Validity and Reliability of the Orthelligent Pro Sensor for Measuring Single-Leg Vertical Jump Height in Healthy Athletic Adults.

The Orthelligent Pro sensor is a practicable, portable measuring instrument. This study assessed the validity and reliability of this sensor in measuring single-leg countermovement jumps. Fifty healthy athletic adults participated in two measurement sessions a week apart in time. They performed single-leg countermovement jumps on the force plate while wearing the Orthelligent Pro sensor on their lower leg. During the first measurement session, Tester 1 invited the participants to make three single-leg countermovement jumps; subsequently, Tester 2 did the same. For assessing the sensor's intratester reliability, Tester 1 again invited the participants to make three single-leg countermovement jumps during the second measurement session. The sensor's validity was assessed by using the force plate results as the gold standard. To determinate the agreement between two measurements, Bland-Altman plots were created. The intertester reliability (ICC = 0.99; 0.97) and intratester reliability (ICC = 0.96; 0.82) were both excellent. The validity calculated (i) on the basis of the mean value of three jumps and (ii) on the basis of the maximum value of three jumps was very high, but it showed a systematic error. Taking this error into account, physiotherapists can use the Orthelligent Pro sensor as a valid and reliable instrument for measuring the jump height of countermovement jumps.

Exploring sex differences in blood-based biomarkers following exhaustive exercise using bioinformatics analysis.

This study examined the acute effects of exercise testing on immunology markers, established blood-based biomarkers, and questionnaires in endurance athletes, with a focus on biological sex differences. Twenty-four healthy endurance-trained participants (16 men, age: 29.2± 7.6 years, maximal oxygen uptake ( V ˙ O 2 max ): 59.4 ± 7.5 ml · min-1 · kg-1; 8 women, age: 26.8 ± 6.1 years, V ˙ O 2 max : 52.9 ± 3.1 ml · min-1 · kg-1) completed an incremental submaximal exercise test and a ramp test. The study employed exploratory bioinformatics analysis: mixed ANOVA, k-means clustering, and uniform manifold approximation and projection, to assess the effects of exhaustive exercise on biomarkers and questionnaires. Significant increases in biomarkers (lymphocytes, platelets, procalcitonin, hemoglobin, hematocrit, red blood cells, cell-free DNA (cfDNA)) and fatigue were observed post-exercise. Furthermore, differences pre- to post-exercise were observed in cytokines, cfDNA, and other blood biomarkers between male and female participants. Three distinct groups of athletes with differing proportions of females (Cluster 1: 100% female, Cluster 2: 85% male, Cluster 3: 37.5% female and 65.5% male) were identified with k-means clustering. Specific biomarkers (e.g., interleukin-2 (IL-2), IL-10, and IL-13, as well as cfDNA) served as primary markers for each cluster, potentially informing individualized exercise responses. In conclusion, our study identified exercise-sensitive biomarkers and provides valuable insights into the relationships between biological sex and biomarker responses.

Kinematical effects of rifle carriage on roller skiing in well-trained female and male biathletes.

PURPOSE: This study aimed to investigate how rifle carriage and skiing speed during biathlon roller skiing affect range of motion (ROM) in joint angles and equipment (skis and poles), the vertical distance between shoulders and treadmill (vertdist ), as well as possible sex differences associated with rifle carriage. METHODS: Fourteen biathletes (6 women, 8 men) roller-skied on a treadmill at submaximal and simulated race speeds, with (WR) and without (NR) a rifle, using gears 3 and 2. Kinematical data for the whole body, poles, roller-skis, rifle, and treadmill were monitored using a 3D motion capture system. Movements determined as flexion/extension (x), abduction/adduction (y), and/or internal/external rotation (z) were analyzed for the hip, shoulder, thorax, knee, ankle, elbow, poles, and roller skis. ROM (the difference between maximal and minimal angles) in joints and equipment, and vertdist were analyzed over six skiing cycles during each condition (WR and NR) and speed. RESULTS: The maximal vertdist was lower for WR compared with NR (gear 3: 1.53 ± 0.06 vs 1.54 ± 0.06 m; gear 2: 1.49 ± 0.06 vs 1.51 ± 0.06 m; both p < 0.001). ROM in the upper body was altered when roller skiing WR (movements decreased in thorax and shoulder (x) and increased in elbow (only gear 3) (x), thorax (only gear 2), and shoulder (y) and (z); all p < 0.05) and increased with speed, without differences between sexes (p > 0.05). CONCLUSION: Since rifle carriage and speed appear to affect the kinematics of roller skiing, coaches, and biathletes are advised to perform skiing technique training under competition-like conditions (i.e., at race speeds while carrying the rifle).

Technique-Dependent Relationship between Local Ski Bending Curvature, Roll Angle and Radial Force in Alpine Skiing.

Skiing technique, and performance are impacted by the interplay between ski and snow. The resulting deformation characteristics of the ski, both temporally and segmentally, are indicative of the unique multi-faceted nature of this process. Recently, a PyzoFlex® ski prototype was presented for measuring the local ski curvature (w″), demonstrating high reliability and validity. The value of w″ increases as a result of enlargement of the roll angle (RA) and the radial force (RF) and consequently minimizes the radius of the turn, preventing skidding. This study aims to analyze segmental w″ differences along the ski, as well as to investigate the relationship among segmental w″, RA, and RF for both the inner and outer skis and for different skiing techniques (carving and parallel ski steering). A skier performed 24 carving and 24 parallel ski steering turns, during which a sensor insole was placed in the boot to determine RA and RF, and six PyzoFlex® sensors were used to measure the w″ progression along the left ski (w1-6″). All data were time normalized over a left-right turn combination. Correlation analysis using Pearson's correlation coefficient (r) was conducted on the mean values of RA, RF, and segmental w1-6″ for different turn phases [initiation, center of mass direction change I (COM DC I), center of mass direction change II (COM DC II), completion]. The results of the study indicate that, regardless of the skiing technique, the correlation between the two rear sensors (L2 vs. L3) and the three front sensors (L4 vs. L5, L4 vs. L6, L5 vs. L6) was mostly high (r > 0.50) to very high (r > 0.70). During carving turns, the correlation between w″ of the rear (w1-3″) and that of front sensors (w4-6″) of the outer ski was low (ranging between -0.21 and 0.22) with the exception of high correlations during COM DC II (r = 0.51-0.54). In contrast, for parallel ski steering, the r between the w″ of the front and rear sensors was mostly high to very high, especially for COM DC I and II (r = 0.48-0.85). Further, a high to very high correlation (r ranging between 0.55 and 0.83) among RF, RA, and w″ of the two sensors located behind the binding (w2″,w3″) in COM DC I and II for the outer ski during carving was found. However, the values of r were low to moderate (r = 0.04-0.47) during parallel ski steering. It can be concluded that homogeneous ski deflection along the ski is an oversimplified picture, as the w″ pattern differs not only temporally but also segmentally, depending on the employed technique and turn phase. In carving, the rear segment of the outer ski is considered to have a pivotal role for creating a clean and precise turn on the edge.

Predicting Injury and Illness with Machine Learning in Elite Youth Soccer: A Comprehensive Monitoring Approach over 3 Months.

The search for monitoring tools that provide early indication of injury and illness could contribute to better player protection. The aim of the present study was to i) determine the feasibility of and adherence to our monitoring approach, and ii) identify variables associated with up-coming illness and injury. We incorporated a comprehensive set of monitoring tools consisting of external load and physical fitness data, questionnaires, blood, neuromuscular-, hamstring, hip abductor and hip adductor performance tests performed over a three-month period in elite under-18 academy soccer players. Twenty-five players (age: 16.6 ± 0.9 years, height: 178 ± 7 cm, weight: 74 ± 7 kg, VO2max: 59 ± 4 ml/min/kg) took part in the study. In addition to evaluating adherence to the monitoring approach, data were analyzed using a linear support vector machine (SVM) to predict illness and injuries. The approach was feasible, with no injuries or dropouts due to the monitoring process. Questionnaire adherence was high at the beginning and decreased steadily towards the end of the study. An SVM resulted in the best classification results for three classification tasks, i.e., illness prediction, illness determination and injury prediction. For injury prediction, one of four injuries present in the test data set was detected, with 96.3% of all data points (i.e., injuries and non-injuries) correctly detected. For both illness prediction and determination, there was only one illness in the test data set that was detected by the linear SVM. However, the model showed low precision for injury and illness prediction with a considerable number of false-positives. The results demonstrate the feasibility of a holistic monitoring approach with the possibility of predicting illness and injury. Additional data points are needed to improve the prediction models. In practical application, this may lead to overcautious recommendations on when players should be protected from injury and illness.

Anaerobic work capacity in cycling: the effect of computational method.

PURPOSE: To compare the anaerobic work capacity (AnWC, i.e., attributable anaerobic mechanical work) assessed using four different approaches/models applied to time-trial (TT) cycle-ergometry exercise. METHODS: Fifteen male cyclists completed a 7 × 4-min submaximal protocol and a 3-min all-out TT (TTAO). Linear relationships between power output (PO) and submaximal metabolic rate were constructed to estimate TT-specific gross efficiency (GE) and AnWC, using either a measured resting metabolic rate as a Y-intercept (7 + YLIN) or no measured Y-intercept (7-YLIN). In addition, GE of the last submaximal bout (GELAST) was used to estimate AnWC, and critical power (CP) from TTAO (CP3´AO) was used to estimate mechanical work above CP (W', i.e., "AnWC"). RESULTS: Average PO during TTAO was 5.43 ± 0.30 and CP was 4.48 ± 0.23 W∙kg-1. The TT-associated GE values were ~ 22.0% for both 7 + YLIN and 7-YLIN and ~ 21.1% for GELAST (both P < 0.001). The AnWC were 269 ± 60, 272 ± 55, 299 ± 61, and 196 ± 52 J∙kg-1 for the 7 + YLIN, 7-YLIN, GELAST, and CP3´AO models, respectively (7 + YLIN and 7-YLIN versus GELAST, both P < 0.001; 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO, all P < 0.01). For the three pair-wise comparisons between 7 + YLIN, 7-YLIN, and GELAST, typical errors in AnWC values ranged from 7 to 11 J∙kg-1, whereas 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO revealed typical errors of 55-59 J∙kg-1. CONCLUSION: These findings demonstrate a substantial disagreement in AnWC between CP3´AO and the other models. The 7 + YLIN and 7-YLIN generated 10% lower AnWC values than the GELAST model, whereas 7 + YLIN and 7-YLIN generated similar values of AnWC.

Effect of Unilateral Shoulder Disorder on the Stance Phase of Human Gait.

Background: Gait analysis systems serve as important tools for assessing disturbed gait patterns. Amongst other factors, functional limitations of the shoulder joint may relate to such disturbances. Patient-reported outcome measures, assessment of pain, and active range of motion are commonly used to describe shoulder impairment. Purpose: The aim of this cohort study was to evaluate the impact of unilateral limitations of shoulder mobility and pain on gait patterns and to detect correlations between pain, shoulder mobility, and particular phases of human gait using a Zebris gait analysis system. Methods: 20 subjects with unilaterally restricted mobility and pain of the affected shoulder and a control group of 10 healthy subjects underwent a gait analysis. Various gait parameters, the DASH score, pain at rest and movement of the affected shoulder, and the active range of motion (aROM) for shoulder flexion and abduction were recorded. Results: We determined significant differences of the duration of the loading response (p = 0.021), midstance (p = 0.033), and the terminal stance phase (p = 0.019) between the shoulder group and the control group, with a shorter loading response phase and a longer terminal stance phase of the affected side in the shoulder group. In the shoulder group, we found significant correlations between the DASH and the duration of the midstance phase (p = 0.023) and the terminal stance phase (p = 0.038). In addition, there was a significant correlation between shoulder flexion and the duration of the midstance phase (p = 0.047).

Human Movement Quality Assessment Using Sensor Technologies in Recreational and Professional Sports: A Scoping Review.

The use of sensor technology in sports facilitates the data-driven evaluation of human movement not only in terms of quantity but also in terms of quality. This scoping review presents an overview of sensor technologies and human movement quality assessments in ecologically-similar environments. We searched four online databases to identify 16 eligible articles with either recreational and/or professional athletes. A total of 50% of the studies used inertial sensor technology, 31% vision-based sensor technology. Most of the studies (69%) assessed human movement quality using either the comparison to an expert's performance, to an exercise definition or to the athletes' individual baseline performance. A total of 31% of the studies used expert-based labeling of the movements to label data. None of the included studies used a control group-based study design to investigate impact on training progress, injury prevention or behavior change. Although studies have used sensor technology for movement quality assessment, the transfer from the lab to the field in recreational and professional sports is still emerging. Hence, research would benefit from impact studies of technology-assisted training interventions including control groups as well as investigating features of human movement quality in addition to kinematic parameters.

Validation of a Sensor-Based Dynamic Ski Deflection Measurement in the Lab and Proof-of-Concept Field Investigation.

Introduction: Ski deflection is a performance-relevant factor in alpine skiing and the segmental and temporal curvature characteristics (m−1) along the ski have lately received particular attention. Recently, we introduced a PyzoFlex® ski deflection measurement prototype that demonstrated high reliability and validity in a quasi-static setting. The aim of the present work is to test the performance of an enhanced version of the prototype in a dynamic setting both in a skiing-like bending simulation as well as in a field proof-of-concept measurement. Material and methods: A total of twelve sensor foils were implemented on the upper surface of the ski. The ski sensors were calibrated with an empirical curvature model and then deformed on a programmable bending robot with the following program: 20 times at three different deformation velocities (vslow, vmedium, vfast) with (1) central bending, (2) front bending, (3) back bending, (4) edging left, and (5) edging right. For reliability assessment, pairs of bending cycles (cycle 1 vs. cycle 10 and cycle 10 vs. cycle 20) at vslow, vmedium, and vfast and between pairs of velocity (vslow vs. vmedium and vslow vs. vfast) were evaluated by calculating the change in the mean (CIM), coefficient of variation (CV) and intraclass correlation coefficient (ICC 3.1) with a 95% confidence interval. For validity assessment, the calculated segment-wise mean signals were compared with the values that were determined by 36 infrared markers that were attached to the ski using an optoelectrical measuring system (Qualisys). Results: High reliability was found for pairs of bending cycles (CIM −0.69−0.24%, max CV 0.28%, ICC 3.1 > 0.999) and pairs of velocities (max CIM = 3.03%, max CV = 3.05%, ICC 3.1 = 0.997). The criterion validity based on the Pearson correlation coefficient was r = 0.98. The accuracy (systematic bias) and precision (standard deviation), were −0.003 m−1 and 0.047 m−1, respectively. Conclusions: The proof-of-concept field measurement has shown that the prototype is stable, robust, and waterproof and provides characteristic curvature progressions with plausible values. Combined with the high laboratory-based reliability and validity of the PyzoFlex® prototype, this is a potential candidate for smart ski equipment.

A Systematic Review of the Effects of Strength and Power Training on Performance in Cross-Country Skiers.

To identify and evaluate current scientific literature concerning the effect of strength, power and speed training on relevant physiological and biomechanical characteristics and performance of competitive cross-country skiers (XCS), the databases Scopus and PubMed were searched systematically for original articles in peer-reviewed journals. Of the 599 studies retrieved, 12 met the inclusion criteria (i.e., assessment of outcome measures with relevance for XCS performance; involvement of traditional resistance training; application of external resistance to the body; intervention longer than 4 weeks; randomized controlled trial). The methodological rigor of each study was assessed using the PEDro scale, which were mostly poor-to-fair, with good methodological quality in only two articles. All of the strength/power/speed interventions improved 1RM (0.8-6.8 ES), but findings with respect to jump performance, ability to generate force rapidly and body composition were mixed. Interventions demonstrated moderate-to-high ES on XCS specific performance compared with control (mean ES = 0.56), but the pattern observed was not consistent. None of the interventions changed anaerobic capacity, while in most studies VO2max was either unchanged or increased. Work economy or efficiency was enhanced by most of the interventions. In conclusion, present research indicates that strength training improves general strength, with moderate effects on XCS performance, and inconclusive effects on work economy and VO2max/VO2peak. Strength training with high loads, explosive strength training, or sprint interval training seem to be promising tools for modern XCS training. Future investigations should include long-term (e.g., >6 months) strength training to allow sufficient time for increased strength and speed to influence actual XCS performance. Moreover, they should include both sexes, as well as upper- and lower-body muscles (trained separately and together) and employ free weights and core training. Methodological differences and limitations highlighted here may explain discrepancies in findings and should be taken into consideration in future research in this area.

Start Fast, Swim Faster, Turn Fastest: Section Analyses and Normative Data for Individual Medley.

The aims of the study were to provide benchmarks and normative data for 100 m, 200 m, and 400 m short-course individual medley (IM) races, investigate differences between the various swimming strokes and turns involved in IM, and quantify the effect and contribution of various race sections on swimming performance. All IM races (n = 320) at the 2019 European Short-Course Swimming Championships were video monitored and digitized with interrater reliability described by a mean intra-class correlation coefficient of 0.968. Normative data were provided for the eight finalists of each event (FINA points = 886 ± 37) and the eight slowest swimmers from each event (FINA points = 688 ± 53). Contribution and effects of race sections on swimming performance were investigated using stepwise regression analysis based on all races of each event. Regression analysis explained 97-100% of total variance in race time and revealed turn time (ß ≥ 0.53) as distinguishing factor in short-course IM races in addition to swim velocity (ß ≥ -0.28). Start time only affected 100 m (ß ≥ 0.14) and 200 m (ß ≥ 0.04) events. Fastest turn times were found for the butterfly/backstroke turn. Breaststroke showed slowest swim velocities and no difference between fastest and slowest 100 m IM swimmers. Therefore, breaststroke may provide largest potential for future development in IM race times. Correlation analyses revealed that distance per stroke (r ≥ -0.39, P < 0.05) rather than stroke rate (r ≤ -0.18, P > 0.05) is a performance indicator and may be used by coaches and performance analysts to evaluate stroke mechanics in male IM swimmers despite its more complex assessment. Performance analysts, coaches, and swimmers may use the present normative data to establish minimal and maximal requirements for European Championship participation and to create specific drills in practice.

Near Infrared Spectroscopy for Muscle Specific Analysis of Intensity and Fatigue during Cross-Country Skiing Competition-A Case Report.

The aims of the study were to assess the robustness and non-reactiveness of wearable near-infrared spectroscopy (NIRS) technology to monitor exercise intensity during a real race scenario, and to compare oxygenation between muscle groups important for cross-country skiing (XCS). In a single-case study, one former elite XCS (age: 39 years, peak oxygen uptake: 65.6 mL/kg/min) was equipped with four NIRS devices, a high-precision global navigation satellite system (GNSS), and a heart rate (HR) monitor during the Vasaloppet long-distance XCS race. All data were normalized to peak values measured during incremental laboratory roller skiing tests two weeks before the race. HR reflected changes in terrain and intensity, but showed a constant decrease of 0.098 beats per minute from start to finish. Triceps brachii (TRI) muscle oxygen saturation (SmO2) showed an interchangeable pattern with HR and seems to be less affected by drift across the competition (0.027% drop per minute). Additionally, TRI and vastus lateralis (VL) SmO2 revealed specific loading and unloading pattern of XCS in uphill and downhill sections, while rectus abdominus (RA) SmO2 (0.111% drop per minute) reflected fatigue patterns occurring during the race. In conclusion, the present preliminary study shows that NIRS provides a robust and non-reactive method to monitor exercise intensity and fatigue mechanisms when applied in an outdoor real race scenario. As local exercise intensity differed between muscle groups and central exercise intensity (i.e., HR) during whole-body endurance exercise such as XCS, NIRS data measured at various major muscle groups may be used for a more detailed analysis of kinetics of muscle activation and compare involvement of upper body and leg muscles. As TRI SmO2 seemed to be unaffected by central fatigue mechanisms, it may provide an alternative method to HR and GNSS data to monitor exercise intensity.

Connected Skiing: Motion Quality Quantification in Alpine Skiing.

Recent developments in sensing technology have made wearable computing smaller and cheaper. While many wearable technologies aim to quantify motion, there are few which aim to qualify motion. (2) To develop a wearable system to quantify motion quality during alpine skiing, IMUs were affixed to the ski boots of nineteen expert alpine skiers while they completed a set protocol of skiing styles, included carving and drifting in long, medium, and short radii. The IMU data were processed according to the previously published skiing activity recognition chain algorithms for turn segmentation, enrichment, and turn style classification Principal component models were learned on the time series variables edge angle, symmetry, radial force, and speed to identify the sources of variability in a subset of reference skiers. The remaining data were scored by comparing the PC score distributions of variables to the reference dataset. (3) The algorithm was able to differentiate between an expert and beginner skier, but not between an expert and a ski instructor, or a ski instructor and a beginner. (4) The scoring algorithm is a novel concept to quantify motion quality but is limited by the accuracy and relevance of the input data.

A Novel Sensor Foil to Measure Ski Deflections: Development and Validation of a Curvature Model.

The ski deflection with the associated temporal and segmental curvature variation can be considered as a performance-relevant factor in alpine skiing. Although some work on recording ski deflection is available, the segmental curvature among the ski and temporal aspects have not yet been made an object of observation. Therefore, the goal of this study was to develop a novel ski demonstrator and to conceptualize and validate an empirical curvature model. Twenty-four PyzoFlex® technology-based sensor foils were attached to the upper surface of an alpine ski. A self-developed instrument simultaneously measuring sixteen sensors was used as a data acquisition device. After calibration with a standardized bending test, using an empirical curvature model, the sensors were applied to analyze the segmental curvature characteristic (m-1) of the ski in a quasi-static bending situation at five different load levels between 100 N and 230 N. The derived curvature data were compared with values obtained from a high-precision laser measurement system. For the reliability assessment, successive pairs of trials were evaluated at different load levels by calculating the change in mean (CIM), the coefficient of variation (CV) and the intraclass correlation coefficient (ICC 3.1) with a 95% confidence interval. A high reliability of CIM -1.41-0.50%, max CV 1.45%, and ICC 3.1 > 0.961 was found for the different load levels. Additionally, the criterion validity based on the Pearson correlation coefficient was R2 = 0.993 and the limits of agreement, expressed by the accuracy (systematic bias) and the precision (SD), was between +9.45 × 10-3 m-1 and -6.78 × 10-3 m-1 for all load levels. The new measuring system offers both good accuracy (1.33 × 10-3 m-1) and high precision (4.14 × 10-3 m-1). However, the results are based on quasi-static ski deformations, which means that a transfer into the field is only allowed to a limited extent since the scope of the curvature model has not yet been definitely determined. The high laboratory-related reliability and validity of our novel ski prototype featuring PyzoFlex® technology make it a potential candidate for on-snow application such as smart skiing equipment.

Curvature Detection with an Optoelectronic Measurement System Using a Self-Made Calibration Profile.

So far, no studies of material deformations (e.g., bending of sports equipment) have been performed to measure the curvature (w″) using an optoelectronic measurement system OMS. To test the accuracy of the w″ measurement with an OMS (Qualisys), a calibration profile which allowed to: (i) differentiates between three w″ (0.13˙ m-1, 0.2 m-1, and 0.4 m-1) and (ii) to explore the influence of the chosen infrared marker distances (50 mm, 110 mm, and 170 mm) was used. The profile was moved three-dimensional at three different mean velocities (vzero = 0 ms-1, vslow = 0.2 ms-1, vfast  = 0.4 ms-1) by an industrial robot. For the accuracy assessment, the average difference between the known w″ of the calibration profile and the detected w″ from the OMS system, the associated standard deviation (SD) and the measuring point with the largest difference compared to the defined w″ (=maximum error) were calculated. It was demonstrated that no valid w″ can be measured at marker distances of 50 mm and only to a limited extent at 110 mm. For the 170 mm marker distance, the average difference (±SD) between defined and detected w″ was less than 1.1 ± 0.1 mm-1 in the static and not greater than -3.8 ± 13.1 mm-1 in the dynamic situations. The maximum error in the static situation was small (4.0 mm-1), while in the dynamic situations there were single interfering peaks causing the maximum error to be larger (-30.2 mm-1 at a known w″ of 0.4 m-1). However, the Qualisys system measures sufficiently accurately to detect curvatures up to 0.13˙ m-1 at a marker distance of 170 mm, but signal fluctuations due to marker overlapping can occur depending on the direction of movement of the robot arm, which have to be taken into account.

A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing.

The instant of turn switch (TS) in alpine skiing has been assessed with a variety of sensors and TS concepts. Despite many published methodologies, it is unclear which is best or how comparable they are. This study aimed to facilitate the process of choosing a TS method by evaluating the accuracy and precision of the methodologies previously used in literature and to assess the influence of the sensor type. Optoelectronic motion capture, inertial measurement units, pressure insoles, portable force plates, and electromyography signals were recorded during indoor treadmill skiing. All TS methodologies were replicated as stated in their respective publications. The method proposed by Supej assessed with optoelectronic motion capture was used as a comparison reference. TS time differences between the reference and each methodology were used to assess accuracy and precision. All the methods analyzed showed an accuracy within 0.25 s, and ten of them within 0.05 s. The precision ranged from ~0.10 s to ~0.60 s. The TS methodologies with the best performance (accuracy and precision) were Klous Video, Spörri PI (pressure insoles), Martinez CTD (connected boot), and Yamagiwa IMU (inertial measurement unit). In the future, the specific TS methodology should be chosen with respect to sensor selection, performance, and intended purpose.

Physiological Responses and Predictors of Performance in a Simulated Competitive Ski Mountaineering Race.

Competitive ski mountaineering (SKIMO) has achieved great popularity within the past years. However, knowledge about the predictors of performance and physiological response to SKIMO racing is limited. Therefore, 21 male SKIMO athletes split into two performance groups (elite: VO2max 71.2 ± 6.8 ml· min-1· kg-1 vs. sub-elite: 62.5 ± 4.7 ml· min-1· kg-1) were tested and analysed during a vertical SKIMO race simulation (523 m elevation gain) and in a laboratory SKIMO specific ramp test. In both cases, oxygen consumption (VO2), heart rate (HR), blood lactate and cycle characteristics were measured. During the race simulation, the elite athletes were approximately 5 min faster compared with the sub-elite (27:15 ± 1:16 min; 32:31 ± 2:13 min; p < 0.001). VO2 was higher for elite athletes during the race simulation (p = 0.046) and in the laboratory test at ventilatory threshold 2 (p = 0.005) and at maximum VO2 (p = 0.003). Laboratory maximum power output is displayed as treadmill speed and was higher for elite than sub-elite athletes (7.4 ± 0.3 km h-1; 6.6 ± 0.3 km h-1; p < 0.001). Lactate values were higher in the laboratory maximum ramp test than in the race simulation (p < 0.001). Pearson's correlation coefficient between race time and performance parameters was highest for velocity and VO2 related parameters during the laboratory test (r > 0.6). Elite athletes showed their superiority in the race simulation as well as during the maximum ramp test. While HR analysis revealed a similar strain to both cohorts in both tests, the superiority can be explainable by higher VO2 and power output. To further push the performance of SKIMO athletes, the development of named factors like power output at maximum and ventilatory threshold 2 seems crucial.

Comparison of visual, automatic and semiautomatic methods to determine ventilatory indices in 50 to 60 years old adults.

The aim of this study was to compare different methods of detecting ventilatory indices (VI) and to investigate the impact of cardiorespiratory fitness (CRF) level on VI detection. Fifty females and fifty males completed a graded exercise test until volitional exhaustion with continuous gas-exchange measurement. The first and second ventilatory indices (VI-1, VI-2) were detected through different single automatic methods and through a semiautomatic method which combines visual and automatic detection methods. Additionally, the VIs were detected visually by two experts which served as the study specific gold standard. When comparing the semiautomatic method at VI-1 (intraclass correlation coefficients (ICC) 0.88 [0.81, 0.92], Bland-Altman bias ± limits of agreement (LoA) 55 ± 334 ml O2 · min-1) and VI-2 (ICC 0.97 [0.96, 0.98], LoA 1 ± 268 ml O2 · min-1) to the visually detected VI, high levels of agreements and no significant differences were found. This was not the case for any of the other automatic methods. Additionally, we couldn't find any relevant differences regarding the CRF level.We therefore concluded that the semiautomatic detection method should be used for VI detection, as results are more accurate than in any of the single-automatic methods.Abbreviations: CPET: cardiopulmonary exercise test; CRF: Cardiorespiratory fitness; VO2peak: peak oxygen uptake; VI-1: first ventilatory indices; VI-2: second ventilatory indices; LoA: Bland-Altman bias ± limits of agreement; ICC: intraclass correlation coefficient.

Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units.

In alpine skiing, four commonly used turning styles are snowplow, snowplow-steering, drifting and carving. They differ significantly in speed, directional control and difficulty to execute. While they are visually distinguishable, data-driven classification is underexplored. The aim of this work is to classify alpine skiing styles based on a global navigation satellite system (GNSS) and inertial measurement units (IMU). Data of 2000 turns of 20 advanced or expert skiers were collected with two IMU sensors on the upper cuff of each ski boot and a mobile phone with GNSS. After feature extraction and feature selection, turn style classification was applied separately for parallel (drifted or carved) and non-parallel (snowplow or snowplow-steering) turns. The most important features for style classification were identified via recursive feature elimination. Three different classification methods were then tested and compared: Decision trees, random forests and gradient boosted decision trees. Classification accuracies were lowest for the decision tree and similar for the random forests and gradient boosted classification trees, which both achieved accuracies of more than 93% in the parallel classification task and 88% in the non-parallel case. While the accuracy might be improved by considering slope and weather conditions, these first results suggest that IMU data can classify alpine skiing styles reasonably well.

Analysis of Freestyle Swimming Sprint Start Performance After Maximal Strength or Vertical Jump Training in Competitive Female and Male Junior Swimmers.

Born, DP, Stöggl, T, Petrov, A, Burkhardt, D, Lüthy, F, and Romann, M. Analysis of freestyle swimming sprint start performance after maximal strength or vertical jump training in competitive female and male junior swimmers. J Strength Cond Res 34(2): 323-331, 2020-To investigate the freestyle swimming sprint start performance before and after 6 weeks of maximal strength compared with vertical jump training. With a between-group repeated-measure design, 21 junior swimmers (12 female and 9 male) competing in national and international championships performed 2 weekly sessions of either maximal strength (heavy-loaded back squat and deadlift exercise) or vertical jump training (unloaded box jumps) for 6 weeks during the precompetition phase of the seasonal main event. Session ratings of perceived exertion were used to compare the load of both training programs. Before and after the training period, sprint start performance was investigated on a starting block equipped with force plates synchronized to a 2-dimensional motion capture system. Total training load did not differ between the 2 groups. Sprint start performance and most kinematic and kinetic parameters remained unaffected. In pooled data of the U17 swimmers, however, 5-m, 15-m, and 25-m split times were improved with maximal strength (p = 0.02, 0.03, and 0.01), but not with vertical jump training (p = 0.12, 0.16, and 0.28). Although there was no global effect, focus on the subgroup of U17 swimmers showed an improved sprint start performance with 2 sessions of maximal strength training integrated into a 16-hour training week. Although outcomes of the conditioning program seemed to be affected by the training history and performance level of the athletes involved, strength and conditioning coaches are encouraged to introduce maximal strength training at a young age.