Journal of Applied Biomechanics最新文献

Electromechanical delay (EMD) of muscle is influenced in part by its in-series arrangement with connective tissue. Therefore, studying EMD might provide a better understanding of the muscle-connective tissue interaction. Here, EMD of the thoracic and lumbar erector spinae muscles were investigated under conditions that could influence muscle-connective tissue interaction. A total of 19 participants performed isometric back extension contractions in 3 different postures that influence lumbar spine angle: sitting, standing, and kneeling. They then performed a 15-minute dynamic stretching routine and repeated the standing contractions. Mean lumbar flexion angles of 0.5°, 9.9°, and 19.8° were adopted for standing, kneeling, and sitting, respectively. No statistically significant differences in the thoracic erector spinae EMD were found between the different postures. Lumbar erector spinae EMD was significantly longer in the sitting (94.1 ms) compared to the standing (69.9 ms) condition, with no differences compared to kneeling (79.7 ms). There were no statistically significant differences of the thoracic or lumbar erector spinae EMDs before and after dynamic stretching. These results suggest that dynamic stretching does not affect the mechanical behavior of the muscle-tendon-aponeurosis units in a way that alters force generation and transmission, but a sitting posture can alter how force is transmitted through the musculotendinous complex of the lumbar erector spinae.

In-lab, marker-based gait analyses may not represent real-world gait. Real-world gait analyses may be feasible using inertial measurement units (IMUs) in combination with open-source data processing pipelines (OpenSense). Before using OpenSense to study real-world gait, we must determine whether these methods estimate joint kinematics similarly to traditional marker-based motion capture (MoCap) and differentiate groups with clinically different gait mechanics. Healthy young and older adults and older adults with knee osteoarthritis completed this study. We captured MoCap and IMU data during overground walking at 2 speeds. MoCap and IMU kinematics were computed with OpenSim workflows. We tested whether sagittal kinematics differed between MoCap and IMU, whether tools detected between-group differences similarly, and whether kinematics differed between tools by speed. MoCap showed more anterior pelvic tilt (0%-100% stride) and joint flexion than IMU (hip: 0%-38% and 61%-100% stride; knee: 0%-38%, 58%-89%, and 95%-99% stride; and ankle: 6%-99% stride). There were no significant tool-by-group interactions. We found significant tool-by-speed interactions for all angles. While MoCap- and IMU-derived kinematics differed, the lack of tool-by-group interactions suggests consistent tracking across clinical cohorts. Results of the current study suggest that IMU-derived kinematics with OpenSense may enable reliable evaluation of gait in real-world settings.

The aim of this study was to test and adapt a treadmill-developed method for determination of inner-cycle parameters and sub-technique in cross-country roller ski skating for a field application. The method is based on detecting initial and final ground contact of poles and skis during cyclic movements. Eleven athletes skied 4 laps of 2.5 km at low- and high-endurance intensities, using 2 types of skis with different rolling coefficients. Participants were equipped with inertial measurement units attached to their wrists and skis, and insoles with pressure sensors and poles with force measurements were used as reference systems. The method based on inertial measurement units was able to detect >97% of the temporal events detected with the reference system. The inner-cycle temporal parameters had a precision ranging from 49 to 59 milliseconds, corresponding to 3.9% to 13.7% of the corresponding inner-cycle duration. Overall, this study showed good reliability of using inertial measurement units on athletes' wrists and skis to determine temporal events, inner-cycle parameters, and the performed sub-techniques in cross-country roller ski skating in field conditions.

Spatiotemporal gait kinematics and their variability are commonly assessed in clinical and laboratory settings to quantify fall risk. Although the Hawthorne effect, or modifications in participant behavior due to knowledge of being observed, has the potential to impact such assessments, it has received minimal attention in the study of gait-particularly gait variability. The purpose of this study was to quantify the Hawthorne effect on variability and central tendency measures of fall-related spatiotemporal gait parameters. Seventeen healthy young adults walked on a treadmill at a self-selected velocity for 2 minutes under covert evaluation (ie, without awareness of being evaluated) and 2 minutes under overt evaluation. The movement was recorded using motion capture technology, from which we calculated mean value and step-to-step variability (using standard deviation and mean absolute deviation) of step length, step width, percent double support, percent stance phase, and stride time. Although central tendencies were unaffected by evaluation type, four-of-five measures of variability were significantly lower during overt evaluation for at least one-of-two metrics. Our results suggest a Hawthorne effect on locomotor control. Researchers should be aware of this phenomenon when designing research studies and interpreting gait assessments.

Although the ability to recover balance in the lateral direction has important implications with regard to fall risk in older adults, the effect of visual input on balance recovery in response to lateral perturbation and the effect of age are not well studied. We investigated the effect of visual input on balance recovery response to unpredictable lateral surface perturbations and its age-related changes. Ten younger and 10 older healthy adults were compared during balance recovery trials performed with the eyes open and eyes closed (EC). Compared with younger adults, older adults showed increased electromyography (EMG) peak amplitude of the soleus and gluteus medius, reduced EMG burst duration of the gluteus maximus and medius, and increased body sway (SD of the body's center of mass acceleration) in EC. In addition, older adults exhibited a smaller % increase (EC-eyes open) of the ankle eversion angle, hip abduction torque, EMG burst duration of the fibularis longus, and a greater % increase of body sway. All kinematics, kinetics, and EMG variables were greater in EC compared with eyes open in both groups. In conclusion, the absence of visual input negatively affects the balance recovery mechanism more in older adults compared with younger adults.

Field-based tibial acceleration measurements are increasingly common but sampling frequencies vary between accelerometers. The purpose of this study was to determine the minimum sampling frequency needed for reliable and accurate measurement of peak axial and resultant tibial acceleration during running in the field. Tibial acceleration was measured at 7161 Hz in 19 healthy runners on concrete and grass. Acceleration data were down sampled to approximate previously used sampling frequencies. Peak axial and resultant tibial acceleration were calculated for each sampling frequency. The within-session reliability and accuracy of peak axial and resultant tibial accelerations were evaluated using intraclass correlation coefficients, mean differences, and 95% limits of agreements. Intraclass correlation coefficients greater than .9 indicated excellent within-session reliability for both peak axial and resultant tibial acceleration measured while running on concrete and grass. Peak axial and resultant tibial accelerations were 0.5 to 1.4 g lower and minimal detectable differences were up to 0.6 g higher at 102 Hz compared with higher sampling frequencies. We recommend a minimum sampling frequency of 199 Hz for accurate and reliable measurements of peak axial and resultant tibial acceleration in the field.

Many head acceleration events (HAEs) observed in youth football emanate from a practice environment. This study aimed to evaluate HAEs in youth football practice drills using a mouthpiece-based sensor, differentiating between inertial and direct HAEs. Head acceleration data were collected from athletes participating on 2 youth football teams (ages 11-13 y) using an instrumented mouthpiece-based sensor during all practice sessions in a single season. Video was recorded and analyzed to verify and assign HAEs to specific practice drill characteristics, including drill intensity, drill classification, and drill type. HAEs were quantified in terms of HAEs per athlete per minute and peak linear and rotational acceleration and rotational velocity. Mixed-effects models were used to evaluate the differences in kinematics, and generalized linear models were used to assess differences in HAE frequency between drill categories. A total of 3237 HAEs were verified and evaluated from 29 football athletes enrolled in this study. Head kinematics varied significantly between drill categorizations. HAEs collected at higher intensities resulted in significantly greater kinematics than lower-intensity drills. The results of this study add to the growing body of evidence informing evidence-based strategies to reduce head impact exposure and concussion risk in youth football practices.

This study assessed activity distribution among the hamstring muscles during the Nordic hamstring exercise (NHE). The objective was to compare muscle activity between and within muscles during the NHE to add insights in its underlying protective mechanism. Through multichannel electromyography, we measured muscle activity in male basketball players during the NHE. Electromyography was assessed at 15 locations: 5 for biceps femoris long head, 4 for semitendinosus, and 6 for semimembranosus. For each percent of the eccentric phase of the NHE, muscle activity was calculated for each electrode location within each hamstring muscle individually. To quantify whole muscle head activity, means and variances across electrodes within each muscle were calculated. Thirty-five noninjured participants were included (mean age, 18 [2] y; mass, 87 [12] kg; height, 192 [9] cm). Heterogeneous muscle activity was found between 38% and 62% and over the whole eccentric contraction phase within the semitendinosus and the semimembranosus, respectively. Muscle activity of the semitendinosus was significantly higher than that of the biceps femoris long head. During the NHE, the relative contribution of the semitendinosus is the highest among hamstring muscles. Its strong contribution may compensate for the biceps femoris long head, the most commonly injured hamstring muscle head.

There is limited research that directly compares the effect of reduced speed with reduced propulsive force production (PFP) on age-related gait changes. We aimed to determine how changes in the gait of older adults correlate with age, speed, or peak PFP over a 6-year span. We collected kinematics and kinetics of 17 older subjects at 2 time points. We determined which biomechanical variables changed significantly between visits and used linear regressions to determine whether combinations of self-selected walking speed, peak PFP, and age correlated to changes in these variables. We found a suite of gait-related changes that occurred in the 6-year period, in line with previous aging studies. Of the 10 significant changes, we found 2 with significant regressions. Self-selected walking speed was a significant indicator of step length, not peak PFP or age. Peak PFP was a significant indicator for knee flexion. None of the biomechanical changes were correlated to the chronological age of the subjects. Few gait parameters had a correlation to the independent variables, suggesting that changes in gait mechanics were not solely correlated to peak PFP, speed, and/or age. This study improves understanding of changes in ambulation that lead to age-related gait modifications.

Computational approaches for movement onset detection can standardize and automate analyses to improve repeatability, accessibility, and time efficiency. With the increasing interest in assessing time-varying biomechanical signals such as force-time recordings, there remains a need to investigate the recently adopted 5 times the standard deviation (5 × SD) threshold method. In addition, other employed methods and their variations such as the reverse scanning and first derivative methods have been scarcely evaluated. The aim of this study was to compare the 5 × SD threshold method, 3 variations of the reverse scanning method, and 5 variations of the first derivative method against manually selected onsets, in the countermovement jump and squat. Limits of agreement with respect to onsets, manually selected from unfiltered data, were best for the first derivative method using a 10-Hz low-pass filter (limits of agreement: -0.02 to 0.05 s and -0.07 to 0.11 s for the countermovement jump and squat, respectively). Thus, even when the onset of unfiltered data is of primary interest, filtering before calculating the first derivative is necessary as it reduces the amplification of high frequencies. The first derivative approach is also less susceptible to inherent variation during the quiet phase prior to the onset compared to the other approaches investigated.