Focus on modern approaches for sports medicine and performance

Objective: The development of objective quantitative tools for the assessment and monitoring of sports-related concussion is critical. Eye tracking is a novel tool that may provide suitable metrics. The aim of this review was to appraise current evidence for the use of eye tracking technology in sports-related concussion assessment and monitoring. Approach: A systematic literature review was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A search was run using Google Scholar, Microsoft Academic and PubMed for literature published between January 1980 and May 2018. Included were empirical research studies in English where at least 50% of the research participants were athletes, the participants were individuals with a diagnosis of concussion, and eye movements were measured using an eye tracking device. Main results: This systematic review integrates 21 publications on sports-related concussion and eye tracking technology, nine of which also qualified for the meta-analysis. Overall, the literature reported significant findings for variables in each of the four classes of eye tracking measurements (movement, position, count, and latency). Meta-comparison was made for seven variables for the acute concussions (the difference between the concussed and the control groups was significant for all of them) and one variable for the latent concussions (the difference was not significant). Significance: Most saccadic and pursuit deficits may be missed during clinical examination, and therefore eye tracking technology may be a useful and sensitive screening and monitoring tool for sports-related concussions. The inconsistencies between the eye movement metrics and methodology still make inferences challenging; however, using tasks that are closely related to brain areas involved in executive functions (such as memory-based saccade or antisaccade tasks) in the acute injury phase holds promise in differentiating between athletes who have a concussion compared to those who do not.

Obesity is a major health issue in both developed and developing countries. The balance between energy intake and exercise is important, and measurements of both energy intake and energy expenditure are required. Many studies have attempted to monitor energy intake via wearable technology, but no standard methods have yet been developed for this purpose. This is in marked contrast to the long history of measurement and estimation of energy expenditure. Indirect calorimetry is commonly used in the laboratory. Energy expenditure associated with daily activity is the most important measure, although a number of alternative measures have also been proposed. This mini-review discusses the current status of energy expenditure measurement.

Objective: Postural control deficits have been extensively reported following sport-related concussions. Concussed athletes demonstrate these deficits as early as 24 h post-concussion and may persist for up to six months. Many of these prior studies have included mixed samples with prior injury history that may affect the postural control data. The purpose of this investigation was to evaluate the effect of concussion history on postural control 24–48 h following sport-related concussion in Division I athletes. Approach: Twenty-eight Division I athletes (seven athlete controls (CON), seven no history (SRC0), seven with a previous concussion (SRC1), and seven with 2–3 concussions (SRC3) participated in this study. All participants were assessed within 24–48 h post-subsequent SRC and performed three trials of quiet stance in the eyes closed (EC) conditions for 30 s each on a force platform (1000 Hz). The data were analyzed with root mean square (RMS) and mean excursion velocity (MEV) in the anteroposterior (AP) and mediolateral (ML) directions. Two 3  ×  2 MANOVAs were run by direction for group comparisons. Main results: SRC2 had significantly greater RMS than CON, SRC0, and SRC1 in the AP direction and ML direction. SRC2 exhibited significantly greater AP and ML MEV than CON, SRC0, and SRC1. Significance: These results demonstrate that having 2–3 prior concussions negatively affects the postural system after a subsequent head injury. Sports medicine staff should approach the recovery process with caution with those that have a prior history of concussion, due to the negative effects that history of concussion has on postural control strategies.

Objective: The purpose of this study was to quantify the measurement error of 3D kinematic and kinetic measures during overground endurance running between two sessions separated by 48 h. Approach: Thirteen recreational runners were assessed on two occasions while running overground, over embedded force plates and through an array of 3D cameras. Main results: In the sagittal, frontal and transverse planes, over the entire stance phase, the typical error of kinematic variables ranged from 1.33°–6.16° for the hip, 1.38°–6.01° for the knee and 0.48°–7.36° for the ankle. Over the same time period and planes typical error of peak-joint moments ranged from 0.04–0.54 Nm · Kg⁻¹ for the hip, 0.06–0.37 Nm · Kg⁻¹ for the knee and 0.01–0.15 Nm · Kg⁻¹ for the ankle. Significance: Results suggest 3D kinematic and kinetic measures of the stance phase in overground-endurance running are reliable between sessions separated by 48 h. The measurement error reported here could inform sample-size estimates for future studies and provide smallest-detectable changes for the interpretation of interventions performed over a similar time scale.

Objectives: To evaluate the effects of ankle taping, bracing, and fibular reposition taping (FRT) on running biomechanics as measured with wearable sensors. Approach: A randomized crossover study design was employed as 12 young adults (six males, six females) with history of ankle sprain completed four 400 m runs at self-selected pace on an outdoor track. One of four conditions (control, taped, braced, FRT) was applied prior to each run. RunScribe^™ sensors were heel-mounted on each shoe and measured kinematic (maximum pronation velocity, pronation excursion), kinetic (braking and impact g) and spatiotemporal (cycle time, contact time, stride length, stride pace) variables. Main results: Compared to the control and FRT conditions, both the taped and braced conditions significantly restricted maximum pronation velocity (control: 767.8  ±  228.3° s⁻¹; FRT: 721.2  ±  213.6° s⁻¹; taped: 528.8  ±  193.6° s⁻¹; braced: 562.1  ±  178.3° s⁻¹) and pronation excursion (control: 17.1  ±  6.6°; FRT: 17.2  ±  6.6°; taped:11.9  ±  4.7°; braced: 12.9  ±  5.1°). Braking g were significantly higher in the control condition (12.1  ±  0.9 g) condition compared to the taped (11.6  ±  1.0 g) and braced (11.6  ±  1.2 g) conditions. Cycle time was significantly greater in the braced condition (677.8  ±  43.7 ms) compared to taped (669.3  ±  44.6 ms) and FRT (672.1  ±  44.2 ms) conditions. Significance: Ankle taping and bracing were shown to be comparable in decreasing ankle kinematics and kinetics, while FRT caused minimal changes in running biomechanics. Taping and bracing may be beneficial in stabilizing and protecting the ankle while FRT should not be used to restrict ankle motion during running.

Objective: Saccadic (fast) eye movements are a routine aspect of neurological examination and are a potential biomarker of mild traumatic brain injury (mTBI). Objective measurement of saccades has become a prominent focus of mTBI research, as eye movements may be a useful assessment tool for deficits in neural structures or processes. However, saccadic measurement within mobile infra-red (IR) eye-tracker raw data requires a valid algorithm. The objective of this study was to validate a velocity-based algorithm for saccade detection in IR eye-tracking raw data during walking (straight ahead and while turning) in people with mTBI and healthy controls. Approach: Eye-tracking via a mobile IR Tobii Pro Glasses 2 eye-tracker (100 Hz) was performed in people with mTBI (n  =  10) and healthy controls (n  =  10). Participants completed two walking tasks: straight walking (walking back and forth for 1 min over a 10 m distance), and walking and turning (turns course included 45°, 90° and 135° turns). Five trials per subject, for one-hundred total trials, were completed. A previously reported velocity-based saccade detection algorithm was adapted and validated by assessing agreement between algorithm saccade detections and the number of correct saccade detections determined from manual video inspection (ground truth reference). Main results: Compared with video inspection, the IR algorithm detected ~97% (n  =  4888) and ~95% (n  =  3699) of saccades made by people with mTBI and controls, respectively, with excellent agreement to the ground truth (intra-class correlation coefficient_2,1  =  .979 to .999). Significance: This study provides a simple yet highly robust algorithm for the processing of mobile eye-tracker raw data in mTBI and controls. Future studies may consider validating this algorithm with other IR eye-trackers and populations.

Objective: The present study aimed to assess if changes in speed and stroke parameters, as measured by an inertial sensor during a maximal effort swimming test, could provide an effective detection of anaerobic capacity in elite swimmers. Approach: Fourteen elite swimmers performed a 75 m maximal swimming test. Changes in speed and stroke parameters, estimated by a body-worn inertial sensor, were analysed to provide insight into stroke mechanics during swimming. Their relationships with the output of the Wingate Anaerobic Test were analysed. Best times in competition were also considered to assess swimmer’s performance. Main results: Mean power measured using the Wingate cycle ergometer test highly correlated with mean speed attained by the swimmers during the proposed 75 m swimming test (R range: .700–.809, p   <  .05). Mean power in the Wingate Anaerobic Test and mean speed in the 75 m swimming test highly correlated with best times attained by the swimmers (R range: .736–.855, p   <  .01; R range: .659–.952, p   <  .05, for Wingate and 75 m swimming test, respectively). Moreover, stroke variables were investigated: in this regard, a significant decrease in stroke rate and swimming speed and a significant increase in stroke length were observed between the first and the third lap (p   <  .01). Significance: The present in-water free swimming test provided insight into specific physiological/mechanical aspects of elite swimmers. The correlation of the swimming and the Wingate tests with swimmer’s performance in competition confirms that they both reflect the skills and anaerobic qualities a swimmer uses in a race. The wearable inertial sensor could represent a feasible solution to evaluate stroke parameters, allowing a timely follow-up of variations in swimming biomechanics along the course of the test and the identification of differences in biomechanical strategy between swimmers. This analysis is of great interest for swimmers and coaches to characterise swimmer’s technique weakness and strength, and to plan individual race pacing strategy.

Objective: Muscle volume (MV) analysis from magnetic resonance imaging (MRI) is time-intensive, and limited measurement reliability data are available. This study investigated a method to reduce lower limb MV analysis time demands, established reliability of these measurements, and applied the findings to quantify muscle size and symmetry in healthy adult males. Approach: Bilateral MRI images were acquired from 15 healthy males (age: 26.5  ±  4.6 years, height: 1.81  ±  0.09 m, body mass: 80.4  ±  12.4 kg) for the entire lower limb. In two participants, the individual gluteals, quadriceps, hamstrings, and triceps surae were manually outlined every 5 mm and MV calculated using 5, 10, 15, 20, 25, and 30 mm distances between images to determine an appropriate distance for reducing analysis time. For all 15 participants, 35 muscles in each limb were manually outlined every 15 mm for use in MV calculations. Reliability of muscle cross-sectional area (CSA) measurement was determined within- and between-sessions and MV measurement reliability determined between-sessions. Between-limb symmetry was calculated using symmetry indices. Main results: A 15 mm inter-slice distance was appropriate for measuring MV (mean difference compared to reference method: 0.7%  ±  0.7%). Between-session measurement reliability was good for MV (Typical Error preferred kicking limb (TE_P): 1.2%, non-preferred kicking limb (TE_NP): 0.8%) and CSA (TE_P: 3.4%  ±  2.9%, TE_NP: 3.2%  ±  1.9%) although CSA Typical Error was larger with increased between-session time (TE_P: 4.1%  ±  3.1%, TE_NP: 4.7%  ±  4.0%). Between-limb differences in MV were small (mean symmetry index: 0.4%  ±  4.1%). Absolute differences in individual MV were larger (mean: 12.6%  ±  2.6%), but representing muscles as functional anatomical groups showed smaller absolute between-limb differences (mean: 4.7%  ±  1.8%). Significance: MV analysis time demand can be reduced by increasing the distance between analysed MRI slices, although participant height, muscle length and muscle shape require consideration. Small between-limb muscle size differences have been reported in adult males.

Objective: To identify clinically significant postural control measures capable of distinguishing the performance of adolescents with concussion from uninjured controls. Approach: Fifteen adolescents with concussion (67% female; median age  =  16.3 years; tested 8  ±  4 d post-injury) and 31 controls (45% female; median age  =  15.2 years) completed a single/dual-task gait evaluation with a smartphone affixed to their lumbar spine, modified balance error scoring system (mBESS), and single/dual-task tandem gait test. Outcome measures were obtained via smartphone (single/dual-task gait speed, cadence, step length), mBESS (double/single/tandem errors), and tandem gait (single/dual-task time). We calculated area under the curve (AUC) values for each measure that demonstrated a significant difference between groups independently, and calculated a comprehensive AUC value for all measures combined. Main results: The concussion group walked significantly slower (mean  =  0.89  ±  0.15 versus 1.05  ±  0.15 m s⁻¹; p   =  0.002) and with significantly fewer steps per minute (median  =  103 [interquartile range  =  94–108] versus 116 [104–118] steps/minute; p   =  0.002) than the control group under single-task conditions. They also completed single-task (median  =  22.0 [16.6–24.2] versus 14.5 [12.4–15.5] s; p   <  0.001) and dual-task (median  =  30.0 [24.0–35.2] versus 18.6 [16.1–21.7] s; p   <  0.001) tandem gait tests significantly slower than controls. The AUC value for single-task gait velocity, single-task cadence, single-task tandem gait time, and dual-task tandem gait time indicated an excellent ability to distinguish between concussion and control groups (AUC  =  0.91, 95% CI  =  0.80–0.99). Significance: Smartphone-obtained gait measures and tandem gait times allowed for an excellent differentiation between adolescents with concussion versus control participants. This reinforces the need for multimodal approaches to postural control impairment recognition among adolescents with concussion.