammad Kamali
arsenic in geosphere and human diseases, as 2010 - 3rd international congress: arsenic in the environment 2012 Vol. 12 pp. 8-13
160
sanjari2012journalcomputing

Abstract

Objective: In this study, using nonlinear dynamics methods, dynamic stability index was used to assess the effect of perturbation training on anterior cruciate ligament (ACL) deficient patients. Materials & Methods: Non-randomized sampling was employed to recruit male athletes with at least 6 months elapsed after their ACL lesion. Using tilt boards, 10 sessions of perturbation training were done. Lower limb kinematics were recorded using electrogoniometers during walking before and after the training. Knee kinematic data of 60 gait cycles was used to calculate dynamic stability index. Time series were reconstructed in five dimensions then finite-time lyapunov exponent was calculated for seven subjects before and after training. Wilcoxon nonparametric test was used to assess the impact of training. Results: The value of the dynamic stability index before and after training was computed as and , respectively. Statistical analysis showed that dynamic stability index of gait improved significantly in ACL deficient patients after perturbation training (P=0.016). Conclusion: Perturbation training improved the dynamic stability of ACL deficient patients. Therefore using nonlinear dynamics methods one can establish an effective theoretical basis for designing and assessment of specific ACL rehabilitation. Such methods could be used in functional assessment of other interventions that affects body movement such as gait.

Citation

ID: 238692
Ref Key: sanjari2012journalcomputing
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
238692
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet