Thomas S. Buchanan

Variation of muscle moment arms with elbow and forearm position

We hypothesized that the moment arms of muscles crossing the elbow vary substantially with forearm and elbow position and that these variations could be represented using a three-dimensional computer model. Flexion/extension and pronation/supination moment arms of the brachioradialis, biceps, brachialis, pronator teres, and triceps were calculated from measurements of tendon displacement and joint angle in two anatomic specimens and were estimated using a computer model of the elbow joint. The anatomical measurements revealed that the flexion/extension moment arms varied by at least 30% over a 95 degrees range of motion. The changes in flexion/extension moment arm magnitudes with elbow flexion angle were represented well by the computer model. The anatomical studies and the computer model demonstrate that the biceps flexion moment arm peaks in a more extended elbow position and has a larger peak when the forearm is supinated. Also, the peak biceps supination moment arm decreases as the elbow is extended. These results emphasize the need to account for the variation of muscle moment arms with elbow flexion and forearm position.

Effects of arm acceleration and behavioral conditions on the organization of postural adjustments during arm flexion

SummaryNine standing subjects performed unilateral arm flexion movements over an eight-fold range of speeds, under two behavioral conditions. In the visually-guided condition, a visual target informed subjects about the correct movement speed. Seven subjects also made movements of different speeds during a self-paced condition, without a visual target. Angular displacement and acceleration of the arm, and EMG activity from the hamstrings (HM), erector spinae (ES) and the anterior deltoid (AD) muscles were measured. The following results were observed. (1) Mean rectified amplitudes of EMG activity in HM and ES were typically correlated with the average arm acceleration and presumably the disturbance to posture and/or balance. HM and ES amplitudes were correlated for only six subjects. Functions relating the ratios of HM/ES EMG amplitudes to acceleration varied between subjects. (2) HM onset latencies were highly variable for slow movements and usually lagged movement. For movements above a threshold-like point in acceleration, HM latencies were correlated with arm acceleration and recruited before movement. ES latencies were constant for fast movements, and negatively correlated with acceleration for slower movements. (3) The recruitment order of HM and AD was influenced by the behavioral condition but not by arm acceleration for fast movements. HM and AD were recruited coincidentally for visually-guided movements, while for self-paced movements, HM was recruited before AD. We conclude that for the arm flexion task: (1) HM and ES are not tightly coupled; (2) both behavioral and mechanical conditions affect the recruitment of postural muscles; and (3) postural and focal components of the movement are probably organized by parallel processes.

The isometric functional capacity of muscles that cross the elbow

We hypothesized that muscles crossing the elbow have fundamental differences in their capacity for excursion, force generation, and moment generation due to differences in their architecture, moment arm, and the combination of their architecture and moment arm. Muscle fascicle length, sarcomere length, pennation angle, mass, and tendon displacement with elbow flexion were measured for the major elbow muscles in 10 upper extremity specimens. Optimal fascicle length, physiological cross-sectional area (PCSA), moment arm, operating range on the force-length curve, and moment-generating capacity were estimated from these data. Brachioradialis and pronator teres had the longest (17.7cm) and shortest (5.5cm) fascicles, respectively. Triceps brachii (combined heads) and brachioradialis had the greatest (14.9cm(2)) and smallest (1.2cm(2)) PCSAs, respectively. Despite a comparable fascicle length, long head of biceps brachii operates over a broader range of the force-length curve (length change=56% of optimal length, 12.8cm) than the long head of triceps brachii (length change=28% of optimal length, 12. 7cm) because of its larger moment arm (4.7cm vs. 2.3cm). Although brachioradialis has a small PCSA, it has a relatively large moment-generating capacity (6.8cm(3)) due to its large moment arm (average peak=7.7cm). These results emphasize the need to consider the interplay of architecture and moment arm when evaluating the functional capabilities of a muscle.

Laxity in healthy and osteoarthritic knees

OBJECTIVE Although it is a cause of osteoarthritis (OA) in animal models, laxity in human knee OA has been minimally evaluated. Ligaments become more compliant with age; whether this results in clinical laxity is not clear. In theory, laxity may predispose to OA and/or result from OA. Our goals were to examine the correlation of age and sex with knee laxity in control subjects without OA, compare laxity in uninvolved knees of OA patients with that in older control knees, and examine the relationship between specific features of OA and knee laxity. METHODS We assessed varus-valgus and anteroposterior laxity in 25 young control subjects, 24 older control subjects without clinical OA, radiographic OA, or a history of knee injury, and 164 patients with knee OA as determined by the presence of definite osteophytes. A device was designed to assess varus-valgus laxity under a constant varus or valgus load while maintaining a fixed knee flexion angle and thigh and ankle immobilization. Radiographic evaluations utilized protocols addressing position, beam alignment, magnification, and landmark definition; the semiflexed position was used, with fluoroscopic confirmation. RESULTS In the controls, women had greater varus-valgus laxity than did men (3.6 degrees versus 2.7 degrees; 95% confidence interval [95% CI] of difference 0.38, 1.56; P = 0.004), and laxity correlated modestly with age (r = 0.29, P = 0.04). Varus-valgus laxity was greater in the uninvolved knees of OA patients than in older control knees (4.9 degrees versus 3.4 degrees; 95% CI of difference 0.60, 2.24; P = 0.0006). In OA patients, varus-valgus laxity increased as joint space decreased (slope -0.34; 95% CI -0.48, -0.19; P < 0.0001) and was greater in knees with than in knees without bony attrition (5.3 degrees versus 4.5 degrees; 95% CI of difference 0.32, 1.27; P = 0.001). CONCLUSION Greater varus-valgus laxity in the uninvolved knees of OA patients versus older control knees and an age-related increase in varus-valgus laxity support the concept that some portion of the increased laxity of OA may predate disease. Loss of cartilage/bone height is associated with greater varus-valgus laxity. These results raise the possibility that varus-valgus laxity may increase the risk of knee OA and cyclically contribute to progression.

Ankle inversion injury and hypermobility: effect on hip and ankle muscle electromyography onset latency.

OBJECTIVE Changes in reflexes associated with chronically sprained ankles were examined by measuring the reflex response latency of hip and ankle muscles during instantaneous ankle/foot inversion. DESIGN Randomized trials. SETTING All studies were performed in the Research Department laboratories at a major rehabilitation center in a large metropolitan area. PATIENTS AND OTHER PARTICIPANTS Twenty subjects were assigned to 2 groups (normal and hypermobile) based on goniometry testing. Subjects were recruited from hospital and University staff and had a mean age of 31 +/- 5 years. OUTCOME MEASURES Subjects stood on a platform constructed such that either foot/ankle could be instantaneously inverted. Latency was measured by EMG surface electrodes placed over the right and left gluteus medius and peroneal muscles. Two-factor analysis of variance was calculated to determine significant muscle onset latency differences (p < .01) between groups. RESULTS Significant EMG latency differences were found in comparing right gluteus medius of the hypermobile group (127.35 +/- 6.02msec) with the normal group (150.49 +/- 6.49msec) during right ankle perturbation, and the left gluteus medius of the hypermobile group (120.71 +/- 6.16msec) with the normal group (136.24 +/- 5.88msec) during left ankle perturbation. CONCLUSIONS These data suggest that there is decreased latency of hip muscle activation after ankle inversion in the hypermobile population. In treating ankle instability, clinicians must decide to address the altered hip muscle recruitment pattern or accept this recruitment pattern as an injury-adaptive strategy and thus accept unknown long-term consequences of premature muscle activation (ie, possible articular predisposition to degenerative changes, altered joint reaction forces, and muscle imbalances).

High-arched runners exhibit increased leg stiffness compared to low-arched runners

Leg stiffness between high-arched (HA) and low-arched (LA) runners was compared. It was hypothesized that high-arched runners would exhibit increased leg stiffness, increased sagittal plane support moment, greater vertical loading rates, decreased knee flexion excursion and increased activation of the knee extensor musculature. Twenty high-arched and 20 low-arched subjects were included in this study. Leg stiffness, knee stiffness, vertical loading rate and lower extremity support moment were compared between groups. Electromyographic data were collected in an attempt to explain differences in leg stiffness between groups. High-arched subjects were found to have increased leg stiffness and vertical loading rate compared to low-arched runners. Support moment at the impact peak of the vertical ground reaction force was related to leg stiffness across all subjects. High-arched subjects demonstrated decreased knee flexion excursion during stance. Finally, high-arched subjects exhibited a significantly earlier onset of the vastus lateralis (VL) than the low-arched runners. Differences exist in leg stiffness and vertical loading rate between runners with different foot types. Differences in lower extremity kinetics in individuals with different foot types may have implications for new treatment strategies or preventative measures.

A model of load sharing between muscles and soft tissues at the human knee during static tasks.

In this study, we have subjects voluntarily generate various forces in a transverse plane just above their ankles. The contributions of their muscles and soft tissues to the support of the total external knee joint moment were determined by analyzing the experimental data using a biomechanical model of the knee. In this model, muscle forces were estimated using the recorded EMGs. To account for subject variability, various muscle parameters were adjusted using a nonlinear least-squares fit of the models estimated flexion and extension joint moments to those recorded externally. Using the estimated muscle forces, the contributions from the muscles and other soft tissues to the total joint moment were obtained. The results showed that muscles were primarily used to support flexion and extension loads at the knee, but in so doing, were able to support some part of the varus or valgus loads. However, soft tissue loading was still required. Soft tissues supported up to an average maximum of 83 percent of the external load in pure varus and valgus. Soft tissue loading in pure varus and valgus was less than 100 percent of the external load as the muscles, on average, were able to support 17 percent of the external load. This muscle support was by virtue of muscle cocontraction and/or specific muscle activation.

Mechanisms underlying quadriceps weakness in knee osteoarthritis.

PURPOSE To identify determinants of quadriceps weakness among persons with end-stage knee osteoarthritis (OA). METHODS One-hundred twenty-three individuals (mean age 64.9 +/- 8.5 yr) with Kellgren/Lawrence grade IV knee OA participated. Quadriceps strength (MVIC) and volitional muscle activation (CAR) were measured using a burst superimposition test. Muscle composition (lean muscle cross-sectional area (LMCSA) and fat CSA (FCSA)) were quantified using magnetic resonance imaging. Specific strength (MVIC/LMCSA) was computed. Interlimb differences were analyzed using paired-sample t-tests. Regression analysis was applied to identify determinants of MVIC. An alpha level of 0.05 was adopted. RESULTS The OA limb was significantly weaker, had lower CAR, and had smaller LMCSA than the contralateral limb. CAR explained 17% of the variance in the contralateral limbs MVIC compared with 40% in the OA limb. LMCSA explained 41% of the variance in the contralateral limbs MVIC compared with 27% in the OA limb. CONCLUSION Both reduced CAR and LMCSA contribute to muscle weakness in persons with knee OA. Similar to healthy elders, the best predictor of strength in the contralateral, nondiseased limb was largely determined by LMCSA, whereas CAR was found to be the primary determinant of strength in the OA limb. Deficits in CAR may undermine the effectiveness of volitional strengthening programs in targeting quadriceps weakness in the OA population.

A real-time EMG-driven virtual arm

An EMG-driven virtual arm is being developed in our laboratories for the purposes of studying neuromuscular control of arm movements. The virtual arm incorporates the major muscles spanning the elbow joint and is used to estimate tension developed by individual muscles based on recorded electromyograms (EMGs). It is able to estimate joint moments and the corresponding virtual movements, which are displayed in real-time on a computer screen. In addition, the virtual arm offers artificial control over a variety of physiological and environmental conditions. The virtual arm can be used to examine how the neuromuscular system compensates for the partial or total loss of a muscles ability to generate force as might result from trauma or pathology. The purpose of this paper is to describe the design objectives, fundamental components and implementation of our real-time, EMG-driven virtual arm.

Prediction of joint moments using a neural network model of muscle activations from EMG signals

Because the relationship between electromyographic (EMG) signals and muscle activations remains unpredictable, a new way to determine muscle activations from EMG signals by using a neural network is proposed and realized. Using a neural network to predict the muscle activations from EMG signals avoids establishing a complex mathematical model to express the muscle activation dynamics. The feed-forward neural network model of muscle activations applied here is composed of four layers and uses an adjusted back-propagation training algorithm. In this study, the basic back-propagation algorithm was not applicable, because muscle activation could not be measured, and hence the error between predicted activation and the real activation was not available. Thus, an adjusted back-propagation algorithm was developed. Joint torque at the elbow was calculated from the EMG signals of ten flexor and extensor muscles, using the neural network result of estimated activation of the muscles. Once muscle activations were obtained, Hill-type models were used to estimate muscle force. A musculoskeletal geometry model was then used to obtain moment arms, from which joint moments were determined and compared with measured values. The results show that this neural network model can be used to represent the relationship between EMG signals and joint moments well.