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Journal of Biomechanical Engineering | Volume 133 | Issue 7 | Research Paper
Research Papers

A Wearable System to Assess Risk for Anterior Cruciate Ligament Injury During Jump Landing: Measurements of Temporal Events, Jump Height, and Sagittal Plane Kinematics

[+] Author and Article Information
Ariel V. Dowling, Julien Favre, Thomas P. Andriacchi

 Department of Mechanical Engineering, Stanford University, Durand Building 061, 496 Lomita Mall, Stanford, CA 94305-4308; Bone and Joint Center, Palo Alto Veterans Affairs, Palo Alto, CA 94304 e-mail: adowling@stanford.edu Department of Mechanical Engineering, Stanford University, Durand Building 061, 496 Lomita Mall, Stanford, CA 94305-4308 e-mail: jfavre@stanford.edu Department of Mechanical Engineering, Stanford University, Durand Building 227, 496 Lomita Mall, Stanford, CA 94305-4308; Department of Orthopedic Surgery, Stanford University Medical Center, Bone and Joint Center, Palo Alto Veterans Affairs, Stanford, CA 94305-5101 e-mail:tandriac@stanford.edu

J Biomech Eng 133(7), 071008 (Jul 22, 2011) (7 pages) doi:10.1115/1.4004413 History: Received March 14, 2011; Revised May 28, 2011; Posted June 13, 2011; Published July 22, 2011; Online July 22, 2011
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The incidence of anterior cruciate ligament (ACL) injury remains high, and there is a need for simple, cost effective methods to identify athletes at a higher risk for ACL injury. Wearable measurement systems offer potential methods to assess the risk of ACL injury during jumping tasks. The objective of this study was to assess the capacity of a wearable inertial-based system to evaluate ACL injury risk during jumping tasks. The system accuracy for measuring temporal events (initial contact, toe-off), jump height, and sagittal plane angles (knee, trunk) was assessed by comparing results obtained with the wearable system to simultaneous measurements obtained with a marker-based optoelectronic reference system. Thirty-eight healthy participants (20 male and 18 female) performed drop jumps with bilateral and unilateral support landing. The mean differences between the temporal events obtained with both systems were below 5 ms, and the precisions were below 24 ms. The mean jump heights measured with both systems differed by less than 1 mm, and the associations (Pearson correlation coefficients) were above 0.9. For the discrete angle parameters, there was an average association of 0.91 and precision of 3.5° for the knee flexion angle and an association of 0.77 and precision of 5.5° for the trunk lean. The results based on the receiver-operating characteristic (ROC) also demonstrated that the proposed wearable system could identify movements at higher risk for ACL injury. The area under the ROC plots was between 0.89 and 0.99 for the knee flexion angle and between 0.83 and 0.95 for the trunk lean. The wearable system demonstrated good concurrent validity with marker-based measurements and good discriminative performance in terms of the known risk factors for ACL injury. This study suggests that a wearable system could be a simple cost-effective tool for conducting risk screening or for providing focused feedback.
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Figures

Grahic Jump Location
+Proposed wearable system
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Proposed wearable system
Figure 1

Proposed wearable system

Grahic Jump Location
+Bland and Altman analysis of jump height. Solid line corresponds to bias and dashed lines correspond to 66% limits of agreement.
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Bland and Altman analysis of jump height. Solid line corresponds to bias and dashed lines correspond to 66% limits of agreement.
Figure 2

Bland and Altman analysis of jump height. Solid line corresponds to bias and dashed lines correspond to 66% limits of agreement.

Grahic Jump Location
+Example of continuous knee flexion angle and trunk lean for one subject during one bilateral jumping task with the discrete time point parameters identified
View Large  |  Save Figure  |  Download Slide (.ppt)
Example of continuous knee flexion angle and trunk lean for one subject during one bilateral jumping task with the discrete time point parameters identified
Figure 3

Example of continuous knee flexion angle and trunk lean for one subject during one bilateral jumping task with the discrete time point parameters identified

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