| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Research Reports |
JH Hollman, PT, PhD, is Assistant Professor, Department of Physical Therapy, Clarke College, 1550 Clarke Dr, Dubuque, IA 52001–3198 (USA) (John.Hollman{at}clarke.edu). Address all correspondence to Dr Hollman
RH Deusinger, PT, PhD, is Assistant Professor, Departments of Internal Medicine and Biomedical Engineering, Washington University School of Medicine, St Louis, Mo
LR Van Dillen, PT, PhD, is Assistant Professor, Program in Physical Therapy, Washington University School of Medicine
MJ Matava, MD, is Assistant Professor, Department of Orthopaedic Surgery, Washington University School of Medicine
Submitted September 21, 2001;
Accepted March 28, 2002
 | Abstract |
|---|
Key Words: Anterior cruciate ligament • Biomechanics • Electromyography • Instantaneous center of rotation • Knee
| Introduction |
|---|
 TopAbstract Introduction MethodsResultsDiscussionConclusionReferences |
|---|
Frankel et al,1 Gerber and Matter,3 and Mitton et al4 did not examine PICR or measure the amount of joint surface rolling and gliding under weight-bearing (WB) conditions. Tibiofemoral joint compression forces are greater during WB knee extension than during non-weight-bearing (NWB) knee extension. During WB knee extension, the knee joint is loaded through body weight as well as through muscle activity. This is more loading than occurs during NWB knee extension, when the leg is unobstructed as it moves through space and the knee is loaded primarily through muscle activity.5,6 As joint compression increases, joint surface geometry regulates relative joint surface rolling and gliding.2,6 As joint compression decreases, the articular ligaments become more involved in regulating joint surface rolling and gliding.2,6 Consequently, several researchers have shown that the knee cruciate ligaments are loaded in the opposite manner from each other during movement and are loaded differently when in WB and NWB.7–11 Anterior cruciate ligament strain is greater than posterior cruciate ligament (PCL) strain during NWB knee extension, whereas PCL strain is greater than ACL strain during WB knee extension. Presumably, this is because greater anterior displacement of the tibia with respect to the femur is believed to occur during NWB.9,10
Collectively, the results of these studies7–11 suggest that knee joint surface rolling and gliding movements, and therefore PICR, may differ between WB and NWB movements. Hollman et al,12 using PICR to estimate knee joint surface rolling and gliding in subjects without knee joint pathology, reported that greater joint surface gliding occurs during NWB knee extension. These data, however, have not been published in a peer-reviewed publication. Given that the ACL provides the primary restraint to anterior tibial displacement,13 we hypothesized that joint surface gliding may be exaggerated in knees with injured ACLs during WB and NWB.
Electromyography (EMG) can provide some insight into variations in muscle activity. In EMG studies, increased muscle activity about a joint is associated with increased joint compression.9 We believe, therefore, that it is reasonable to expect that altered muscle activity may also influence the relative amount of rolling and gliding and the PICR. Evidence suggests the hamstring muscles contribute to knee joint stability.9,10 In the absence of the structural integrity of the ACL, hamstring muscle co-contraction is thought to provide stability during knee extension either by virtue of its posteriorly directed force, its contribution to increased joint compression, or a combination of both mechanisms.5,9,14–16
Data from several studies indicate that people with an injured ACL or reconstructed ACL demonstrate greater hamstring muscle EMG activity or altered hamstring muscle timing during functional activities than do subjects without knee pathology.17–21 In our opinion, this suggests that a change in muscle coordination may be necessary to improve stability in knees with injured ACLs. We contend that an increase in hamstring muscle activity may be sufficient to counteract the increased gliding that might otherwise be present. Electromyographic analyses that accompany the measurement of joint surface rolling and gliding movements, in our opinion, can determine whether differences in muscle activity are associated with changes in joint surface rolling and gliding.
The primary purpose of our study was to compare joint surface rolling and gliding between subjects without knee pathology and subjects with injured ACLs during NWB and WB movements. A secondary purpose was to determine whether EMG activity of selected lower-extremity muscles, particularly the hamstring muscles, differed between these groups. We hypothesized that greater joint surface gliding would occur in knees with injured ACLs than in knees without pathology, assuming that an increase in hamstring muscle activity would not sufficiently counteract the hypothesized change in rolling and gliding movements. If a change in rolling or gliding did not occur, we hypothesized that greater hamstring muscle activity would be present in subjects with injured ACLs.
| Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionReferences |
|---|
|
10 degrees to 90 degrees of knee flexion (relative to a 0°–180° notation system23) and an active straight leg raise of 60 degrees or greater in a supine position. This position was chosen in an effort to reduce potential effects of short hamstring muscles on knee joint movements. All subjects with injured ACLs had at least 120 degrees of knee flexion, although 3 subjects with acute injuries had mild knee joint effusion at the time of testing and had deficits in full extension of up to 5 degrees. We made a judgment that those with mild effusion, assuming they could move through the knee range of motion required of the study, would not have substantially adverse effects on the results and were therefore included in the study. Potential subjects with injured ACLs were excluded if they had any history of neurological or neuromuscular pathology. Comparison subjects without knee pathology were recruited from a population of convenience—the undergraduate and graduate student populations at Washington University in St Louis. Potential subjects were excluded from the study if they had any history of knee injury or neurological or neuromuscular pathology. Comparison subjects were allowed to take part only if they satisfied the following criteria: (1) active range of motion of the knee of 0 to 130 degrees of flexion or greater, (2) an active straight leg raise in a supine position of 60 degrees or greater, (3) grade 5 force production capability of the right quadriceps femoris and hamstring muscles based on manual muscle testing techniques,24 and (4) negative findings on the Lachman's test, posterior drawer test, valgus and varus ligament stability tests, and McMurray's meniscus test.25 We did not examine the reliability of these measurements.
Instrumentation
Movements were recorded with 2 Panasonic AG-455P SVHS video cameras.* Kinematic data were processed with Ariel Performance Analysis System (APAS) software, APAS99 version 3.5.
The APAS software provides accurate measurements of linear (mean error less than 2 mm) and angular (mean error less than 0.3°) standards26 and reliable measurements of angular velocity data, with intraclass correlation coefficients exceeding .85 at various speeds of movement.27 Coordinate transformations and instantaneous center of rotation (ICR) calculations are described elsewhere28 and were performed using custom-written programs in Microsoft Excel 97, version SR-1.
Electromyographic signals were collected with bipolar surface electrodes having an on-site pre-amplification gain of 310.
Each active electrode pair consisted of two 8-mm-diameter silver-silver chloride electrodes with an interelectrode distance of 35 mm. The on-site preamplifiers had common mode rejection ratio ratings of approximately 105 dB at 60 Hz with high direct current input impedance of 100,000 MW and bandwidth frequencies of 8 Hz to 31 kHz. The EMG signals were processed with APAS software, and normalization procedures were performed with custom-written programs in Microsoft Excel.
A Bertec force platform|| was used as a video synchronization and EMG triggering device. Subjects made contact with the force platform while initiating their movement, which simultaneously turned on an external light source that was visible in the video fields of both video cameras and initiated EMG sampling. This triggering mechanism enabled videographic images and EMG data to be synchronized.
Procedure
All subjects signed an informed consent form approved by the Washington University School of Medicine Institutional Review Board. The primary investigator (JHH) conducted a brief physical examination to assess knee joint range of motion and assessed muscle force and knee stability in subjects without knee pathology. Active range of motion of the knee was measured with a universal goniometer using techniques described by Norkin and White,23 and muscle force was measured manually using techniques described by Kendall et al.24 Only the involved side was tested in subjects with injured ACLs. In subjects without knee pathology, the side tested was selected in a random manner to equalize the distribution of right and left knees between the groups. For 11 subjects without knee pathology, we randomly selected whether the right or left knee would be tested. After we determined that 15 subjects would be tested per group, the side tested in the group without pathology was assigned so that there would be an equal number of right and left knees tested in the study.
Surface EMG electrodes were taped over the mid–muscle belly of each subject's vastus lateralis, medial hamstring (ie, the semitendinosus), medial gastrocnemius, and gluteus maximus muscles. Electrodes were placed in a manner that we believe was in parallel with the line of action of the muscle. To facilitate signal conduction, each electrode site was rubbed with an alcohol wipe prior to electrode attachment. Electrode locations were found by following the description of Ericson et al,29 and specific locations were identified by palpating the respective muscle bellies. Once electrodes were applied, EMG signals were sampled during maximal voluntary isometric contractions (MVICs) for each muscle group.
Photoreflective markers, which were 2 cm in diameter, were placed on the lateral thigh and lateral leg to provide rigid-body representation of the thigh and leg segments. The markers were placed on the thigh 10 cm distal to the greater trochanter and 5 cm proximal to the lateral epicondyle and on the leg 1 to 2 cm distal to the fibular head and 1 to 2 cm proximal to the lateral malleolus, which minimized skin movement artifact.30 We did not examine the reliability of placing these markers.
Subjects sat on either a 35.6-cm (14-in) or 40.6-cm (16-in) wooden chair, depending on the subject's height and lower-extremity limb length that allowed the knee to be in approximately 100 degrees of flexion in its resting position. Subjects performed 5 repetitions each of the NWB and WB movements. To do the NWB movement, subjects extended their leg to a position of maximal knee extension. Subjects did the WB movement by executing a 2-legged sit-to-stand movement. Subjects initiated both testing conditions by exerting pressure on the force platform, which allowed us to synchronize the kinematic and EMG data. Because joint rotation at slow angular speeds (<30°/s) decreases PICR measurement accuracy,31 we attempted to control the speed of movement by instructing subjects to perform their movements over a period of approximately 1 second.
Data Processing
Reflective marker spatial locations and instantaneous center of rotation (ICR) calculations.
All spatial location data were recorded at 60 Hz, the sampling frequency of the video cameras. Images were captured, compressed, and stored on the computer hard drive with APAS software. Subsequently, the video files were transformed via direct linear transformation.32 Three-dimensional spatial locations of reflective markers defining the thigh and leg were autodigitized and smoothed between 3 and 6 Hz using a second-order Butterworth digital filter. Cutoff frequencies for each marker were selected by using spectral power analyses in the "Filter" module of APAS software. Spatial location data were transformed to a local reference system fixed in the thigh segment with its origin located at the lateral femoral epicondyle. The PICR data were calculated in a manner originally described by Winter31 and detailed by Hollman and Deusinger28 and Loudon.33 The joint's estimated instantaneous angular velocity (w) and the leg segment's estimated instantaneous tangential linear velocity (V) in the sagittal plane of motion were used to calculate locations of the ICR by identifying the distance (R) of the ICR from the lateral malleolus marker by
|
|
In Cartesian coordinates represented by a right-handed coordinate system, the location of the ICR is calculated as the distance (Rx, Ry) from the lateral malleolus as follows:
|
|
|
|
The accuracy and precision of ICR measurement that we used is based on data obtained with a model from which the ICR was a stationary and known entity. Calculations yielded a mean error magnitude of less than 1 mm and a standard deviation of 4.3 mm.28 The reliability coefficient for the method when applied to human knee joint PICR measurement exceeds .80.33 The ICR coordinate locations calculated for the first 3 digitizable trials from each movement condition were used for obtaining mean condition-dependent PICR patterns for each subject.
Intrinsic knee joint surface movements model.
Coordinates of the ICR were obtained for each participant through the range of motion and extracted at 10-degree intervals from 90 degrees to 10 degrees of knee flexion. Knee joint surface movements were examined on 2 levels. First, a mean PICR for each movement condition was plotted and analyzed visually to examine observable differences between the subject groups and between the WB and NWB movements. Second, participants' ICR coordinate data were applied to a planar mathematical knee joint model (Fig. 1) that was used to calculate relative proportions of knee joint surface rolling and gliding.
|
Based on the selected femoral contact point locations and the ICR data obtained experimentally, the relative proportion of rolling to gliding was calculated using the slip ratio described by O'Connor and Zavatsky.37 The slip ratio is defined by
|
|
|
|
|
|
is the fixed rotation angle (10°) between successive contact points. Ultimately, percent rolling (% rolling), defined by |
|
|
|
EMG.
The EMG data were sampled at 1,000 Hz. We used this sampling rate to satisfy the Nyquist theorem, which states that the sampling rate must be greater than or equal to 2 times the highest frequency component in the analog signal. Therefore, we were able to sample muscle fiber firing frequencies up to 500 Hz. All raw signals were full-wave rectified and subsequently processed through a linear envelope with a 50-millisecond floating window. The processed EMG data obtained from the test conditions then were normalized by dividing the magnitude of a muscle's EMG activity by its peak MVIC magnitude and multiplying by 100, and the normalized EMG values were expressed as a percentage of MVIC (% MVIC). The normalized EMG values, which were synchronized with knee angles, were extracted at respective 10-degree knee angle positions and used for data analysis. Because we consider lower-extremity EMG data to be highly reliable within testing sessions for movements similar to those used in this study,39 data from one repetition in each movement condition was processed for each subject.
Data Analysis
Movements.
A 3-way mixed model analysis of variance (ANOVA) with 
=.05 was conducted to test the null hypothesis that no difference occurred in rolling and gliding movements between subjects without knee pathology and subjects with injured ACLs. The dependent variable was % gliding. The between-subjects factor was group (subjects without knee pathology and subjects with injured ACLs). The within-subjects factors were movement (NWB and WB) and knee angle (90°, 80°, ..., 10°). We tested the main effects of group and movement and the group interactions with movement and knee angle to determine in which condition or conditions and at which knee angle or angles rolling and gliding movements differed between groups. If either a group x movement or group x movement x knee angle interaction existed, we then conducted a mixed-model ANOVA on each movement to determine whether differences occurred between groups within a movement. If a group x knee angle interaction existed, we conducted post hoc t tests with a Bonferroni-adjusted alpha to determine the knee angle or angles at which % gliding differed. The main effect of movement was tested to determine whether joint surface rolling and gliding differed between the WB and NWB movements across groups.
EMG.
A 4-way mixed-model ANOVA with the same between-subject factor (group) and 3 within-subjects factors—including movement, knee angle, and muscle (vastus lateralis, medial hamstring, medial gastrocnemius, gluteus maximus)—was conducted to test the null hypothesis that no difference existed in % MVIC between groups (=.05). We chose this analysis to determine whether differences in EMG activity occurred between subjects with injured ACLs and subjects without knee pathology. If the group main effect or interactions involving the group factor were significant, then a mixed-model ANOVA was performed on each muscle to determine which muscle or muscles differed between groups.
| Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionReferences |
|---|
|
|
There was a main effect for movement (F=9.67, df=1,28, P=.004). More joint surface gliding occurred in the NWB movement than in the WB movement (% gliding: WB=42.8%±1.7%, NWB=44.2%±1.4%) across both groups. A movement x knee angle interaction (F=12.11, df=8,224, P<.001) revealed that the difference in % gliding between movements was particularly apparent at full knee extension (% gliding: WB=33.7%±1.3%, NWB=47.1%±2.6%; t29=5.44, P=.001). More joint surface gliding occurred in the NWB movement than in the WB movement among subjects in both groups, particularly at full knee extension.
EMG
The EMG data are illustrated in Figure 4. Overall, EMG activity was greater in the WB movement than in the NWB movement (F=81.56, df=1,28, P=.001). Electromyographic activity also differed among muscles (F=39.10, df=4,112, P=.001) and across knee angles (F=7.47, df=8,224, P=.001). There was no group main effect, however, nor were there any interactions involving the group factor (Tab. 2). Because EMG activity did not differ between subjects without knee pathology and subjects with injured ACLs (F=2.00, df=1,28, P=.169, 1–ß=0.36), no additional analysis of EMG data was conducted.
|
|
| Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionReferences |
|---|
A second finding of our study is that, although less joint surface gliding occurred in the WB movement than in the NWB movement for both groups throughout the WB motion, greater joint surface gliding did occur in knees with injured ACLs than in knees without pathology (Fig. 3B). Researchers9,42,43 have found greater increases in anterior tibial displacement, anterior shearing forces, and ACL strain during knee extension in NWB than during knee extension in WB. For example, Jenkins et al44 demonstrated with knee arthrometer measurements that isometric quadriceps femoris muscle contractions produced greater anterior tibial displacement during a NWB movement than during a WB movement. Jenkins et al reported intraclass correlation coefficients ranging from .74 in the WB condition to .96 in the NWB condition. We did not examine reliability as part of our study. Results of such studies have led some clinicians to use WB exercise for many lower extremity disorders, particularly for the rehabilitation of patients with injured or reconstructed ACLs.45,46 Our findings, however, suggest that increased joint surface gliding may still be prevalent in knees with injured ACLs during WB movements.
EMG
Several researchers17–21 have indicated that muscle activity during the stance phase of the gait cycle differs between individuals without knee pathology and individuals with injured ACLs. People with injured ACLs are thought to produce more or earlier hamstring muscle activity in the gait cycle than people without knee pathology. Therefore, we hypothesized that subjects with injured ACLs may have exhibited increased hamstring muscle activity, particularly during WB movement. We found no differences in muscle activity, however, between subjects without knee pathology and subjects with injured ACLs. The lack of increased hamstring muscle activity may partially account for the increase in joint surface gliding seen in the knees with injured ACLs, in particular throughout the WB movement. Renstrom et al16 and Solomonow et al47 reported that hamstring muscle activity reduces anterior tibial displacement. Our data suggest that, in the absence of increased hamstring muscle activity in individuals with injured ACLs, anterior tibial displacement may not be reduced to a level equivalent to the displacement that occurs in knees without pathology.
The power analysis for our study was based on rolling and gliding data only. Muscle activity effects may have been present, but they were not detected because of low statistical power of the EMG portion of our study (1–ß=0.36). The effect size of differences in EMG magnitude between groups in our study was equal to 0.27, which would have required 60 subjects to obtain a statistical power of 0.80.
Clinical Relevance
Measurement of PICR may be used to examine joint surface rolling and gliding movements and may provide a basis for quantifying knee joint dysfunction or instability. Additional research incorporating PICR measurements and joint surface rolling and gliding movements may be useful. For example, some people with injured ACLs are able to perform functional tasks, including athletic activities, without the knee instability or pain often associated with ACL injury.48 Factors that differentiate people who are able to cope with their injured ACL from those who are not able to cope have not been fully elucidated.48,49 An ability to quantify rolling and gliding movements may provide insight into why some people function better with damaged ACLs than others.
Limitations
The methods and model used in this study were based on several assumptions that may differ to varying degrees among people. We believe, therefore, that the application of PICR is probably not yet appropriate for clinical decision making. The method for measuring PICR and our model for calculating % gliding were based on the assumption that the knee joint is primarily a joint with a single degree of freedom and a joint that rotates about a flexion/extension axis (represented 2-dimensionally by the PICR) and translates in the sagittal plane. The knee is actually a 3-dimensional joint that incorporates secondary rotations in the frontal (abduction/adduction) and transverse (axial rotation) planes of motion. The assumption that knee movements can be represented by general plane motion discounts potential effects of axial rotation (the "screw home mechanism") on the calculation of rolling and gliding. Changes in the screw home mechanism may account for the differences in rolling and gliding movements we observed. The evidence of whether differences occur in the screw home mechanism during NWB and WB movements, however, is conflicting.50,51
Our mathematical knee model for estimating joint surface rolling and gliding may also be limited because the geometric components of the model represent average joint surface geometry obtained from a limited number of subjects in 3 morphological studies,34–36 and we did not distinguish between the medial and lateral femoral condyles. The size and radii of curvature of the bony segments and joint surfaces comprising the knee joint vary among people.34–36 Nevertheless, several researchers52–54 have found that the radii of the posterior portions of the medial and lateral condyles that articulate with the tibia are not meaningfully different. Because movement and group interaction effects were present in our study, we believe our model was appropriate for addressing our goal of comparing average rolling and gliding movements between groups.
Some of our other measurements also contribute to limitations. Although skin markers are assumed to represent rigid body motion of underlying skeletal segments, it is well known that a violation of the rigid body assumption occurs with the use of skin markers in motion analysis.30,55,56 Less error, however, is typically introduced for sagittal-plane measurements at the knee than either frontal- or transverse-plane measurements, and marker placement methods do exist that minimize skin or soft tissue movement error.30 We attempted to minimize soft tissue movement error by modifying typical marker positions as recommended by Cappozzo et al.30 Furthermore, previous research33 has demonstrated high correlations (Pearson product moment coefficients [r] ranging from .78 to .88) in cadaver knees between ICR locations determined through use of skin markers with videographic motion analysis and through the use of bone markers with fluoroscopy. We therefore believe our methods were sound.
| Conclusion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionReferences |
|---|
| Footnotes |
|---|
The Washington University School of Medicine Institutional Review Board approved the protocol for this study.
The results of this study were presented in a poster at the 47th Annual Meeting of the Orthopaedic Research Society, February 25–28, 2001, San Francisco, Calif, and in an abstract in the Transactions of the 47th Annual Meeting, Orthopaedic Research Society.
This project was funded in part by NIH-NCMMR training grant #5T32HDO743405.
* Panasonic Broadcast & Television Systems Co, Franklin Park, IL 60131. 
Ariel Dynamics Inc, 6 Aliconte St, Trabuco Canyon, CA 92679.
Microsoft Corp, One Microsoft Way, Redmond, WA 98052-6399.
Motion Control, Division of Iomed Inc, 1290 West 2320 South, Ste A, Salt Lake City, UT 84119.
|| Bertec Corp, 819 Loch Lomond Ln, Worthington, OH 43085.
| References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionConclusionReferences |
|---|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
