There is evidence to suggest that navicular drop measures are associated with specific lower-extremity gait biomechanical parameters. The aim of this study was to examine the relationship between navicular drop and a) rearfoot eversion excursion, b) tibial internal rotation excursion, c) peak ankle inversion moment, and d) peak knee adduction moment during the stance phase of running. Sixteen able-bodied men having an average age of 28.1 (SD = 5.30) years, weight of 81.5 (SD = 10.40) kg, height of 179.1 (SD = 5.42) cm volunteered and ran barefoot at 170 steps/minute over a force plate. Navicular drop measures were negatively correlated with tibial internal rotation excursion (r = −0.53, P = .01) but not with rearfoot eversion excursion (r = −0.19; P = .23). Significant positive correlations were found between navicular drop and peak knee adduction moment (r = .62, P < .01) and peak ankle inversion moment (r = .60, P < .01). These findings suggest that a low navicular drop measure could be associated with increasing tibial rotation excursion while high navicular drop measure could be associated with increased peak ankle and knee joint moments. These findings indicate that measures of navicular drop explained between 28% and 38% of the variability for measures of tibial internal rotation excursion, peak knee adduction moment and peak ankle inversion moments.
Mansour Eslami, Mohsen Damavandi and Reed Ferber
Karen D. Kendall, Christie Schmidt and Reed Ferber
It has been theorized that a positive Trendelenburg test (TT) indicates weakness of the stance hip-abductor (HABD) musculature, results in contralateral pelvic drop, and represents impaired load transfer, which may contribute to low back pain. Few studies have tested whether weakness of the HABDs is directly related to the magnitude of pelvic drop (MPD).
To examine the relationship between HABD strength and MPD during the static TT and during walking for patients with nonspecific low back pain (NSLBP) and healthy controls (CON). A secondary purpose was to examine this relationship in NSLBP after a 3-wk HABD-strengthening program.
Clinical research laboratory.
20 (10 NSLBP and 10 CON).
Main Outcome Measures:
Normalized HABD strength, MPD during TT, and maximal pelvic frontal-plane excursion during walking.
At baseline, the NSLBP subjects were significantly weaker (31%; P = .03) than CON. No differences in maximal pelvic frontal-plane excursion (P = .72), right MPD (P = 1.00), or left MPD (P = .40) were measured between groups. During the static TT, nonsignificant correlations were found between left HABD strength and right MPD for NSLBP (r = −.32, P = .36) and CON (r = −.24, P = .48) and between right HABD strength and left MPD for NSLBP (r = −.24, P = .50) and CON (r = −.41, P = .22). Nonsignificant correlations were found between HABD strength and maximal pelvic frontal-plane excursion for NSLBP (r = −.04, P = .90) and CON (r = −.14, P = .68). After strengthening, NSLBP demonstrated significant increases in HABD strength (12%; P = .02), 48% reduction in pain, and no differences in MPD during static TT and maximal pelvic frontal-plane excursion compared with baseline.
HABD strength was poorly correlated to MPD during the static TT and during walking in CON and NSLBP. The results suggest that HABD strength may not be the only contributing factor in controlling pelvic stability, and the static TT has limited use as a measure of HABD function.
Christian A. Clermont, Sean T. Osis, Angkoon Phinyomark and Reed Ferber
Certain homogeneous running subgroups demonstrate distinct kinematic patterns in running; however, the running mechanics of competitive and recreational runners are not well understood. Therefore, the purpose of this study was to determine whether we could separate and classify competitive and recreational runners according to gait kinematics using multivariate analyses and a machine learning approach. Participants were allocated to the ‘competitive’ (n = 20) or ‘recreational’ group (n = 15) based on age, sex, and recent race performance. Three-dimensional (3D) kinematic data were collected during treadmill running at 2.7 m/s. A support vector machine (SVM) was used to determine if the groups were separable and classifiable based on kinematic time point variables as well as principal component (PC) scores. A cross-fold classification accuracy of 80% was found between groups using the top 5 ranked time point variables, and the groups could be separated with 100% cross-fold classification accuracy using the top 14 ranked PCs explaining 60.29% of the variance in the data. The features were primarily related to pelvic tilt, as well as knee flexion and ankle eversion in late stance. These results suggest that competitive and recreational runners have distinct, ‘typical’ running patterns that may help explain differences in injury mechanisms.
Ricky Watari, Blayne Hettinga, Sean Osis and Reed Ferber
The purpose of this study was to validate measures of vertical oscillation (VO) and ground contact time (GCT) derived from a commercially-available, torso-mounted accelerometer compared with single marker kinematics and kinetic ground reaction force (GRF) data. Twenty-two semi-elite runners ran on an instrumented treadmill while GRF data (1000 Hz) and three-dimensional kinematics (200 Hz) were collected for 60 s across 5 different running speeds ranging from 2.7 to 3.9 m/s. Measurement agreement was assessed by Bland-Altman plots with 95% limits of agreement and by concordance correlation coefficient (CCC). The accelerometer had excellent CCC agreement (> 0.97) with marker kinematics, but only moderate agreement, and overestimated measures between 16.27 mm to 17.56 mm compared with GRF VO measures. The GCT measures from the accelerometer had very good CCC agreement with GRF data, with less than 6 ms of mean bias at higher speeds. These results indicate a torsomounted accelerometer provides valid and accurate measures of torso-segment VO, but both a marker placed on the torso and the accelerometer yield systematic overestimations of center of mass VO. Measures of GCT from the accelerometer are valid when compared with GRF data, particularly at faster running speeds.
Alan Hreljac, Alan Arata, Reed Ferber, John A. Mercer and Brandi S. Row
Previous research has demonstrated that the preferred transition speed during human locomotion is the speed at which critical levels of ankle angular velocity and acceleration (in the dorsiflexor direction) are reached, leading to the hypothesis that gait transition occurs to alleviate muscular stress on the dorsiflexors. Furthermore, it has been shown that the metabolic cost of running at the preferred transition speed is greater than that of walking at that speed. This increase in energetic cost at gait transition has been hypothesized to occur due to a greater demand being placed on the larger muscles of the lower extremity when gait changes from a walk to a run. This hypothesis was tested by monitoring electromyographic (EMG) activity of the tibialis anterior, medial gastrocnemius, vastus lateralis, biceps femoris, and gluteus maximus while participants (6 M, 3 F) walked at speeds of 70, 80, 90, and 100% of their preferred transition speed, and ran at their preferred transition speed. The EMG activity of the tibialis anterior increased as walking speed increased, then decreased when gait changed to a run at the preferred transition speed. Concurrently, the EMG activity of all other muscles that were monitored increased with increasing walking speed, and at a greater rate when gait changed to a run at the preferred transition speed. The results of this study supported the hypothesis presented.
Karrie L. Hamstra-Wright, Burcu Aydemir, Jennifer Earl-Boehm, Lori Bolgla, Carolyn Emery and Reed Ferber
Hip- and knee-muscle-strengthening programs are effective in improving short-term patient-reported and disease-oriented outcomes in individuals with patellofemoral pain (PFP), but few to no data exist on moderate- to long-term postrehabilitative outcomes. The first purpose of the study was to assess differences in pain, function, strength, and core endurance in individuals with PFP before, after, and 6 mo after successful hip- or knee-muscle-strengthening rehabilitation. The second purpose was to prospectively follow these subjects for PFP recurrence at 6, 12, and 24 mo postrehabilitation.
For 24 mo postrehabilitation, 157 physically active subjects with PFP who reported treatment success were followed. At 6 mo postrehabilitation, pain, function, hip and knee strength, and core endurance were measured. At 6, 12, 18, and 24 mo, PFP recurrence was measured via electronic surveys.
Sixty-eight subjects (43%) returned to the laboratory at 6 mo. Regardless of rehabilitation program, subjects experienced significant improvements in pain and function, strength, and core endurance pre- to postrehabilitation and maintained improvements in pain and function 6 mo postrehabilitation (Visual Analog Scale/Pain—pre 5.12 ± 1.33, post 1.28 ± 1.14, 6 mo 1.68 ± 2.16 cm, P < .05; Anterior Knee Pain Scale/Function—pre 76.38 ± 8.42, post 92.77 ± 7.36, 6 mo 90.27 ± 9.46 points, P < .05). Over the 24 mo postrehabilitation, 5.10% of subjects who responded to the surveys reported PFP recurrence.
The findings support implementing a hip-or knee-muscle-strengthening program for the treatment of PFP. Both programs improve pain, function, strength, and core endurance in the short term with moderate- and long-term benefits of improved pain and function and low PFP recurrence.
Christian A. Clermont, Lauren C. Benson, W. Brent Edwards, Blayne A. Hettinga and Reed Ferber
The purpose of this study was to use wearable technology data to quantify alterations in subject-specific running patterns throughout a marathon race and to determine if runners could be clustered into subgroups based on similar trends in running gait alterations throughout the marathon. Using a wearable sensor, data were collected for cadence, braking, bounce, pelvic rotation, pelvic drop, and ground contact time for 27 runners. A composite index was calculated based on the “typical” data (4–14 km) for each runner and evaluated for 14 individual 2-km sections thereafter to detect “atypical” data (ie, higher indices). A cluster analysis assigned all runners to a subgroup based on similar trends in running alterations. Results indicated that the indices became significantly higher starting at 20 to 22 km. Cluster 1 exhibited lower indices than cluster 2 throughout the marathon, and the only significant difference in characteristics between clusters was that cluster 1 had a lower age–grade performance score than cluster 2. In summary, this study presented a novel method to investigate the effects of fatigue on running biomechanics using wearable technology in a real-world setting. Recreational runners with higher age–grade performance scores had less atypical running patterns throughout the marathon compared with runners with lower age–grade performance scores.