Objective: This study aims to validate an instrumented dual-task (DT) assessment procedure based on smartphone-embedded sensors. Data processing algorithms were developed to extract relevant features, and ice hockey players were evaluated. Participants: In total, 114 Swiss elite ice hockey players. Design: Experimental study. Main Measures: Participants performed DT tests regularly during the season and within the days following a diagnosed concussion. The DT test consisted of static balance and self-paced walking, combined with counting backward by 3. In total, 265 DT tests were performed, including 38 tests between 1 day and 2 weeks after the 13 diagnosed concussions. Results: Cognitive abilities during gait were mainly affected after a concussion. A DT performance metric was defined based on features significantly associated with worsening DT performance after the concussion ( P < .001, effect size d = 1.50). Finally, a model was proposed to estimate the risk of concussion based on a DT test outcome. Conclusion: DT assessments can detect residual cognitive impairments even after other clinical symptoms have resolved. These tests offer medical staff objective insights, facilitating informed decision-making during the return-to-play process.

Background: Sport-related concussions are a public health concern and can lead to long-term health impairment. Nevertheless, assessing concussions in spots such as ice hockey can be challenging during games. Dual-task (DT) tests, quantifying interference between cognitive and motor performance, have been used to detect cognitive impairment after a concussion. Methods: in this work, 114 Swiss elite ice hockey players performed DT tests at regular interval during the season and within the days following a diagnosed concussion. The DT test consisted of a static balance and a self-paced walking, both combined with counting backward by 3. In total, 265 DT tests were performed, including 38 tests between 1 day and 2 weeks after the 15 diagnosed concussions. Results: Cognitive abilities during gait were mainly affected after a concussion. A DT performance metric was defined based on features significantly associated with worsening DT performance after the concussion (p< 0.001, effect size d = 1.50). Finally, an individual and a global model were proposed to estimate the risk of concussion based on a DT test outcome. Conclusion: These tests provide objective insights to the medical staff, ensuring a secure and trusted decision-making process when deciding if the player should be removed from the game for recovery. Dual-task tests could also improve the return to play evaluation by detecting remaining cognitive deficiencies even in the absence of symptoms. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by Innosuisse (grant number 100.098 IP-ICT) ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Our Institutional Ethics Committee previously approved the experiment (CCER-VD 2023-00039) and complied with the Declaration of Helsinki. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Abstract Background The aim of this study is to explore the effect of treadmill slope on ground reaction forces and local muscle oxygenation as putative limiting factors of peak oxygen uptake in graded maximal incremental running tests. Thirteen trained male runners completed five maximal incremental running tests on treadmill at − 15%, − 7.5%, 0%, 7.5% and 15% slopes while cardiorespiratory and local muscle oxygenation responses as well as ground reaction forces were continuously recorded. Blood lactate concentration and isometric knee extensor torque were measured before and after each test. Results Peak oxygen uptake was lower at − 15% slope compared to all other conditions (from − 10 to − 17% lower, p < 0.001), with no difference between − 7.5 and + 15% slope. Maximal heart rate and ventilation values were reached in all conditions. The negative external mechanical work increased from steep uphill to steep downhill slopes (from 6 to 92% of total external work) but was not correlated with the peak oxygen uptake reduction. Local muscle oxygenation remained higher in − 15% slope compared to level running (p = 0.003). Conclusions Similar peak oxygen uptake can be reached in downhill running up to − 7.5% slope. At more severe downhill slopes (i.e., − 15%), greater negative muscle work and limited local muscle deoxygenation occurred, even in subjects familiarized to downhill running, presumably preventing the achievement of similar to other condition’s peak oxygen uptake. Key Points Trained male runners can reach like level running V̇O2peak at moderate but not at severe negative slope. Negative external mechanical work increases with increasing negative slope. At maximal intensity Vastus Lateralis muscle oxygenation is higher in steep negative slope. Knee extensor isometric muscle torque is preserved after maximal level and uphill running, but reduced after downhill running, despite lower blood lactate. Progressive reduction of V̇O2 at maximal effort with increasing negative slope might be related to the metabolic consequences of increased lower limb negative external work (i.e., eccentric muscle actions).

EDITORIAL article Front. Sports Act. Living, 02 February 2024Sec. Elite Sports and Performance Enhancement Volume 6 - 2024 | https://doi.org/10.3389/fspor.2024.1372080

This case study aims to examine changes in the lower limb joint kinematic profile and performance stability induced by repeated ski runs in two world-class alpine skiers. Two Olympic medallist alpine skiers were tested during their slalom training, with continuous recording of right knee and hip angles, along with turn time and run time. The eight runs of the training session were analysed with linear mixed models. Results showed no effect of runs repetition on performance (i.e., run and turn time; P ≥ 0.279). There was no global effect of runs repetition on minimal and maximal angles for either the knee or the hip (P > 0.151). There was an interaction between run and leg for the maximal angle of both the knee and hip (P ≤ 0.047), which increased across runs for the outside leg and decreased for the inside leg. The maximal angular velocity for both the knee and hip increased with runs repetition in extension (P ≤ 0.028). There were no overall changes in maximal angular velocity in flexion with runs repetition (P ≥ 0.264), but there was an interaction between run and leg for the knee (P < 0.001) due to faster eccentric velocities across runs for the outside leg and slower velocities for the inside leg. In conclusion, the observed joint kinematic alterations without concomitant performance impairment support the concept of multiple movement strategies in athletes to achieve similar performance, especially under fatigue conditions.

The aim of this study was to adapt a treadmill-developed method for determination of inner-cycle parameters 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 four laps of 2.5 km at low and high endurance-intensity, using two types of skis with different rolling coefficients. Participants were equipped with inertial measurement units (IMUs) attached to their wrists and skis, while insoles with pressure sensors and poles with force measurements were used as reference systems. The method based on IMUs was able to detect more than 97% of the temporal events compared to the reference system. The inner-cycle temporal parameters had a precision ranging from 49 to 59 ms, corresponding to 3.9% to 13.7% of the corresponding inner-cycle duration. Overall, this study showed good reliability of using IMUs on athlete’s wrists and skis to determine temporal events, inner-cycle parameters and the performed sub-techniques in cross-country roller ski skating in field-conditions.

The objective of this study was to determine whether the relationships between energy cost of running (Cr) and running mechanics during downhill (DR), level (LR) and uphill (UR) running could be related to fitness level. Nineteen athletes performed four experimental tests on an instrumented treadmill: one maximal incremental test in LR, and three randomized running bouts at constant speed (10 km h −1 ) in LR, UR and DR (± 10% slope). Gas exchange, heart rate and ground reaction forces were collected during steady-state. Subjects were split into two groups using the median Cr for all participants. Contact time, duty factor, and positive external work correlated with Cr during UR (all, p < 0.05), while none of the mechanical variables correlated with Cr during LR and DR. Mechanical differences between the two groups were observed in UR only: contact time and step length were higher in the economical than in the non-economical group (both p < 0.031). This study shows that longer stance duration during UR contributes to lower energy expenditure and Cr (i.e., running economy improvement), which opens the way to optimize specific running training programs.

Balance impairment is frequent in people with multiple sclerosis (pwMS) and affects risk of falls and quality of life. By using inertial measurement units (IMUs) on the Single Leg Stance Test (SLS) we aimed to discriminate healthy controls (HC) from pwMS and detect differences in balance endurance and quality. Thirdly, we wanted to test the correlation between instrumented SLS parameters and self-reported measures of gait and balance. Fifty-five pwMS with mild (EDSS<4) and moderate disability (EDSS≥4) and 20 HC performed the SLS with 3 IMUs placed on the feet and sacrum and filled the Twelve Item Multiple Sclerosis Walking Scale (MSWS-12) questionnaire. A linear mixed model was used to compare differences in the automated balance measures. Balance duration was significantly longer in HC compared to pwMS (p < 0.001) and between the two disability groups (p < 0.001). Instrumented measures identified that trunk stability (normalized mediolateral and antero-posterior center of mass stability) had the strongest association with disability (R2 marginal 0.30, p < 0.001) and correlated well with MSWS-12 (R = 0.650, p < 0.001). PwMS tended to overestimate own balance compared to measured balance duration. The use of both self-reported and objective assessments from IMUs can secure the follow-up of balance in pwMS.

Feedback of power during running is a promising tool for training and determining pacing strategies. However, current power estimation methods show low validity and are not customized for running on different slopes. To address this issue, we developed three machine-learning models to estimate peak horizontal power for level, uphill, and downhill running using gait spatiotemporal parameters, accelerometer, and gyroscope signals extracted from foot-worn IMUs. The prediction was compared to reference horizontal power obtained during running on a treadmill with an embedded force plate. For each model, we trained an elastic net and a neural network and validated it with a dataset of 34 active adults across a range of speeds and slopes. For the uphill and level running, the concentric phase of the gait cycle was considered, and the neural network model led to the lowest error (median ± interquartile range) of 1.7% ± 12.5% and 3.2% ± 13.4%, respectively. The eccentric phase was considered relevant for downhill running, wherein the elastic net model provided the lowest error of 1.8% ± 14.1%. Results showed a similar performance across a range of different speed/slope running conditions. The findings highlighted the potential of using interpretable biomechanical features in machine learning models for the estimating horizontal power. The simplicity of the models makes them suitable for implementation on embedded systems with limited processing and energy storage capacity. The proposed method meets the requirements for applications needing accurate near real-time feedback and complements existing gait analysis algorithms based on foot-worn IMUs.

A spring mass model is often used to describe human running, allowing to understand the concept of elastic energy storage and restitution. The stiffness of the spring is a key parameter and different methods have been developed to estimate both the vertical and the leg stiffness components. Nevertheless, the validity and the range of application of these models are still debated. The aim of the present study was to compare three methods (i. e., Temporal, Kinetic and Kinematic-Kinetic) of stiffness determination. Twenty-nine healthy participants equipped with reflective markers performed 5-min running bouts at four running speeds and eight inclines on an instrumented treadmill surrounded by a tri-dimensional motion camera system. The three methods provided valid results among the different speeds, but the reference method (i. e., Kinematic-Kinetic) provided higher vertical stiffness and lower leg stiffness than the two other methods (both p<0.001). On inclined terrain, the method using temporal parameters provided non valid outcomes and should not be used. Finally, this study highlights that both the assumption of symmetry between compression and decompression phases or the estimation of the vertical displacement and changes in leg length are the major sources of errors when comparing different speeds or different slopes.

The aim of this study was to develop and validate a method using inertial measurements units (IMUs) to determine inner-cycle parameters (e.g., cycle, poles and skis contact, and swing time) and the main sub-techniques (i.e., G2, G3 and G4) in cross-country roller ski skating on a treadmill. The developed method is based on the detection of poles and skis initial and final contacts with the ground during the cyclic movements. Thirteen well-trained athletes skied at different combinations of speed (6–24 km∙h-1) and incline (2–14%) on a treadmill using the three different sub-techniques. They were equipped with IMUs attached to their wrists and skis. Their movements were tracked using reflective markers and a multiple camera infrared system. The IMU-based method was able to detect more than 99% of the temporal events. It calculated the inner-cycle temporal parameters with a precision ranging from 19 to 66 ms, corresponding to 3.0% to 7.8% of the corresponding inner-cycle duration. The obtained precision would likely allow differentiation of skiers on different performance levels and detection of technique changes due to fatigue. Overall, this laboratory validation provides interesting possibilities also for outdoor applications.

PURPOSE:To investigate the performance effects of video- and sensor-based feedback for implementing a terrain-specific micropacing strategy in cross-country (XC) skiing.METHODS:Following a simulated 10-km skating time trial (Race1) on snow, 26 national-level male XC skiers were randomly allocated into an intervention (n = 14) or control group (n = 12), before repeating the race (Race2) 2 days later. Between races, intervention received video- and sensor-based feedback through a theoretical lecture and a practical training session aiming to implement a terrain-specific micropacing strategy focusing on active power production over designated hilltops to save time in the subsequent downhill. The control group only received their overall results and performed a training session with matched training load.RESULTS:From Race1 to Race2, the intervention group increased the total variation of chest acceleration on all hilltops (P < .001) and reduced time compared with the control group in a specifically targeted downhill segment (mean group difference: -0.55 s; 95% confidence interval [CI], -0.9 to -0.19 s; P = .003), as well as in overall time spent in downhill (-14.4 s; 95% CI, -21.4 to -7.4 s; P < .001) and flat terrain (-6.5 s; 95% CI, -11.0 to -1.9 s; P = .006). No between-groups differences were found for either overall uphill terrain (-9.3 s; 95% CI, -31.2 to 13.2 s; P = .426) or total race time (-32.2 s; 95% CI, -100.2 to 35.9 s; P = .339).CONCLUSION:Targeted training combined with video- and sensor-based feedback led to a successful implementation of a terrain-specific micropacing strategy in XC skiing, which reduced the time spent in downhill and flat terrain for intervention compared with a control group. However, no change in overall performance was observed between the 2 groups of XC skiers.

The aim of this work was to determine whether wearable inertial measurement units (IMUs) could detect gait improvements across different disability groups of people with Multiple Sclerosis (pwMS) by the six-minute walk test (6MWT) during a rehabilitation stay in a specialized rehabilitation center. Forty-six pwMS and 20 healthy controls (HC) were included in the study. They performed the 6MWT with two inertial measurement units (IMUs) placed on the feet. Thirty-two of the pwMS were retested at the end of the stay. PwMS were divided in a mild-disability and a moderate-disability group. The 6MWT was divided in six sections of 1 min each for technical analysis, and linear mixed models were used for statistical analyses. The comparison between the two disability groups and HC highlighted significant differences for each gait parameter (all p < 0.001). The crossing effect between the test-retest and the two disability groups showed greater improvement for the moderate-disability group. Finally, the gait parameter with the higher effect size, allowing the best differentiation between the disability groups, was the foot flat ratio (R2 = 0.53). Gait analyses from wearable sensors identified different evolutions of gait patterns during the 6MWT in pwMS with different physical disability. The measured effect of a short-time rehabilitation on gait with 6MWT was higher for pwMS with higher degree of disability. Using IMUs in a clinical setting allowed to identify significant changes in inter-stride gait patterns. Wearable sensors and key parameters have the potential as useful clinical tools for focusing on gait in pwMS.

Objective: The aim of this study was to provide a new machine learning method to determine temporal events and inner-cycle parameters (e.g., cycle, pole and ski contact and swing time) in cross-country roller-ski skating on the field, using a single inertial measurement unit (IMU). Methods: The developed method is based on long short-term memory neural networks to detect the initial and final contact of the poles and skis with the ground during the cyclic movements. Eleven athletes skied four laps of 2.5 km at a low and high intensity using skis with two different rolling coefficients. They were equipped with IMUs attached to the upper back, lower back and to the sternum. Data from force insoles and force poles were used as the reference system. Results: The IMU placed on the upper back provided the best results, as the LSTM network was able to determine the temporal events with a mean error ranging from −1 to 11 ms and had a standard deviation (SD) of the error between 64 and 70 ms. The corresponding inner-cycle parameters were calculated with a mean error ranging from −11 to 12 ms and an SD between 66 and 74 ms. The method detected 95% of the events for the poles and 87% of the events for the skis. Conclusion: The proposed LSTM method provides a promising tool for assessing temporal events and inner-cycle phases in roller-ski skating, showing the potential of using a single IMU to estimate different spatiotemporal parameters of human locomotion.

The aim of this study was to provide a theoretical model to predict the vertical loading rate (VLR) at different slopes and speeds during incline running. Twenty-nine healthy subjects running at least once a week performed in a randomized order 4-min running trials on an instrumented treadmill at various speeds (8, 10, 12, and 14 km h−1) and slopes (− 20%, − 10%, − 5%, 0%, + 5%, + 10%, + 15%, + 20%). Heart rate, gas exchanges and ground reaction forces were recorded. The VLR was then calculated as the slope of the vertical force between 20 and 80% of the duration from initial foot contact to the impact peak. There was no difference in VLR between the four different uphill conditions at given running speeds, but it was reduced by 27% at 5% slope and by 54% at 10% slope for the same metabolic demand (similar $${\dot{\text{V}}\text{O}}_{{2}}$$ ), when compared to level running. The average VLR measured at maximal aerobic intensity during level running would be decreased by 52.7% at + 5%, by 63.0% at + 10%, and by 73.3% at + 15% slope. Moreover, VLR was dependent on the slope in downhill conditions. This study highlights the possibility to use uphill running to minimize rate of mechanical load (i.e., osteoarticular load) from foot impact on the ground and as a time-efficient exercise routine (i.e., same energy expenditure than in level running in less time).

Background:Alpine skiers typically train using repeated practice runs requiring high bursts of muscle activity but there is little field-based evidence characterizing neuromuscular function across successive runs. Purpose:To examine the impact of repeated ski runs on electromyographic activity (EMG) of the knee extensors and flexors in elite alpine skiers. Methods:Nineteen national team alpine skiers were tested during regular ski training [Slalom (SL), Giant Slalom (GS), Super Giant Slalom and Downhill (Speed)] for a total of 39 training sessions. The surface EMG of the vastus lateralis (VL), rectus femoris (RF), vastus medialis (VM), biceps femoris (BF) and semimembranosus/semitendinosus (SMST) muscles was continuously recorded along with right knee and hip angles. The EMG root mean square signal was normalized to a maximal voluntary contraction (%MVC). The first and fourth runs of the training session were compared. Results:There was no meaningful main effect of run on EMG relative activation time or mean power frequency beyond the skier's intrinsic variability. However, EMG activity of the vastii increased from the first to the fourth run in SL [VM, ~+3%MVC for IL and outside leg (OL), p = 0.035)], speed (VL, IL:+6%/OL:+11%, p = 0.015), and GS (VM, IL:0/OL:+7%, p < 0.001); the later with an interaction with leg (p < 0.001) due to a localized increase on the OL. The run time and turn time did not change from the first to the fourth run. There were no meaningful changes in angular velocities, amplitude of movement, or maximal and minimal angles. Conclusion:Neuromuscular activity remains highly stable in elite skiers with low variability across four runs.

Objectives: This study aimed to investigate air drag and lift during the in-run and flight phase of ski and snowboard slopestyle and big air, to allow more valid modeling of jumps and hence reduce injury risk. Design: We present an experimental, multiple single athlete study based on wind tunnel measurements of 4 skiers and 3 snowboarders. Methods: Measurements were carried out in a closed loop wind tunnel, measuring airflow speed and 3D forces acting on the athletes. Athletes performed trials in typical postures at 35, 60 and 85 km/h wearing slim-, regular-and wide fit apparel. Drag and lift area (c(D)A; c(L)A) were calculated and analyzed using linear and multiple regression to describe their dependencies on posture, apparel and speed. Results: cDA values were higher than earlier assumed and ranged from 0.3 to 0.95 m(2) for skiers and from 0.35 to 0.55 m(2) for snowboarders, primarily dominated by posture, and followed by apparel. cLA ranged from -0.1 to 0.45 m(2) for skiers and from 0.04 to 0.17 m(2) for snowboarders. To facilitate more valid jump modeling posture-and apparel-dependent formulations for air drag coefficients were provided and the consequences of sport spe-cific differences on modeling were highlighted. Conclusions: Applying the air drag coefficients and relationships determined in this study will help to improve validity of jump modeling in big air and slopestyle. The variability in aerodynamic forces in slopestyle and big air is caused by differences between sports, posture and apparel. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of Sports Medicine Australia.

Previous research has shown that friction between ski and snow can vary substantially due to changes in snow conditions. The variation of friction affects the speed a freestyle skier or snowboarder (athlete) reaches during the in-run of a jump. Athletes risk severe injuries if their take-off speed is not within the right margin to land in the “sweet spot” zone. To reduce the risk of injury, snow park designers and competition managers need to calculate the speed athletes reach during the in-run. However, despite multiple attempts over the last decades, to date no model can predict ski-snow friction from snow physical quantities. Hence, simulations of in-run speeds suffer from insufficient validity. For the first time, this work combines kinematic athlete data and comprehensive snow surface measurements to infer the coefficient of friction of freestyle skis and snowboards across a wide range of snow conditions. Athletes’ point mass kinematics were recorded at more than 200 straight gliding runs with differential global navigation satellite systems. The subjects’ air drag and lift were deployed from wind tunnel measurements. Along with the kinematic data and data from wind measurements, a mechanical model of the athlete was established to solve the equation of motion for the coefficient of friction between ski/snowboard and snow. The friction coefficients for ski (snowboard) ranged from 0.023 ± 0.006 (0.026 ± 0.008) to 0.139 ± 0.018 (0.143 ± 0.017) and could be explained well (Radj2 = 0.77) from the measured snow parameters using a multivariate statistical model. Our results provide a new quantitative tool for practitioners to predict the friction of skis and snowboard on snow of various conditions, which aims to increase athletes’ safety in slopestyle and big air.

The aim of this study was first to determine if level, uphill, and downhill energy cost of running (ECR) values were correlated at different slopes and for different running speeds, and second, to determine the influence of lower limb strength on ECR. Twenty-nine healthy subjects completed a randomized series of 4-min running bouts on an instrumented treadmill to determine their cardiorespiratory and mechanical (i.e., ground reaction forces) responses at different constant speeds (8, 10, 12, and 14 km·h −1 ) and different slopes (−20, −10, −5, 0, +5, +10, +15, and +20%). The subjects also performed a knee extensor (KE) strength assessment. Oxygen and energy costs of running values were correlated between all slopes by pooling all running speeds (all r 2 ≥ 0.27; p ≤ 0.021), except between the steepest uphill vs. level and the steepest downhill slope (i.e., +20% vs. 0% and −20% slopes; both p ≥ 0.214). When pooled across all running speeds, the ECR was inversely correlated with KE isometric maximal torque for the level and downhill running conditions (all r 2 ≥ 0.24; p ≤ 0.049) except for the steepest downhill slope (−20%), but not for any uphill slopes. The optimal downhill grade (i.e., lowest oxygen cost) varied between running speeds and ranged from −14% and −20% (all p < 0.001). The present results suggest that compared to level and shallow slopes, on steep slopes ~±20%, running energetics are determined by different factors (i.e., reduced bouncing mechanism, greater muscle strength for negative slopes, and cardiopulmonary fitness for positive slopes). On shallow negative slopes and during level running, ECR is related to KE strength.