, and approximately 75% were women. Nationally, about 2/3 of older individuals reporting knee pain are women. Age was not a significant predictor of pain level in this population.
lyzed as a pooled group.
The typical time for an individual to complete each step event in the protocol was about 4 seconds (not including the three second pause between events), with the time to complete the step-up and step-down phases being 1 - 1.5 seconds, and a 0.5 second one-legged stance phase (Figure 3). The muscle use pattern was similar in the majority of subjects. Maximal muscle effort in all four muscles typically peaked approximately half-way through the step-up and step-down phases. During the single legged stance phase, BF and Sr effort returned to close to resting levels, while VL and VM effort decreased substantially but typically remained well above resting level. VL and VM generally tracked each other closely throughout the events, and similarly, BF and Sr generally tracked each other closely, though at a level of effort which was typically one-half to one-third that of VL and VM.
Step-wise robust MM regression identified five parameters which were interpreted as significant predictors of self-reported knee pain level (Table 2). The most significant predictor (p = 0.00006) was the ratio of the biceps femoris to sartorius muscle effort (BF/Sr) when stepping down, with higher BF/Sr ratios being associated with higher pain levels. Interestingly, BF/Sr during the step-up phase was also found to be a significant predictor of knee pain (p = 0.001), however, for the step-up phase of the event, higher BF/Sr ratios were associated with lower knee pain levels. VL effort during the step-up phase (concentric contraction) relative to VL effort during the step-down phase (eccentric contraction) was found to be the second most significant predictor of knee pain (p = 0.0003). In individuals with minimal knee pain,
Table 2. Regression analysis on knee pain as a function of measured muscle ratios and body mass. N = 42 knees.
Figure 3. Typical muscle use pattern during the experimental procedure as assessed using VMG. Peak muscle force was generated by all four recorded muscles (VL, VM, BF, Sr) approximately halfway through the step-up and the step-down phases. VL and VM were found to track each other closely, as well as BF and Sr, however, BF and Sr effort levels were typically one-half to onethird that of the quadriceps muscles.
VL effort was seen to be substantially lower (by a factor of two) during step-up than during step-down (Figure 4), whereas those reporting a high level of knee pain demonstrated much higher VL activity during step-up than step-down. The VL/VM ratio was also observed to be a borderline significant predictor of knee pain, though only when the quadriceps were undergoing concentric contraction (p = 0.008). Lastly, the weakest predictor identified in the multiple step-wise regression was body mass (p = 0.009). The combination of the above identified muscle effort ratios along with body mass was sufficient to explain 40% of the variation in reported pain levels.
In this study we investigated the ability of VMG recording techniques to provide estimates of muscle effort during functional activity as a clinical means to identify muscle imbalances in individuals with low level knee pain. Our results provide confirming evidence for the importance of several muscle imbalances which have
Figure 4. Vastus lateralis effort as a function of reported knee pain level. (a) Concentric contraction; (b) Eccentric contraction. No significant effects of pain on VL effort during step-up and step-down activity were observed in this population.
previously been reported as contributing to knee pain, but we were also able to identify important muscle balance ratios which, to our knowledge, have not previously been reported in the context of knee pain.
4.1. VMG Performance
We evaluated the ability of VMG to track maximal muscle effort under 60˚/sec isokinetic contraction conditions and concluded that R2 values in the range of 0.75 were sufficient to justify use of VMG in this study. As most of the subjects completed the step-up phase in about 1-1 1/2 seconds, and the 20 - 25 cm step typically requires a range of motion of approximately 60˚ - 80˚, the 60˚/s testing conditions seems to have been appropriate. Quadriceps muscles generate their maximum force near 60˚ of flexion, and correspondingly, are less efficient at shorter or longer muscle lengths. Nonetheless, VMG appears to be capable of tracking the muscle force throughout this wide variation in muscle length. That the correlations between torque and VMG output were not higher may be the result of two factors not incorporated into these tests. Specifically, multiple quadriceps muscles contribute to knee extension, yet only the VL was evaluated here, though this was the muscle which we expected to come closest to being utilized at maximum dynamic contraction conditions given the study protocol. Inclusion of additional quadriceps muscles in the analysis would be straightforward from a recording perspective, but would require the development of an algorithm for determining how the individual muscle contributions should be combined to obtain an estimate of knee torque. In addition, the measured torque values were not converted to an estimate of muscle force by incorporating the kinematics of the knee joint. While the torque to muscle force relation is relatively flat in the region we analyzed (15˚ - 75˚) , such correction may serve to substantially improve the correlations.
4.2. Hamstring Hip-Abductor Ratios
One distinct advantage of VMG is that it can provide an absolute measure of muscle effort, thereby allowing direct comparison of the effort in complementary muscle pairs. Among the four muscles we were evaluating in this study, the observed tracking of VL and VM was expected, but the remarkably close tracking of BF with Sr was an unexpected observation. Being a relatively weak hip abductor the Sartorius is not commonly studied, however, from the perspective of VMG recording the Sartorius is a particularly convenient hip abductor to record from as it is readily accessible on the medial side of the mid-thigh. While the role of hip abductors stabilizing the pelvis to prevent medial compartment loading has previously been discussed, it was interesting to find that the BF to Sr ratio (during step-down) was the strongest predictor of knee pain in our study population. This would seem to indicate that the Sr is a good surrogate abductor to evaluate in the clinic, though further studies doing direct comparisons between the Sartorius and other hip abductors should be pursued.
We were also intrigued that the BF/Sr ratio during step-up was a significant predictor of knee pain, though in the reverse direction, that is, a higher BF/Sr ratio during step-up was associated with less pain. This observation would appear to be consistent with the co-contraction role of the hamstrings in opposing the forward motion of the tibia during quadriceps contraction, however, in no situation did we find the quadriceps/hamstring ratio to be a significant predictor of knee pain. This observation, therefore, needs further investigation. In addition, the fact that BF and Sr muscle efforts are consistently one-half to one-third those observed in the VL and VM is consistent with their much smaller size, though this observation also seems to deserve further investigation given the importance of their roles in maintaining muscle balance during knee motion.
4.3. VL-VM Ratio
Consistent with numerous reports, we found the VL/VM ratio to be a significant predictor of knee pain, suggesting that PFPS was a significant contributor to the knee pain experienced by this population. While PFPS is a condition commonly associated with young people who regularly participate in repetitive knee motion activities (running, cycling, swimming, etc.), PFPS is also associated with extended sitting, kneeling and repeated stair climbing, activities that are likely to be a significant aspect of daily living for our older study population. Here, we addressed the VL/VM ratio only from an amplitude perspective, though timing was implicitly incorporated as a result of our cueing the analysis off the rise and fall times of the VL muscle during step-up and step-down. Because the VL/VM ratio during step-up turned out to be a significant predictor of pain and, it would likely be worthwhile to reevaluate the data looking explicitly for VM firing delays during step-down to see if this may be a more robust predictor of knee pain.
A particularly interesting observation from our data set is the strong relationship between knee pain and the ratio of peak VL force during step-up to that generated during step-down, that is, the respective VL forces generated during concentric vs. eccentric contraction. This ratio was the second most significant factor identified in our analysis, and shows a remarkable range, from approximately 0.5, for those with minimal knee pain, to greater than 1.5 for those with high levels of knee pain. These results appear to be distinctly different from those reported by Hortobagyi, et al. . In this latter EMG study involving both stair climbing and stair descent, the VLcon/VLecc ratios were found to be, on average, remarkably similar between individuals with OA (1.4), older individuals with no knee pain (1.1), and healthy young individuals (1.6). However, such EMG results may arise due to the well know fact that EMG signals increase under conditions of muscle fatigue, and so EMG results can be difficult to interpret when subjects are challenged to perform activities requiring maximum muscle effort. While the importance of eccentric quadriceps training has been reported for the treatment of jumper’s knee , our data would seem to indicate that similar exercises may prove to be useful in the management of knee OA as well.
The VLcon/VLecc data can also be utilized to address the main hypothesis of this study, that is, whether the observed imbalances reflect a coping mechanism for reducing pain of motion, or whether the pain has arisen as a result of a maladapted muscle use pattern. In principle, such a determination would require a prospective study, however, our dose response data allows speculation on the consistency of the relationships between pain and the muscle forces being generated. Specifically, while we have shown that the VLcon/VLecc ratio is strongly associated with knee pain levels, it is evident in Figure 4 that neither concentric VL strength nor eccentric VL strength demonstrate any significant trend at increasing pain levels. Therefore, the significant increase in the VLcon/VLecc ratio which is observed appears to be arising from concomitant small increases in concentric strength and corresponding decreases in eccentric strength. This is a rather natural development as many, if not most, activities of daily living rely much more on concentric quadriceps activity than on eccentric quadriceps activity. We therefore suggest that our data is consistent with the observed imbalances representing a slow drift in strength among the various muscle groups, at least in part due to body weight gain, resulting in significant muscle force imbalances which then give rise to inappropriate knee loading patterns which results in a painful knee. That is, we suggest that our data lends support to the hypothesis that knee pain follows the development of muscle imbalances, correspondingly, the correction of the observed imbalances would be expected to alleviate the knee pain reported by this study population.
4.4. Limitations to the Study
As a correlation analysis, this study cannot, of course, identify the causal basis of knee pain; such a conclusion would require follow-up to specific muscle training interventions. The main goal, therefore, was to determine whether VMG provided results consistent with previous reports which have relied on dynamometry and/or EMG analysis, such that an appropriate intervention study could be undertaken. This raises the issue of the accuracy and reproducibility of the observed results. Previous work has shown that VMG recording reproducibility (intra-assay variability) is 10% - 15% for the muscles utilized in this study; nonetheless, with only 42 painful knees available for analysis, a multiple regression approach presents significant challenges. To minimize the risk of over interpreting the data set, we incorporated three quality control procedures; first, we utilized a stepwise regression approach, second, we utilized robust M-M regression to preclude spurious correlations, and finally, we set our significance value at a relatively high level (p = 0.01). Three of our observed correlations were well below this threshold, though two (VL/VM ratio and body mass) were of borderline statistical significance. A much larger study, in particular, one which included a larger range of pain levels, would be necessary to clarify the roles of these various muscle imbalances in the development of knee OA.
5. SUMMARY AND CONCLUSIONS
VMG is a relatively quick, and accurate, means to assess muscle effort and identify muscle force imbalances during dynamic functional activities involving both concentric and eccentric muscle contractions. VMG analysis of individuals with relatively low level knee pain (≤6 on a 10 point scale) has allowed isolation of several knee muscle imbalances associated with self-reported pain, in particular, the biceps femoris to Sartorius ratio, the vastus lateralis to vastus medialis ratio, and the vastus lateralis force ratio in concentric vs. eccentric contraction. These muscle imbalances, when combined with body weight, were found to be sufficient to explain 40% of the variation in the self-reported pain levels in a population of 35 - 85 year old men and women.
Because there is no evidence of physical joint damage in close to 75% of individuals with knee pain, it is reasonable to assume that joint misuse plays a significant role in the etiology of the reported pain. Correspondingly, the ability to identify knee muscle misuse patterns which can be readily corrected through exercise or behavioral changes could provide a simple and effective means to ameliorate knee pain and preclude progressive damage that would eventually result in corrective surgery and/or eventual knee replacement. This study provides confirmation that VMG analysis may be capable of providing this capability in the clinic.
This study was supported in part by the Clinical Science and Engineering Research Center at Binghamton University, the Southern Tier Center on Aging, and the Center for Advanced Sensor Technology at Stony Brook University. We would like to thank Swapan Mookerjee, Matt McMahon, Jason Cole, Sree Koneru, Amy Chaffee, Tim Cortesi, and Chuck Schwerin for their assistance in the manuscript preparation.