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It is widely accepted that the general process of aging can be reflected by changes in motor function. Typically, optimal performance of a given motor task is observed for healthy young adults with declines being observed for individuals at either end of the lifespan. This study was designed to examine differences in the average and variability (i.e., intraindividual variability) of chewing, simple reaction time, postural control, and walking responses. For this study, 15 healthy children, 15 young adults, and 15 older adults participated. Our results indicated the movement performance for the reaction time and postural sway followed a U shape with young adults having faster reaction times and decreased postural sway compared to the children and older adults. However, this pattern was not preserved across all motor tasks with no age differences emerging for (normalized) gait speed, while chewing rates followed a U-shaped curve with older adults and children chewing at faster rates. Taken together, these findings would indicate that the descriptive changes in motor function with aging are heavily influenced by the nature of the task being performed and are unlikely to follow a singular pattern.

sBiofeedback has been effectively implemented to improve the mediation and distribution of joint loads during gait, however, the inability to effectively coordinate lower limb movement by altering loading patterns may increase pathological stress and risk of injury and deleterious joint changes. This study examined the influence cueing an increase or decrease in lower extremity loading has on inter- and intralimb joint coordination during gait, applied herein for 12 persons following anterior cruciate ligament reconstruction across three loading conditions (control, high, and low). Visual biofeedback was presented on a screen via a force-measuring treadmill with targeted changes prescribed based on stride-to-stride peak vertical ground reaction forces bilaterally. The pattern and stability of coordination dynamics among each of the ankle, hip and knee joint pairs were assessed via discrete relative phase and cross-recurrence quantification analyses for each condition. High and low loading altered the pattern and stability of intralimb coordination; low loading led to decreased coordination stability (20° greater than control condition) and high loading resulted in a more tightly coupled coordination pattern (higher %CDET). With thoughtful consideration for movement control, biofeedback can be used to target mechanisms leading to long-term deleterious joint adaptations.

Autism spectrum disorder (ASD) is a complex diagnosis characterized primarily by persistent deficits in social communication/interaction and repetitive behavior patterns, interests, and/or activities. ASD is also characterized by various physiological and/or behavioral features that span sensory, neurological, and neuromotor function. Although problems with lower body coordination and control have been noted, little prior research has examined lower extremity strength and proprioception, a process requiring integration of sensorimotor information to locate body/limbs in space. We designed this study to compare lower limb proprioception and strength in adolescents with ASD and neurotypical controls. Adolescents diagnosed with ASD (n = 17) and matched controls (n = 17) performed ankle plantarflexion/dorsiflexion bilateral proprioception and strength tests on an isokinetic dynamometer. We assessed position-based proprioception using three targeted positions (5 and 20-degrees plantarflexion and 10-degrees dorsiflexion) and speed-based proprioception using two targeted speeds (60 and 120-degrees/second). We assessed strength at 60-degrees/second. Participants with ASD performed 1.3-times more poorly during plantarflexion position and 2-times more poorly during the speed-based proprioception tests compared to controls. Participants with ASD also exhibited a 40% reduction in plantarflexion strength compared to controls. These findings provide insight into mechanisms that underly the reduced coordination, aberrant gait mechanics, and coordination problems often seen in individuals with ASD, and the identification of these mechanisms now permits better targeting of rehabilitative goals in treatment programs.

Functional chewing patterns are achieved early in life prior to other motor skills like walking. Chewing seems to improve specific aspects of attention; however, there is limited research on chewing in dual motor tasks. This study examined relationships between chewing and secondary motor tasks in children. Sixteen typically developing children (13.1 ± 2.3 years) participated in finger tapping, simple reaction time, and walking while chewing at different speeds. The chewing rates varied when produced with a secondary motor task, especially for slow chewing and preferred chewing, and the secondary motor tasks were differentially influenced by the chewing. This relationship was not as strong as what has been reported in adults. It appears the neural oscillatory mechanisms involved in chewing and the secondary motor tasks may not be fully developed in children.

INTRODUCTION To determine whether individuals with a history of anterior cruciate ligament reconstruction (ACLR) exhibit altered neuromotor function compared to healthy controls. It was hypothesized that the ACLR group would have slower postural responses compared to healthy individuals of similar age. MATERIALS AND METHODS Sixteen adults with a unilateral ACLR and 16 matched healthy controls participated. General assessments of neuromotor function were gathered and included measures of reaction time (both seated and postural conditions), walking ability, balance, ankle ROM, proprioception, knee joint laxity, patellar tendon reflex latency, and quadriceps strength. Data were analyzed using mixed generalized linear models with between-subject (ie, controls, ACLR) and within-subject factors (ie, affected, unaffected limb). RESULTS Individuals with an ACLR exhibited a significant slowing of their postural reaction times compared to the control individuals. The ACLR group was slower under both the simple (ACLR: 484 ± 6.17 ms, control: 399 ± 1.95 ms) and choice reaction time conditions (ACLR: 550 ± 43 ms, control: 445 ± 43 ms). No other group differences were found in any of the other measures. CONCLUSION Overall, ACLR individuals had a reduced ability to respond quickly under more challenging postural conditions (ie, stepping response). This finding would indicate that the impact of an ACLR is not purely mechanical and restricted to the joint. Rather, injury and reconstruction of the ACL impact neural mechanisms, altering individuals' ability to respond under challenging balance tasks.

The best predictor of future injury is previous injury and this has not changed in a quarter century despite the introduction of evidence-based medicine and associated revisions to post-injury treatment and care. Nearly nine million sports-related injuries occur annually, and the majority of these require medical intervention prior to clearance for the athlete to return to play (RTP). Regardless of formal care, these athletes remain two to four times more likely to suffer a second injury for several years after RTP. In the case of children and young adults, this sets them up for a lifetime of negative health outcomes. Thus, the initial injury is the tipping point for a post-injury cascade of negative sequelae exposing athletes to more physical and psychological pain, higher medical costs, and greater risk of severe long-term negative health throughout their life. This chapter details the technologies and method that make up the automated Intelligent Phenotypic Plasticity Platform (IP3)-a revolutionary new approach to the current standard of post-injury care that identifies and targets deficits that underly second injury risk in sport. IP3 capitalizes on the biological concept of phenotypic plasticity (PP) to quantify an athlete's functional adaptability across different performance environments, and it is implemented in two distinct steps: (1) phenomic profiling and (2) precision treatment. Phenomic profiling indexes the fitness and subsequent phenotypic plasticity of an individual athlete, which drives the personalization of the precision treatment step. IP3 leverages mixed-reality technologies to present true-to-life environments that test the athlete's ability to adapt to dynamic stressors. The athlete's phenotypic plasticity profile is then used to drive a precision treatment that systematically stresses the athlete, via a combination of behavioral-based and genetic fuzzy system models, to optimally enhance the athlete's functional adaptability. IP3 is computationally light-weight and, through the integration with mixed-reality technologies, promotes real-time prediction, responsiveness, and adaptation. It is also the first ever phenotypic plasticity-based precision medicine platform, and the first precision sports medicine platform of any kind.

Aging is associated with physiological changes which can manifest as age-related slowing of voluntary movements. Dual-task conditions can magnify this slowing process in older adults. The current study describes healthy adult chewing patterns and examined effects of concurrent chewing on performance of simple reaction time (RT), finger tapping, and gait. Chewing rates were measured from electromyographic (EMG) activity from the masseter muscle. Stepping rates were calculated using accelerometers mounted on the lower trunk and leg. Tapping rates were collected using accelerometers secured to a fixed surface. Simple RT was attained from a purposely designed switch. Results demonstrated that older adults walked slower, tapped slower, and had slower reaction times compared to young individuals, however chew rates were similar. This dichotomy became more pronounced when motor tasks were performed at faster speeds, with the exception being chewing. Additionally, chewing altered performance of secondary motor tasks for all individuals. Strong coupling emerged between cyclical actions (i.e., chewing-gait and chewing-tapping), reflecting entrainment between the respective neural oscillators driving the actions. In contrast, RT responses slowed appreciably when chewing was performed concurrently, indicating an interference effect. Taken together, these results illustrate the contrasting effects of chewing on a secondary motor task and highlights bidirectional effects of dual tasking on performance.

(1) Background: Biomechanics during landing tasks, such as the kinematics and kinetics of the knee, are altered following anterior cruciate ligament (ACL) injury and reconstruction. These variables are recommended to assess prior to clearance for return to sport, but clinicians lack access to the current gold-standard laboratory-based assessment. Inertial sensors serve as a potential solution to provide a clinically feasible means to assess biomechanics and augment the return to sport testing. The purposes of this study were to (a) develop multi-sensor machine learning algorithms for predicting biomechanics and (b) quantify the accuracy of each algorithm. (2) Methods: 26 healthy young adults completed 8 trials of a double limb jump landing task. Peak vertical ground reaction force, peak knee flexion angle, peak knee extension moment, and peak sagittal knee power absorption were assessed using 3D motion capture and force plates. Shank- and thigh- mounted inertial sensors were used to collect data concurrently. Inertial data were submitted as inputs to single- and multiple- feature linear regressions to predict biomechanical variables in each limb. (3) Results: Multiple-feature models, particularly when an accelerometer and gyroscope were used together, were valid predictors of biomechanics (R2 = 0.68–0.94, normalized root mean square error = 4.6–10.2%). Single-feature models had decreased performance (R2 = 0.16–0.60, normalized root mean square error = 10.0–16.2%). (4) Conclusions: The combination of inertial sensors and machine learning provides a valid prediction of biomechanics during a double limb landing task. This is a feasible solution to assess biomechanics for both clinical and real-world settings outside the traditional biomechanics laboratory.

The development of stable postural control is characterized by changes in sway variability and periods of rapid reorganization of motor system components.The current study examined whether changing biomechanical and perceptual demands influences the postural control behavior during development.The center of pressure (COP) was assessed via a cross-sectional design. Data were collected from 48 females in three age groups (late childhood, mid-adolescence, and young adulthood) during four quiet stance conditions: (1) eyes open with feet apart, (2) eyes open with feet together, (3) eyes closed with feet apart, and (4) eyes closed with feet together. Linear measures included total path length of the COP and the mean/standard deviation of the overall COP position and speed. To characterize the sway patterns via nonlinear analyses, the speed and two-dimensional positional time series were submitted to sample entropy and Renyi entropy, respectively.The linear results indicated that the late childhood group displayed longer COP trajectories (p.001) and faster and more variable COP speed (p's.001). These results held for both the feet apart and feet together conditions, independent of vision. The nonlinear results indicated that the late childhood group exhibited less regularity, overall, in their COP sway position (i.e., Renyi entropy) compared to the two older groups in the feet apart condition (p's ≤ .041), and to the young adults in the feet together condition, independent of vision (p .001). However, the mid-adolescent group demonstrated greater regularity in their COP speed (i.e., sample entropy) when their eyes were closed compared to the other two groups, independent of stance (p's.05).The linear results support previous findings, while the nonlinear measures indicate sway characteristics that may provide a window into the development of underlying control processes that regulate quiet standing.

Biofeedback has recently been explored to target deviant lower extremity loading mechanics following anterior cruciate ligament reconstruction (ACLR) to mitigate the development of post traumatic osteoarthritis. The impact this feedback has on the structure of the stride interval dynamics—a barometer of gait system health—however, have yet to be examined. This study was designed to assess how feedback, used to alter lower-extremity loading during gait, affects the structure of stride interval variability by examining long-range stride-to-stride correlations during gait in those with unilateral ACLR. Twelve participants walked under three separate loading conditions: (1) control (i.e., no cue) (2) high loading, and (3) low loading. Baseline vertical ground reaction force (vGRF) data was used to calculate a target 5% change in vGRF for the appropriate loading condition (i.e., high loading was +5% vGRF, low loading was −5% vGRF). The target for the load condition was displayed on a screen along with real-time vGRF values, prescribing changes in stride-to-stride peak vertical ground reaction forces of each limb. From time-series of stride intervals (i.e., duration), we analyzed the mean and standard deviation of stride-to-stride variability and, via detrended fluctuation analysis (i.e., DFA α), temporal persistence for each feedback condition. Both the high and low loading conditions exhibited a change toward more temporally persistent stride intervals (high loading: α =0.92, low loading: α = 0.98) than walking under the control condition (α = 0.78; high vs. control: p = .026, low vs. control: p = .001). Overall, these results indicate that altering lower extremity load changes the temporal persistence of the stride internal dynamics in ACLR individuals, demonstrating the implications of the design of gait training interventions and the influence feedback has on movement strategies.