Publications

@article{nokey,

title = {Validation of a Sensor-Based Dynamic Ski Deflection Measurement in the Lab and Proof-of-Concept Field Investigation},

author = {C. Thorwartl and J. Kröll and A. Tschepp and W. Teufl and T. Stöggl},

doi = {https://doi.org/10.3390/s22155768},

year  = {2022},

date = {2022-08-02},

urldate = {2022-08-02},

journal = {Sensors},

volume = {22},

issue = {2},

pages = {5768},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The modified German subjective vitality scale (SVS-GM): Psychometric properties and application in daily life},

author = {L. Buchner and G. Amesberger and T. Finkenzeller and S. R. Moore and S. Würth},

doi = {https://doi.org/10.3389/fpsyg.2022.948906},

issn = {1664-1078},

year  = {2022},

date = {2022-07-29},

urldate = {2022-07-29},

journal = {Frontiers in Psychology},

volume = {13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Human Movement Quality Assessment Using Sensor Technologies in Recreational and Professional Sports: A Scoping Review.},

author = {V. Venek and S. Kranzinger and H. Schwameder and T. Stöggl},

doi = { https://doi.org/10.3390/s22134786 },

year  = {2022},

date = {2022-06-20},

urldate = {2022-06-20},

journal = {Sensors},

volume = {22},

number = {4786},

issue = {13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Breath Tools: A Synthesis of Evidence-Based Breathing Strategies to Enhance Human Running},

author = {E. Harbour and T. Stöggl and H. Schwameder and T. Finkenzeller},

editor = {Nicolò, A.; Cogo, A.; LoMauro, A.},

url = {https://www.frontiersin.org/article/10.3389/fphys.2022.813243},

doi = {https://doi.org/10.3389/fphys.2022.813243},

isbn = {1664-042X   },

year  = {2022},

date = {2022-03-30},

urldate = {2022-03-30},

journal = {Frontiers in Physiology },

volume = {13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Concurrent Evolution of Biomechanical and Physiological Parameters With Running-Induced Acute Fatigue},

author = {G. Prigent and A. Paraschiv-Ionescu and C. Besson and V. Gremeaux and K. Aminian},

doi = {doi:10.3389/fphys.2022.814172},

year  = {2022},

date = {2022-02-11},

urldate = {2022-02-11},

journal = {Frontiers in Physiology},

volume = {13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Thorwartl2021b,

title = {Curvature Detection with an Optoelectronic Measurement System Using a Self-Made Calibration Profile},

author = {C. Thorwartl and T. Stöggl and W. Teufl and H. Holzer and J. Kröll},

doi = {10.3390/s22010051},

year  = {2021},

date = {2021-12-22},

urldate = {2021-12-22},

journal = {Sensors},

volume = {22},

number = {1},

pages = {51},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Apte2021,

title = {Biomechanical Response of the Lower Extremity to Running-Induced Acute Fatigue: A Systematic Review},

author = {S. Apte and G. Prigent and T. Stöggl and A. Martínez and C. Snyder and V. Gremeaux-Bader and K. Aminian},

doi = {10.3389/fphys.2021.646042},

year  = {2021},

date = {2021-08-27},

journal = {Frontiers in Physiology},

volume = {12},

number = {646042},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Connected Skiing: Validation of Edge Angle and Radial Force Estimation as Motion Quality Parameters During Alpine Skiing},

author = {C. Snyder and A. Martínez and G. Strutzenberger and T. Stöggl},

doi = {10.1080/17461391.2021.1970236},

year  = {2021},

date = {2021-08-25},

journal = {European Journal of Sport Science},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running},

author = {G. Prigent and K. Aminian and T. Rodrigues and J.-M. Vesin and G.P. Millet and M. Falbriard and F. Meyer},

doi = {https://doi.org/10.3390/s21165651 },

year  = {2021},

date = {2021-08-22},

urldate = {2022-08-21},

journal = {Sensors},

volume = {21},

pages = {5651},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Harbour2021,

title = {Enhanced Breathing Pattern Detection during Running Using Wearable Sensors},

author = {E. Harbour and M. Lasshofer and M. Genitrini and H. Schwameder},

doi = {10.3390/s21165606},

year  = {2021},

date = {2021-08-20},

urldate = {2021-08-20},

journal = {Sensors},

volume = {21},

number = {16},

abstract = {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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}