Journal of Applied Biomechanics最新文献

Foot strength is important for gait, balance, and function, but it is challenging to measure. Evidence explaining why strength differences exist between sitting and standing test positions is needed to improve clinical value. Observing changes in ground reaction force (Δ GRF) during strength testing may help explain these differences. Our purpose was to determine if Δ GRF differed between test positions, and if Δ GRF was associated with strength. Twenty healthy adults (x¯ = 24.7 y) were randomly assigned to a first test position, sitting or standing. With one foot on a force plate, subjects pressed down and pulled with their toes on a towel connected to a scale, for each test position. Paired t tests and Pearson correlation coefficients were used in analyses of strength and 3D Δ GRF outcomes. Mean peak foot strength and Δ GRFx (anterior-posterior direction) were greater in standing (P < .001). Correlations were strong between sitting and standing peak strength (r = .703) and between peak strength and Δ GRFx (r = .738) and Δ GRFz (superior-inferior) (r = .595) in standing. Greater strength production in standing, which was directly correlated to Δ GRF, was congruent with task demands and may reflect the importance of rearfoot stability during foot strength testing. From a clinical perspective, the standing test position is favored over sitting.

This study applied decision-tree (DT) machine learning models to determine whether this approach is more accurate when classifying slip outcome during walking, and to refine the cutoff thresholds of each slip type. Kinematic data of the heel were collected from 50 adults (23.1 [3.6] y) during 516 walking trials. The first DT model (DT1) was trained with heel slip distance and heel slip velocity as predictor variables; the second model (DT2) added heel slip acceleration as the third predictor variable. Walking trials were first classified as a no-slip, slip-recovery, or slip-fall outcome based on visual observation, and these classifications were used as response labels to train the DT models. Results indicated that both DT models yielded different thresholds in classifying slip outcomes and were similar to thresholds suggested in previous studies. However, both DT models resulted in 4.1% to 7.6% greater overall prediction accuracy compared with previously suggested thresholds, with DT2 generally performing better than DT1. Although the improved performance was offset by a ∼7% lower sensitivity when classifying no-slip outcomes and greater model complexity, future studies examining slip responses during gait should incorporate the thresholds derived from the DT2 model to most accurately classify the type of slip outcome.

Gait symmetry is often assumed in healthy individuals, yet functional asymmetries arise from biomechanical and neurophysiological factors. Although light upper body loading can improve walking performance, its effect on lower limb joint asymmetry remains unclear. This study examined how different loading conditions affect sagittal plane gait asymmetry at the hip, knee, and ankle. Twenty-two participants walked under 4 conditions: no weight, unilateral arm weight, bilateral arm weights, and waist weights each using 0.45-kg loads. Three-dimensional joint angles were normalized to 101 points across the gait cycle. Asymmetry was assessed using statistical parametric mapping and pointwise effect size. Two metrics were used: (1) temporal extent, defined as the percentage of the gait cycle with significant left-right differences (P < .05) and the percentage of the gait cycle with effect size >0.8 and (2) group-level prevalence, defined as the percentage of participants showing significant asymmetry at each time point. Significant asymmetries were observed across all joints and conditions, with hip and knee levels consistently exceeding those at the ankle. Effect size values often exceeded statistical thresholds, highlighting meaningful differences. Loading produced minimal systematic effects, though individual responses varied. Importantly, light arm weights did not increase asymmetry, supporting their use for gait enhancement.

Clarification of glenohumeral joint alignment changes during the late cocking phase may reveal the mechanisms of throwing injuries. This study aimed to determine the effect of shoulder external rotation on humeral head center deviation relative to the scapular glenoid. Twenty-eight baseball players participated. The anteroposterior deviation of the humeral head center relative to the glenoid (humeral head translation) and the distance between the humeral head and posterior glenoid rim perpendicular to the glenoid articular surface (posterior glenohumeral distance) were measured. Magnetic resonance imaging of the throwing shoulder was performed at 90° abduction with 90°, 100°, and 110° external rotation; for the nonthrowing shoulder, measurements were conducted at 90° and 100°. In humeral head translation, the posterior translation of the humeral head relative to the glenoid was significantly greater at 110° compared to 90° external rotation position (P = .003). Humeral head translation was associated with posterior glenohumeral distance at the 90° (β-coefficient = 0.649) and 100° (β-coefficient = 0.556) external rotation positions. Increased shoulder external rotation resulted in posterior translation of the humeral head and proximity between the humeral head and the posterior glenoid rim. The factors identified as contributing to posterior deviation of the humeral head may trigger throwing shoulder injuries during the late cocking phase.

Delayed-onset muscle soreness (DOMS) is a noninvasive pain model offering a unique opportunity to study trunk neuromuscular adaptations. While prior research has examined regional muscle activation in the lumbar region, the spatial distribution of median frequencies (MF) under DOMS has not been explored. This study investigated the effect of DOMS-induced pain on the spatial distribution of MF in the lumbar erector spinae muscles and its association with trunk force variability during submaximal contractions. Twenty healthy adults completed 2 laboratory sessions: 1 pain-free and 1 under low back DOMS. High-density surface electromyography was recorded bilaterally on the erector spinae during submaximal isometric trunk extensions. MF distribution was analyzed using centroid coordinates with and without DOMS. Force variability was also assessed. DOMS significantly increased perceived muscle pain and soreness in the lumbar region. It also caused a cranial and medial shift of the MF centroid, significant on 1 side of the trunk. However, force variability remained stable between conditions. These results suggest that DOMS induces regional adaptations in lumbar muscle MF. The spatial distribution of MF may serve as a novel and sensitive marker of neuromuscular adaptation to pain. The trunk system was able to maintain force steadiness despite pain and soreness.

It is unknown whether interlimb differences in gait mechanics affect the magnitude or distribution of tibiofemoral joint contact forces or whether load carriage increases potential effects of limb dominance. Thus, this study aimed to compare the effects of load carriage on total, medial, and lateral tibiofemoral joint contact force between the dominant and nondominant limbs. Twenty-four adults (12 women, 21 right-leg dominant) walked at 1.4 m·s-1 during 3 load carriage conditions (0%, 15%, and 30% body weight). Medial and lateral tibiofemoral joint contact forces were calculated during 5 stance phases for each limb in each condition. A 3 × 2 repeated-measures analysis of variance was used to compare the dominant and nondominant limbs across the 3 loading conditions. Peak tibiofemoral joint forces increased directly with load carriage (P < .001). The nondominant limb peak medial tibiofemoral joint contact force was greater than that of the dominant limb (P = .026), whereas dominant limb peak lateral tibiofemoral joint contact force was greater than that of the nondominant (P < .001) limb. Although the results were close to the minimal detectable difference, we concluded that the distribution of tibiofemoral joint contact force during load carriage may be influenced by limb dominance. These findings underscore the relevance of limb dominance as a consideration in research design and data interpretation.

The pelvis and trochanteric soft tissue stiffness influence hip impact force during falls. We examined potential relationships between the stiffness values acquired from different methodologies. Twenty-six individuals simulated sideways falls. During trials, force-deformation data of the trochanteric soft tissue were recorded, then fitted to polynomial and exponential functions. Stiffness was determined as a slope of the tangent line at maximum deformation (Ks_1st, Ks_2nd, and Ks_exp) and at 0.4 N (Ks_2nd_0.4 N, Ks_exp_0.4 N). Similarly, force-deformation data of the pelvis were fitted exponentially to determine the pelvis stiffness at peak impact force (Kb). We also used a clinical device to measure the trochanteric soft tissue stiffness (Ks_myoton). Correlation and regression analyses were performed. The Kb was correlated with Ks_1st and Ks_2nd (P < .05) and decreased 1.7 and 0.7 kN/m for every 1 kN/m increase in Ks_1st and Ks_2nd, respectively (R2 = .23 and R2 = .21), but no variables were correlated with the Ks_myoton (P > .05). When normalized, however, both Kb and Ks_myoton were correlated with Ks_1st and Ks_2nd (P < .05). These findings provide insights into hip impact dynamics, suggesting that trochanteric soft tissue stiffness measured with a clinical device may serve as a predictor of pelvis stiffness during falls.

This study examined the influence of lateral constraints and sex on walking in different settings. Thirty-eight adults (17 males: 25 [3] y, 21 females: 24 [4] y) walked overground for 20 m in open (no constraints), open pathway (defined by lines on the floor), and hallway (pathway defined by walls) settings at 3 speeds (slow, preferred, and fast). Inertial sensors recorded kinematics (Xsens Awinda, Movella) to calculate stride velocity, stride length (SL), cadence, and double support phase percentage. Stride velocity, SL, and cadence were also normalized to account for body size. Linear mixed models were used for statistical analysis (α = .05). No setting or setting by speed effects were found. Males had greater SL compared with females at preferred and fast speeds. Males had greater normalized SL compared with females at fast speeds. Females had greater cadence compared with males across conditions. Males had greater double support phase percentage compared with females at slow speeds. Wider hallways may allow for walking assessments generalizable to open settings. Considering sex differences in cadence at any speed, SL at preferred and fast speeds, normalized SL at fast speeds, and double support phase percentage at slow speeds may be valuable for interpreting walking assessments.

Inertial Measurement Units (IMUs) enable accurate estimation of anatomical joint angles but require a sensor-to-segment calibration. Literature has presented several algorithms that address this gap; however, adequately comparing calibration performance is not trivial. This study compares 3 calibration methods: N-pose calibration (NP), functional calibration (FC), and manual alignment (MA) to estimate 3D wrist joint angles during single-plane and multiplane tasks. Thirteen healthy participants were instrumented with IMUs and optical markers to compute the range of motion error (ε), root mean squared error, and offset between the joint angles from the optical reference and each IMU calibration (NP, FC, and MA) as dependent variables. We then performed 3-way repeated-measures analyses of variance on each dependent variable to evaluate interactions between calibrations, tasks, and joint axes. NP showed the worst root mean squared error (8.34° [7.41°]) performance in the calibration main effect (η2G = .095) and calibration × tasks interaction (η2G = .121). In an exploratory analysis, FC performed best (main effect root mean squared error = 6.52° [4.47°]) in the offset calibration × axes interaction in single-plane (η2G = .160) tasks. Therefore, we recommend FC to optimally perform wrist calibration and against NP. These findings are viable in aiding the development of portable IMU-based clinical motion-tracking devices.