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Apte, S.; Prigent, G.; Stöggl, T.; Martínez, A.; Snyder, C.; Gremeaux-Bader, V.; Aminian, K.
Biomechanical Response of the Lower Extremity to Running-Induced Acute Fatigue: A Systematic Review (Journal Article)
In: Frontiers in Physiology, 12 (646042), 2021.
Objective: To investigate (i) typical protocols used in research on biomechanical response to running-induced fatigue, (ii) the effect of sport-induced acute fatigue on the biomechanics of running and functional tests, and (iii) the consistency of analyzed parameter trends across different protocols.
Methods: Scopus, Web of Science, Pubmed, and IEEE databases were searched using terms identified with the Population, Interest and Context (PiCo) framework. Studies were screened following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and appraised using the methodological index for non-randomized studies MINORS scale. Only experimental studies with at least 10 participants, which evaluated fatigue during and immediately after the fatiguing run were included. Each study was summarized to record information about the protocol and parameter trends. Summary trends were computed for each parameter based on the results found in individual studies.
Results: Of the 68 included studies, most were based on in-lab (77.9%) protocols, endpoint measurements (75%), stationary measurement systems (76.5%), and treadmill environment (54.4%) for running. From the 42 parameters identified in response to acute fatigue, flight time, contact time, knee flexion angle at initial contact, trunk flexion angle, peak tibial acceleration, CoP velocity during balance test showed an increasing behavior and cadence, vertical stiffness, knee extension force during MVC, maximum vertical ground reaction forces, and CMJ height showed a decreasing trend across different fatigue protocols.
Conclusion: This review presents evidence that running-induced acute fatigue influences almost all the included biomechanical parameters, with crucial influence from the exercise intensity and the testing environment. Results indicate an important gap in literature caused by the lack of field studies with continuous measurement during outdoor running activities. To address this gap, we propose recommendations for the use of wearable inertial sensors.
Snyder, C.; Martínez, A.; Strutzenberger, G.; Stöggl, T.
Connected Skiing: Validation of Edge Angle and Radial Force Estimation as Motion Quality Parameters During Alpine Skiing (Journal Article)
In: European Journal of Sport Science, 2021.
Recent studies have developed wearable sensor systems to detect, classify and evaluate performance during alpine skiing. In order to enrich skiing data to provide motion quality feedback, edge angle (EA) and radial force (Fr) are parameters of interest. However, the estimation of these parameters via calibration free wearable technologies has not been validated. The purpose of this study was to develop and validate a wearable method to estimate EA and Fr. Participants completed simulated skiing trials on an indoor skiing carpet. Two IMU’s mounted to the ski boots estimated EA and Fr and compared to reference values measured with a 3D motion capture system. The performance of the wearable system was quantified by accuracy and precision. The overall accuracy and precision of the wearable system was 97.6 ± 12.4% and 15.5 ± 17.6% for EA, and 105.5 ± 5.7% and 29.8 ± 10.0% respectively for Fr. The developed wearable system was accurate for the estimation of EA and Fr, but was highly variable with low precision for both metrics. Further research is needed to improve the precision of field relevant skiing metrics during in-field studies using simple measurement setups that can easily be implemented by recreational and expert skiers alike.
IMU’s mounted on the boots are sufficient tools for accurate estimation of edge angle and radial force during both long and short style turns on a skiing simulator.
As the estimation of edge angle and radial force are dependent on other estimated parameters (i.e. turn switch), the precision of these metrics is relatively low.
The results of the current study apply only to simulated alpine skiing on a treadmill, and further work is required to prove the accuracy and precision of this system on snow.
Harbour, E.; Lasshofer, M.; Genitrini, M.; Schwameder, H.
Enhanced Breathing Pattern Detection during Running Using Wearable Sensors (Journal Article)
In: Sensors, 21 (16), 2021.
Breathing pattern (BP) is related to key psychophysiological and performance variables during exercise. Modern wearable sensors and data analysis techniques facilitate BP analysis during running but are lacking crucial validation steps in their deployment. Thus, we sought to evaluate a wearable garment with respiratory inductance plethysmography (RIP) sensors in combination with a custom-built algorithm versus a reference spirometry system to determine its concurrent validity in detecting flow reversals (FR) and BP. Twelve runners completed an incremental running protocol to exhaustion with synchronized spirometry and RIP sensors. An algorithm was developed to filter, segment, and enrich the RIP data for FR and BP estimation. The algorithm successfully identified over 99% of FR with an average time lag of 0.018 s (−0.067,0.104) after the reference system. Breathing rate (BR) estimation had low mean absolute percent error (MAPE = 2.74 [0.00,5.99]), but other BP components had variable accuracy. The proposed system is valid and practically useful for applications of BP assessment in the field, especially when measuring abrupt changes in BR. More studies are needed to improve BP timing estimation and utilize abdominal RIP during running.
Thorwartl, C.; Kröll, J.; Tschepp, A.; Schäffner, P.; Holzer, H.; Stöggl, T.
A Novel Sensor Foil to Measure Ski Deflections: Development and Validation of a Curvature Model (Journal Article)
In: Sensors, 21 (14), pp. 4848, 2021.
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.
Martínez, Aaron; Snyder, Cory; Moore, Stephanie R.; Stöggl, Thomas
A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing (Journal Article)
In: Sensors, 21 (7), 2021.
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.
Moore, S. R.; Kranzinger, C; Fritz, J.; Stöggl, T.; Kröll, J.; Schwameder, H.
Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques (2020) (Journal Article)
In: Sensors, 20 (23), 2020.
Neuwirth, C.; Snyder, C.; Kremser, W.; Brunauer, R.; Holzer, H.; Stöggl, T.
Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units (2020) (Journal Article)
In: Sensors, 20 (15), 2020.
Martínez, A.; Nakazato, K.; Scheiber, P.; Snyder, C.; Stöggl, T.
Comparison of the Turn Switch Time Points Measured by Portable Force Platforms and Pressure Insoles (2020) (Journal Article)
In: Front. Sports Act. Living, 2020.
Takeda, M.; Miyamoto, N.; Endo, T.; Ohtonen, O.; Lindinger, S.; Linnamo, V.; Stöggl, T.
Cross-Country Skiing Analysis and Ski Technique Detection by High-Precision Kinematic Global Navigation Satellite System (2019) (Journal Article)
In: Sensors, 19 (22), 2019.
Martínez, A.; Brunauer, R.; Venek, V.; Snyder, C.; Jahnel, R.; Buchecker, M.; Thorwartl, C.; Stöggl, T.
Development and Validation of a Gyroscope-Based Turn Detection Algorithm for Alpine Skiing in the Field (2019) (Journal Article)
In: Front. Sports Act. Living, 2019.
Fritz, J.; Brunauer, R.; Snyder, C.; Kröll, J.; Stöggl, T.; Schwameder, H.
Foot strike angle calculation during running based on in-shoe pressure measurements (2019) (Journal Article)
In: Footwear Science, 11 (1), pp. 147-149, 2019.
Björklund, G.; Swarén, M.; Born, D. P.; Stöggl, T.
Biomechanical adaptations and performance indicators in short trail running (2019) (Journal Article)
In: Frontiers in physiology, 2019.
Stöggl, T.; Ohtonen, O.; Takeda, M.; Miyamoto, N.; Snyder, C.; Lemmettylä, T.; Linnamo, V.; Lindinger, S.
Comparison of Exclusive Double Poling to Classic Techniques of Cross-country Skiing (2019) (Journal Article)
In: 51 (4), pp. 760-772, 2019.
Martínez, A.; Jahnel, R.; Buchecker, M.; Snyder, C.; Brunauer, R.; Stöggl, T.
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup (2019) (Journal Article)
In: Sensors, 19 (4), 2019.