Structural Integrity, Flexibility, and Timing: Introduction to a Special Issue on Resilience.

This introduction to a special issue of Nonlinear Dynamics, Psychology and Life Sciences on the topic of resilience discusses the contributing articles in terms of their flexibility in methods, models, scale, and contexts combined with their integrity in shared theoretical understanding and generative knowledge. The ubiquity of resilience is discussed, a feature of potentially any living or non-living system and substance. This breadth calls for a flexible set of models and methods, along with the quest for integrative theory to make resilience science more resilient. Since resilience involves the ability of a substance or system to persist, to repair or recover, and to evolve, any common theory would consider structural integrity (the ability to hold together), flexibility (the ability to adjust and return), time and timing. Nonlinear dynamical systems theory is proposed as the only scientific perspective capable of building this sort of common knowledge of a ubiquitous process involving these specific features. The synopsis of each article's contribution to the issue includes an analysis of the flexibility the article adds in terms of models, methods, scale, and applied context, along with the theoretical integrity produced with respect to these common features of resilient processes: flexibility, integrity, time, and timing.

Feasibility and Preliminary Effectiveness of an Online Meditation Intervention in Young Adults With Concussion History.

CONTEXT: Mindfulness interventions (yoga, meditation) in traumatic brain injury populations show promising improvements in injury outcomes. However, most studies include all injury severities and use in-person, general programming lacking accessibility and specificity to the nuance of concussion. Therefore, this study investigated the feasibility and preliminary effectiveness of an online, concussion-focused meditation intervention among young adults with a concussion history. DESIGN: Unblinded, single-arm, pilot intervention. METHODS: Fifteen young adults aged 18 to 30 with a concussion history within the past 5 years completed 10 to 20 minutes per day of online, guided meditations for 6 weeks. Feasibility was assessed using the Feasibility of Intervention Measure. Concussion symptoms were measured using the Rivermead Post-Concussion Symptom Questionnaire, perceived stress the Perceived Stress Scale-10, and mindfulness the Five Facet Mindfulness Questionnaire. Descriptive statistics described the study sample and determined intervention adherence and feasibility. Paired sample t tests were used to examine preintervention/postintervention changes in concussion symptoms, perceived stress, and mindfulness, with descriptive statistics further detailing significant t tests. RESULTS: Fifteen participants were enrolled, and 12 completed the intervention. The majority completed 5+ days per week of the meditations, and Feasibility of Intervention Measure (17.4 [1.8]) scores indicated high feasibility. Concussion symptom severity significantly decreased after completing the meditation intervention (11.3 [10.3]) compared with before the intervention (24.5 [17.2]; t[11] = 3.0, P = .01). The number of concussion symptoms reported as worse than before their concussion significantly decreased after completing the meditation intervention (2.7 [3.9]) compared with before the intervention (8.0 [5.7]; t[11] = 3.7, P = .004). Postintervention, 83.33% (n = 10) reported lower concussion symptom severity, and 75.00% (n = 9) reported less concussion symptoms as a mild, moderate, or severe problem (ie, worse than before injury). CONCLUSIONS: Findings suggest positive adherence and feasibility of the meditation intervention, with the majority reporting concussion symptom improvement postintervention. Future research is necessary to expand these pilot findings into a large trial investigating concussion-specific meditation programming.

Effect of sensor number and location on accelerometry-based vertical ground reaction force estimation during walking.

Knee osteoarthritis is a major cause of global disability and is a major cost for the healthcare system. Lower extremity loading is a determinant of knee osteoarthritis onset and progression; however, technology that assists rehabilitative clinicians in optimizing key metrics of lower extremity loading is significantly limited. The peak vertical component of the ground reaction force (vGRF) in the first 50% of stance is highly associated with biological and patient-reported outcomes linked to knee osteoarthritis symptoms. Monitoring and maintaining typical vGRF profiles may support healthy gait biomechanics and joint tissue loading to prevent the onset and progression of knee osteoarthritis. Yet, the optimal number of sensors and sensor placements for predicting accurate vGRF from accelerometry remains unknown. Our goals were to: 1) determine how many sensors and what sensor locations yielded the most accurate vGRF loading peak estimates during walking; and 2) characterize how prescribing different loading conditions affected vGRF loading peak estimates. We asked 20 young adult participants to wear 5 accelerometers on their waist, shanks, and feet and walk on a force-instrumented treadmill during control and targeted biofeedback conditions prompting 5% underloading and overloading vGRFs. We trained and tested machine learning models to estimate vGRF from the various sensor accelerometer inputs and identified which combinations were most accurate. We found that a neural network using one accelerometer at the waist yielded the most accurate loading peak vGRF estimates during walking, with average errors of 4.4% body weight. The waist-only configuration was able to distinguish between control and overloading conditions prescribed using biofeedback, matching measured vGRF outcomes. Including foot or shank acceleration signals in the model reduced accuracy, particularly for the overloading condition. Our results suggest that a system designed to monitor changes in walking vGRF or to deploy targeted biofeedback may only need a single accelerometer located at the waist for healthy participants.

Examining Patterns and Predictors of ADHD Teens' Skill-Learning Trajectories During Enhanced FOrward Concentration and Attention Learning (FOCAL+) Training.

OBJECTIVE: Examine patterns and predictors of skill learning during multisession Enhanced FOrward Concentration and Attention Learning (FOCAL+) training. BACKGROUND: FOCAL+ teaches teens to reduce the duration of off-road glances using real-time error learning. In a randomized controlled trial, teens with ADHD received five sessions of FOCAL+ training and demonstrated significant reductions in extended glances (>2-s) away from the roadway (i.e., long-glances) and a 40% reduced risk of a crash/near-crash event. Teens' improvement in limiting long-glances as assessed after each FOCAL+ training session has not been examined. METHOD: Licensed teen (ages 16-19) drivers with ADHD (n = 152) were randomly assigned to five sessions of either FOCAL+ or modified standard driver training. Teens completed driving simulation assessments at baseline, after each training session, and 1 month and 6 months posttraining. Naturalistic driving was monitored for one year. RESULTS: FOCAL+ training produced a 53% maximal reduction in long-glances during postsession simulated driving. The number of sessions needed to achieve maximum performance varied across participants. However, after five FOCAL+ training sessions, number of long-glances was comparable irrespective of when teens achieved their maximum performance. The magnitude of reduction in long-glances predicted levels of long-glances during simulated driving at 1 month and 6 months posttraining but not naturalistic driving outcomes. FOCAL+ training provided the most benefit during training to teens who were younger and had less driving experience. CONCLUSION: FOCAL+ training significantly reduces long-glances beginning at the 1st training session. APPLICATION: Providing five FOCAL+ training sessions early on during teen driving may maximize benefit.

Biopsychosocial Resilience through a Complex Adaptive Systems Lens: A Narrative Review of Nonlinear Modeling Approaches.

Human resilience is often considered as static traits using a reductionist approach. More recent work has demonstrated it to be a dynamic and emergent property of complex systems. This narrative review explores human resilience through a self-organizing framework with a specific emphasis on the application of nonlinear modeling approaches. Four classes of approaches are examined: univariate dynamics, bivariate coupling, topological modeling, and network modeling. Univariate dynamics capture the temporal structure and flexibility within a single time series, while bivariate coupling approaches quantify the interaction dynamics and coordination between two time series. Topological modeling identifies bifurcations and attractor dynamics as signals of critical transitions relative to emergence and system stability. Network modeling represents system structure with a focus on connectivity, flexibility, and system integrity. Applying a complex systems framework, this review provides insights into data modeling opportunities for characterizing important features of a system's capacity to bounce back and recover from stress. These characteristics are connected to meta-flexibility, which characterizes a system's adaptive responsiveness to stressors, including post-traumatic growth, and the relation between meta-flexibility and metastability is discussed. Overall, this review provides a foundation of tools for researchers interested in under-standing human resilience through a complex systems framework.

Executive Functioning as a Predictor of Adverse Driving Outcomes in Teen Drivers With ADHD.

OBJECTIVE: The present study examined the association between executive functioning (EF) and risky driving behaviors in teens with ADHD. METHOD: Teens diagnosed with ADHD (n = 179; Mage = 17.4 years) completed two 15-min drives in a fixed-base driving simulator. EF was assessed using parent- and self-report Behavior Rating Inventory of Executive Functioning (BRIEF-2), a temporal reproduction task, and a Go/No-Go task (GNG). Driving outcomes included known predictors of crashes: count of long (>2 s) off-road glances, standard deviation (SD) of lane position (SDLP), mean speed, and SD speed. Generalized linear mixed models, controlling for intelligence and driving experience, were conducted. RESULTS: Higher rates of GNG commission errors predicted higher rates of long off-road glances. Lower parent-rated EF and increased rates of GNG omission errors predicted SDLP. Higher rates of GNG commission errors also predicted faster average driving speed. CONCLUSION: Heterogeneity in EF is associated with differences in teen ADHD risky driving behaviors.

Gait Variability Structure Linked to Worse Cartilage Composition Post-ACL Reconstruction.

INTRODUCTION: Aberrant gait variability has been observed after anterior cruciate ligament reconstruction (ACLR), yet it remains unknown if gait variability is associated with early changes in cartilage composition linked to osteoarthritis development. Our purpose was to determine the association between femoral articular cartilage T1ρ magnetic resonance imaging relaxation times and gait variability. METHODS: T1ρ magnetic resonance imaging and gait kinematics were collected in 22 ACLR participants (13 women; 21 ± 4 yr old; 7.52 ± 1.43 months post-ACLR). Femoral articular cartilage from the ACLR and uninjured limbs were segmented into anterior, central, and posterior regions from the weight-bearing portions of the medial and lateral condyles. Mean T1ρ relaxation times were extracted from each region and interlimb ratios (ILR) were calculated (i.e., ACLR/uninjured limb). Greater T1ρ ILR values were interpreted as less proteoglycan density (worse cartilage composition) in the injured limb compared with the uninjured limb. Knee kinematics were collected at a self-selected comfortable walking speed on a treadmill with an eight-camera three-dimensional motion capture system. Frontal and sagittal plane kinematics were extracted, and sample entropy was used to calculate kinematic variability structure (KV structure ). Pearson's product-moment correlations were conducted to determine the associations between T1ρ and KV structure variables. RESULTS: Lesser frontal plane KV structure was associated with greater mean T1ρ ILR in the anterior lateral ( r = - 0.44, P = 0.04) and anterior medial condyles ( r = - 0.47, P = 0 .03). Lesser sagittal plane KV structure was associated with greater mean T1ρ ILR in the anterior lateral condyle ( r = - 0.47, P = 0.03). CONCLUSIONS: The association between less KV structure and worse femoral articular cartilage proteoglycan density suggests a link between less variable knee kinematics and deleterious changes joint tissue changes. The findings suggest that less knee kinematic variability structure is a mechanism linking aberrant gait to early osteoarthritis development.

Differences in Lower Extremity Coordination Patterns as a Function of Sports Specialization.

The practice of early sport specialization, defined as intense year-round training in a single sport at the exclusion of others, is increasing in youth athletics. Despite potential benefits, sport specialization may be detrimental to the health of young athletes, as specialization may increase the risk of musculoskeletal injuries-particularly overuse injuries. However, there remains limited knowledge about how sports specialization uniquely alters underlying sports-related motor behavior. The purpose of this study was to compare the variability of movement patterns exhibited by highly sports specialized youth athletes to that of nonspecialized athletes during performance of a sport-specific, virtual reality based cutting task. It was hypothesized that highly specialized athletes would display different patterns of movement coordination compared to nonspecialized athletes during both the run-up phase and cut-and-decelerate phase. In support of the hypothesis, specialized athletes exhibited both intra- and inter-limb coordination that were significantly different than unspecialized athletes. Overall, the results indicate that the highly specialized athletes tended to exhibit greater degrees of coordination but also the ability to break the coordinated patterns of joint angle changes to execute a cutting maneuver, which requires asymmetric demands on the lower extremities while planting on one leg and changing direction.

Movement Regularity Differentiates Specialized and Nonspecialized Athletes in a Virtual Reality Soccer Header Task.

BACKGROUND: Young athletes who specialize early in a single sport may subsequently be at increased risk of injury. While heightened injury risk has been theorized to be related to volume or length of exposure to a single sport, the development of unhealthy, homogenous movement patterns, and rigid neuromuscular control strategies may also be indicted. Unfortunately, traditional laboratory assessments have limited capability to expose such deficits due to the simplistic and constrained nature of laboratory measurement techniques and analyses. METHODS: To overcome limitations of prior studies, the authors proposed a soccer-specific virtual reality header assessment to characterize the generalized movement regularity of 44 young female athletes relative to their degree of sport specialization (high vs low). Participants also completed a traditional drop vertical jump assessment. RESULTS: During the virtual reality header assessment, significant differences in center of gravity sample entropy (a measure of movement regularity) were present between specialized (center of gravity sample entropy: mean = 0.08, SD = 0.02) and nonspecialized center of gravity sample entropy: mean = 0.10, SD = 0.03) groups. Specifically, specialized athletes exhibited more regular movement patterns during the soccer header than the nonspecialized athletes. However, no significant between-group differences were observed when comparing participants' center of gravity time series data from the drop vertical jump assessment. CONCLUSIONS: This pattern of altered movement strategy indicates that realistic, sport-specific virtual reality assessments may be uniquely beneficial in exposing overly rigid movement patterns of individuals who engage in repeated sport specialized practice.

Trial of Training to Reduce Driver Inattention in Teens with ADHD.

BACKGROUND: Teens with attention deficit-hyperactivity disorder (ADHD) are at increased risk for motor vehicle collisions. A computerized skills-training program to reduce long glances away from the roadway, a contributor to collision risk, may ameliorate driving risks among teens with ADHD. METHODS: We evaluated a computerized skills-training program designed to reduce long glances (lasting ≥2 seconds) away from the roadway in drivers 16 to 19 years of age with ADHD. Participants were randomly assigned in a 1:1 ratio to undergo either enhanced Focused Concentration and Attention Learning, a program that targets reduction in the number of long glances (intervention) or enhanced conventional driver's education (control). The primary outcomes were the number of long glances away from the roadway and the standard deviation of lane position, a measure of lateral movements away from the center of the lane, during two 15-minute simulated drives at baseline and at 1 month and 6 months after training. Secondary outcomes were the rates of long glances and collisions or near-collisions involving abrupt changes in vehicle momentum (g-force event), as assessed with in-vehicle recordings over the 1-year period after training. RESULTS: During simulated driving after training, participants in the intervention group had a mean of 16.5 long glances per drive at 1 month and 15.7 long glances per drive at 6 months, as compared with 28.0 and 27.0 long glances, respectively, in the control group (incidence rate ratio at 1 month, 0.64; 95% confidence interval [CI], 0.52 to 0.76; P<0.001; incidence rate ratio at 6 months, 0.64; 95% CI, 0.52 to 0.76; P<0.001). The standard deviation of lane position (in feet) was 0.98 SD at 1 month and 0.98 SD at 6 months in the intervention group, as compared with 1.20 SD and 1.20 SD, respectively, in the control group (difference at 1 month, -0.21 SD; 95% CI, -0.29 to -0.13; difference at 6 months, -0.22 SD; 95% CI, -0.31 to -0.13; P<0.001 for interaction for both comparisons). During real-world driving over the year after training, the rate of long glances per g-force event was 18.3% in the intervention group and 23.9% in the control group (relative risk, 0.76; 95% CI, 0.61 to 0.92); the rate of collision or near-collision per g-force event was 3.4% and 5.6%, respectively (relative risk, 0.60, 95% CI, 0.41 to 0.89). CONCLUSIONS: In teens with ADHD, a specially designed computerized simulated-driving program with feedback to reduce long glances away from the roadway reduced the frequency of long glances and lessened variation in lane position as compared with a control program. During real-world driving in the year after training, the rate of collisions and near-collisions was lower in the intervention group. (Funded by the National Institutes of Health; ClinicalTrials.gov number, NCT02848092.).

Active Warfighter Mental Health Lower in Mid-Career.

PURPOSE: The present study investigated Special Operations Forces (SOF) combat Servicemember mental health at different SOF career stages in association with resilience. METHODS: Fifty-eight SOF combat Service Members either entering SOF (career start; n=38) or multiple years with their SOF organization (mid-career; n=20) self-reported mild traumatic brain injury (TBI) history, resilience, subjective well-being, depression, anxiety, and posttraumatic stress. Poisson regression analyses were employed to test SOF career stage differences in each mental health symptom using resilience, while accounting for other pertinent military factors. RESULTS: There were significant interaction effects of SOF career stage and resilience on mental health symptoms. SOF career start combat Servicemembers endorsed lower depression and posttraumatic stress and higher subjective well-being with higher resilience, but these associations between resilience and mental health symptoms were not seen in SOF mid-career Servicemembers. CONCLUSIONS: Although preliminary, the adaptive association between resilience and mental health seemed to be blunted in combat Servicemembers having served multiple years in SOF. This information informs research to provide evaluation tools to support prophylactic performance and long-term health preservation in military populations.

Association Between Head Impact Biomechanics and Physical Load in College Football.

Head impacts and physical exertion are ubiquitous in American football, but the relationship between these factors is poorly understood across a competitive season or even within an individual session. Gameplay characteristics, including player position and session type, may contribute to these relationships but have not been prospectively examined. The current study aimed to determine if an association exists between head impact biomechanics and physical load metrics. We prospectively studied college football players during the 2017-2021 football seasons across representative playing positions (15 offensive and defensive linemen, 11 linebackers and tight ends, and 15 defensive backs, running backs, and receivers). Participants wore halters embedded with Catapult Vector GPS monitoring systems to quantify player load and participant helmets were equipped with the Head Impact Telemetry System to quantify head impact biomechanics and repetitive head impact exposure (RHIE). Generalized linear models and linear regression models were employed to analyze in-session and season-long outcomes, while addressing factors such as player position and session type on our data. Player load was associated with RHIE (p < 0.001). Season-long player load predicted season-long RHIE (R2 = 0.31; p < 0.001). Position group affected in-session player load (p = 0.025). Both player load and RHIE were greater in games than in practices (p < 0.001), and position group did not affect RHIE (p = 0.343). Physical load burden was associated with RHIE within sessions and across an entire season. Session type affected both RHIE and player load, while position group only affected player load. Our data point to tracking physical load burden as a potential proxy for monitoring anticipated RHIE during the season.

Warfighter Resilience.

PURPOSE: Our aim in this study was to psychometrically test resilience assessments (Ego Resiliency Scale [ER89], Connor-Davidson Resilience Scale [CD-RISC 25], Responses to Stressful Experiences Scale [RSES short-form]) and describe resilience levels in a Special Operations Forces (SOF) combat sample. METHODS: Fifty-eight SOF combat Servicemembers either entering SOF (career start; n = 38) or having served multiple years with their SOF organization (mid-career; n = 20) self-reported resilience, mild traumatic brain injury (mTBI) history, and total military service. RESULTS: All resilience metrics demonstrated acceptable internal consistency, but ceiling effects were found for CD-RISC and RSES scores. ER89 scores were moderate on average. ER89 scores were higher in SOF career start than mid-career Servicemembers (ηρ2 = 0.07) when accounting for the interaction between SOF career stage and total military service (ηρ2 = 0.07). DISCUSSION: SOF mid-career Servicemembers had similar ER89 resilience scores with more total military service. The SOF career start combat Servicemembers had higher ER89 measured resilience with less total military service only, potentially showing a protective effect of greater service before entering SOF. CONCLUSION: The ER89 may be a more optimal military resilience metric than the other metrics studied; longitudinal research on SOF combat Servicemember resilience is warranted.

Preliminary Report on the Train the Brain Project, Part II: Neuroplasticity of Augmented Neuromuscular Training and Improved Injury-Risk Biomechanics.

CONTEXT: Neuromuscular training (NMT) facilitates the acquisition of new movement patterns that reduce the anterior cruciate ligament injury risk. However, the neural mechanisms underlying these changes are unknown. OBJECTIVE: To determine the relationship between brain activation and biomechanical changes after NMT with biofeedback. DESIGN: Cohort study. SETTING: Research laboratory. PATIENTS OR OTHER PARTICIPANTS: Twenty female high school soccer athletes, with 10 in an augmented NMT group and 10 in a control (no training) group. MAIN OUTCOME MEASURE(S): Ten participants completed 6 weeks of NMT augmented with real-time biofeedback to reduce knee injury-risk movements, and 10 participants pursued no training. Augmented neuromuscular training (aNMT) was implemented with visual biofeedback that responded in real time to injury-risk biomechanical variables. A drop vertical jump with 3-dimensional motion capture was used to assess injury-risk neuromuscular changes before and after the 6-week intervention. Brain-activation changes were measured using functional magnetic resonance imaging during unilateral knee and multijoint motor tasks. RESULTS: After aNMT, sensory (precuneus), visual-spatial (lingual gyrus), and motor-planning (premotor) brain activity increased for knee-specific movement; sensorimotor cortex activity for multijoint movement decreased. The knee-abduction moment during landing also decreased (4.66 ± 5.45 newton meters; P = .02; Hedges g = 0.82) in the aNMT group but did not change in the control group (P > .05). The training-induced increased brain activity with isolated knee movement was associated with decreases in knee-abduction moment (r = 0.67; P = .036) and sensorimotor cortex activity for multijoint movement (r = 0.87; P = .001). No change in brain activity was observed in the control group (P > .05). CONCLUSIONS: The relationship between neural changes observed across tasks and reduced knee abduction suggests that aNMT facilitated recruitment of sensory integration centers to support reduced injury-risk mechanics and improve sensorimotor neural efficiency for multijoint control. Further research is warranted to determine if this training-related multimodal neuroplasticity enhances neuromuscular control during more complex sport-specific activities.

The relationship between resilience and neurophysiological stress in Special Operations Forces combat service members.

Military resilience research is increasing due to the growing literature associating resilience with stress adaptation. This study aimed to investigate which physiological stress adaptation components were associated with resilience in Special Operations Forces combat service members. Special Operations Forces combat service members (n = 117) self-reported resilience (ER89) and lifetime clinician-confirmed mild traumatic brain injury history. Participants also underwent transcranial Doppler ultrasonography to measure middle cerebral artery velocity during rest and a breath-holding task. Neither resilience nor mild traumatic brain injury history was significantly associated with middle cerebral artery velocity percent increase following breath-holding; younger Special Operations Forces combat service members had a higher percent increase in middle cerebral artery velocity following a breath-holding task. Resilience was negatively associated with time to return to baseline middle cerebral artery velocity following peak velocity; whereas, mild traumatic brain injury history did not have a significant association. The Special Operations Forces combat service members that scored higher in resilience tended to return to baseline middle cerebral artery velocity following peak velocity faster than their less resilient counterparts. More resilient Special Operations Forces combat service members recovered faster from physiological stress (breath-holding) than less resilient counterparts. This is the first study to investigate resilience and cerebrovascular stress response and recovery in this population. Our initial findings indicated that the Ego Resiliency Scale may be an optimal resilience psychometric and should be used to evaluate effective military resilience trainings, which aim to improve performance and mental health.

Phenomics in sport: Can emerging methodology drive advanced insights?

Methodologies in applied sport science have predominantly driven a reductionist grounding to component-specific mechanisms to drive athlete training and care. While linear mechanistic approaches provide useful insights, they have impeded progress in the development of more complex network physiology models that consider the temporal and spatial interactions of multiple factors within and across systems and subsystems. For this, a more sophisticated approach is needed and the development of such a methodological framework can be considered a Sport Grand Challenge. Specifically, a transdisciplinary phenomics-based scientific and modeling framework has merit. Phenomics is a relatively new area in human precision medicine, but it is also a developed area of research in the plant and evolutionary biology sciences. The convergence of innovative precision medicine, portable non-destructive measurement technologies, and advancements in modeling complex human behavior are central for the integration of phenomics into sport science. The approach enables application of concepts such as phenotypic fitness, plasticity, dose-response dynamics, critical windows, and multi-dimensional network models of behavior. In addition, profiles are grounded in indices of change, and models consider the athlete's performance or recovery trajectory as a function of their dynamic environment. This new framework is introduced across several example sport science domains for potential integration. Specific factors of emphasis are provided as potential candidate fitness variables and example profiles provide a generalizable modeling approach for precision training and care. Finally, considerations for the future are discussed, including scaling from individual athletes to teams and additional factors necessary for the successful implementation of phenomics.

Cueing Changes in Peak Vertical Ground Reaction Force to Improve Coordination Dynamics in Walking.

AbstractsBiofeedback 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.

The Intelligent Phenotypic Plasticity Platform (IP3) for Precision Medicine-Based Injury Prevention in Sport.

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.

The Effect of Navigation Demand on Decision Making in a Dynamic, Sport-Inspired Virtual Environment.

Athletes commonly make decisions about the passability of closing gaps when navigating sport environments. This study examined whether increased temporal pressure to arrive at a desired location modifies these decisions. Thirty participants navigated toward a waypoint in a virtual, sport-inspired environment. To do so, they had to decide whether they could pass through closing gaps of virtual humans (and take the shortest route) or steer around them (and take a longer route). The decision boundary of participants who were time pressured to arrive at a waypoint was biased toward end gaps of smaller sizes and was less reliably defined, resulting in a higher number of collisions. Effects of temporal pressure were minimized with experience in the experimental task. Results indicate that temporal pressure affects perceptual-motor processes supporting information pickup and shapes the information-action coupling that drives compliance with navigation demands. Theoretical and practical implications are discussed.

Combining Inertial Sensors and Machine Learning to Predict vGRF and Knee Biomechanics during a Double Limb Jump Landing Task.

(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.