A principal component analysis approach to correcting the knee flexion axis during gait

JOURNAL OF BIOMECHANICS

卷:49

Article

Jensen, Elisabeth^1,2  Lugade, Vipul^1,3  Crenshaw, Jeremy⁴  Miller, Emily²  Kaufman, Kenton² 

[1] Mayo Clin, Mayo Grad Sch, Biomed Engn & Physiol Track, Rochester, MN 55905 USA

[2] Mayo Clin, Div Orthoped Res, Mot Anal Lab, Charlton North L-1101, Rochester, MN 55905 USA

[3] Chiang Mai Univ, Dept Phys Therapy, Whitaker Int Program, Chiang Mai 50200, Thailand

[4] Univ Delaware, Dept Kinesiol & Appl Physiol, Newark, DE 19713 USA

关键词: Gait analysis;    Kinematics;    Axis of rotation;    Marker placement;    Correction algorithm;   

DOI  :  10.1016/j.jbiomech.2016.03.046

来源: Elsevier

【 摘 要 】

Accurate and precise knee flexion axis identification is critical for prescribing and assessing tibial and femoral derotation osteotomies, but is highly prone to marker misplacement-induced error. The purpose of this study was to develop an efficient algorithm for post-hoc correction of the knee flexion axis and test its efficacy relative to other established algorithms. Gait data were collected on twelve healthy subjects using standard marker placement as well as intentionally misplaced lateral knee markers. The efficacy of the algorithm was assessed by quantifying the reduction in knee angle errors. Crosstalk error was quantified from the coefficient of determination (r(2)) between knee flexion and adduction angles. Mean rotation offset error (alpha(o)) was quantified from the knee and hip rotation kinematics across the gait cycle. The principal component analysis (PCA)-based algorithm significantly reduced r(2) (p < 0.001) and caused alpha(o,knee) to converge toward 11.9 +/- 8.0 degrees of external rotation, demonstrating improved certainty of the knee kinematics. The within-subject standard deviation of alpha(o,hip) between marker placements was reduced from 13.5 +/- 1.5 degrees to 0.7 +/- 0.2 degrees (p < 0.001), demonstrating improved precision of the knee kinematics. The PCA-based algorithm performed at levels comparable to a knee abduction-adduction minimization algorithm (Baker et al., 1999) and better than a null space algorithm (Schwartz and Rozumalski, 2005) for this healthy subject population. (C) 2016 Elsevier Ltd. All rights reserved.

【 授权许可】

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