Feature selection using a principal component analysis of the kinematics of the pivot shift phenomenon.

The pivot shift test reproduces a complex instability of the knee joint following rupture of the anterior cruciate ligament. The grade of the pivot shift test has been shown to correlate to subjective criteria of knee joint function, return to physical activity and long-term outcome. This severity is represented by a grade that is attributed by a clinician in a subjective manner, rendering the pivot shift test poorly reliable. The purpose of this study was to unveil the kinematic parameters that are evaluated by clinicians when they establish a pivot shift grade. To do so, eight orthopaedic surgeons performed a total of 127 pivot shift examinations on 70 subjects presenting various degrees of knee joint instability. The knee joint kinematics were recorded using electromagnetic sensors and principal component analysis was used to determine which features explain most of the variability between recordings. Four principal components were found to account for most of this variability (69%), with only the first showing a correlation to the pivot shift grade (r = 0.55). Acceleration and velocity of tibial translation were found to be the features that best correlate to the first principal component, meaning they are the most useful for distinguishing different recordings. The magnitudes of the tibial translation and rotation were amongst those that accounted for the least variability. These results indicate that future efforts to quantify the pivot shift should focus more on the velocity and acceleration of tibial translation and less on the traditionally accepted parameters that are the magnitudes of posterior translation and external tibial rotation.

[1]  H. Matsumoto Mechanism of the pivot shift. , 1990, The Journal of bone and joint surgery. British volume.

[2]  Robert Ho,et al.  Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS , 2006 .

[3]  K. Deluzio,et al.  Principal component models of knee kinematics and kinetics: Normal vs. pathological gait patterns , 1997 .

[4]  S. Olney,et al.  Multivariate examination of data from gait analysis of persons with stroke. , 1998, Physical therapy.

[5]  Daniel Kendoff,et al.  In vivo analysis of the pivot shift phenomenon during computer navigated ACL reconstruction , 2008, Knee Surgery, Sports Traumatology, Arthroscopy.

[6]  P. Jokl,et al.  Implications of the Pivot Shift in the ACL-Deficient Knee , 2005, Clinical orthopaedics and related research.

[7]  Kouki Nagamune,et al.  In Vivo Measurement of the Pivot-Shift Test in the Anterior Cruciate Ligament—Deficient Knee Using an Electromagnetic Device , 2007, The American journal of sports medicine.

[8]  J. L. Astephen,et al.  Biomechanical features of gait waveform data associated with knee osteoarthritis: an application of principal component analysis. , 2007, Gait & posture.

[9]  David R. Labbé,et al.  Accounting for velocity of the pivot shift test manoeuvre decreases kinematic variability. , 2011, The Knee.

[10]  久保 晴司 Reliability and usefulness of a new in vivo measurement system of the pivot shift , 2007 .

[11]  Kevin J Deluzio,et al.  Neuromuscular and Lower Limb Biomechanical Differences Exist between Male and Female Elite Adolescent Soccer Players during an Unanticipated Side-cut Maneuver , 2007, The American journal of sports medicine.

[12]  Kristian M O'Connor,et al.  Differences in cutting knee mechanics based on principal components analysis. , 2009, Medicine and science in sports and exercise.

[13]  R. Cattell,et al.  A Comprehensive Trial Of The Scree And Kg Criteria For Determining The Number Of Factors. , 1977, Multivariate behavioral research.

[14]  H. Kaiser The varimax criterion for analytic rotation in factor analysis , 1958 .

[15]  Lianne Jones,et al.  Reduction, classification and ranking of motion analysis data: an application to osteoarthritic and normal knee function data , 2008, Computer methods in biomechanics and biomedical engineering.

[16]  A A Amis,et al.  Intraoperative measurement of knee kinematics in reconstruction of the anterior cruciate ligament. , 2002, The Journal of bone and joint surgery. British volume.

[17]  A. C. Rencher Methods of multivariate analysis , 1995 .

[18]  Andrew A. Amis,et al.  Measurement of Knee Laxity and Pivot-Shift Kinematics With Magnetic Sensors , 2008 .

[19]  A. Pearle,et al.  The pivot shift. , 2008, The Journal of the American Academy of Orthopaedic Surgeons.

[20]  Andrew A. Amis,et al.  The pivot-shift phenomenon: a clinical and biomechanical perspective , 1998 .

[21]  Michael Roan,et al.  An application of principal component analysis for lower body kinematics between loaded and unloaded walking. , 2009, Journal of biomechanics.

[22]  N. Hagemeister,et al.  A reproducible method for studying three-dimensional knee kinematics. , 2005, Journal of biomechanics.

[23]  E S Grood,et al.  A joint coordinate system for the clinical description of three-dimensional motions: application to the knee. , 1983, Journal of biomechanical engineering.

[24]  William I. Sterett,et al.  Relationships between Objective Assessment of Ligament Stability and Subjective Assessment of Symptoms and Function after Anterior Cruciate Ligament Reconstruction , 2004, The American journal of sports medicine.

[25]  Stefano Zaffagnini,et al.  Pivot‐shift test: Analysis and quantification of knee laxity parameters using a navigation system , 2009, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[26]  K. Deluzio,et al.  Gait assessment in unicompartmental knee arthroplasty patients: Principal component modelling of gait waveforms and clinical status , 1999 .