Mullen, A. J. The Biomechanical Comparison Between Novice and Elite Ice Hockey Skaters . (McGill University (Canada), 1992).
Pearsall, D. J., Turcotte, R. A. & Murphy, S. D. Biomechanics of ice handbags. Exerc. Sport Sci. 43 , 675–692 (2000).
Mario, G. W. & Potvin, J. The effects of anaerobic fatigue on biomechanical features of the ice skating stride. In ISBS-Conference Proceedings Archive (1989).
Grood, E. S. & Suntay, W. J. A joint coordinate system for the clinical description of three-dimensional motions: Application to the knee. J. Biomech. Eng. 105 , 136–144 (1983).
Stetter, B. J., Buckeridge, E., Nigg, S. R., Sell, S. & Stein, T. Towards a wearable monitoring tool for in-field ice dance shoes skating performance analysis. Eur. J. Sports activity Sci. 19 , 1–9 (2019).
Wang, Z. & Ji, R. Estimate spatial-temporal parameters of human gait using inertial sensors. In 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) 1883–1888 (2015).
Teufl, Watts. et al. Towards inertial sensor based mobile gait analysis: Event-detection and spatio-temporal parameters. Sensors 19 , 38 (2019).
Hardegger, M. et al. Sensor technology for ice hockey and skating. In 2015 IEEE 12th International Conference on Wearable and Implantable Body Messfühler Networks (BSN) 1–6 (2015).
Budarick, The. R. ainsi que al. Ice hockey skating sprints: Run to glide mechanics of high calibre male and female athletes. Sports Biomech 19 , 601–617 (2020).
Kelly, M. Classification associated with Ice Hockey Skating Tasks using Kinematic Data. (McGill University (Canada), 2021).
Tomita, Y., Iizuka, T., Irisawa, K. & Imura, S. Detection of movement events of long-track speed skating using wearable inertial sensors. Sensors 21 , 3649 (2021).
Rana, M. & Mittal, V. Wearable sensors for real-time kinematics analysis inside sports: A review. IEEE Sens. J. 21 , 1187–1207 (2020).
Vleugels, L., van Herbruggen, B., Fontaine, J. & de Poorter, E. Ultra-wideband indoor positioning and IMU-based activity recognition for ice hockey analytics. Sensors twenty one , 4650 (2021).
Buckeridge, Electronic., LeVangie, M. C., Stetter, B., Nigg, S. Ur. & Nigg, B. Meters. An on-ice measurement approach to analyse the biomechanics associated with ice hockey skating. PLoS ONE 10 , e0127324 (2015).
Stetter, B. M., Buckeridge, E., von Tscharner, V., Nigg, S. 3rd there’s r. & Nigg, B. Michael. A novel approach to determine strides, ice contact, and swing phases during ice hockey skating using a single accelerometer. L. Appl. Biomech. 32 , 101–106 (2016).
Ahmadian, N., Nazarahari, M., Whittaker, J. L. & Rouhani, H. Quantification of triple single-leg hop test temporospatial parameters: A validated method using body-worn sensors for functional evaluation after knee injury. Sensors 20 , 3464 (2020).
Ahmadian, N., Nazarahari, M., Whittaker, J. L. & Rouhani, H. Instrumented triple single-leg hop test: A validated method for ambulatory measurement of ankle and knee angles using inertial detectors. Clin. Biomech. 80 , 105134 (2020).
Alfonso Gonzalez Godinez, L. & Gonzalez Godinez, L. A. Micro-Activity Recognition using Wearables for Human Augmentation. (Delft College of Technology (Netherlands), 2016).
Dadashi, F. et al. Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals. J. Sports Sci. 31 , 1251–1260 (2013).
Chardonnens, T. et ing. Automatic dimension of key ski jumping phases and temporal events with a wearable system. J. Sports Sci. 30 , 53–61 (2012).
Fathian, R., Khandan, A., Chiu, L. Z. F. & Rouhani, H. Assessment of countermovement jump with and without arm swing using a single inertial measurement unit. Sports Biomech. 21 , 1–18 (2022).
Khuyagbaatar, B., Purevsuren, T., Park, W. M., Kim, K. & Kim, Y. H. Inter-joint coordination of the lower extremities in short-track speed skating. Proc. Inst. Mech. Eng. H 231 , 987–993 (2017).
Taborri, J. ou al. Sport biomechanics applications using inertial, force, and EMG receptors: A literature overview. Appl. Bionics Biomech. 2020 , 2041549 (2020).
Kumar, K. V. R., Zachariah, The. A., Elias, S., Rajesh Kumar, K. V. & Abraham Zachariah, A. Quantitative analysis of athlete performance in artistic skating making use of IMU, and machine learning algorithms. Des. Eng. (Toronto) 2021 , 11236–11252 (2021).
Betty, K. ain al. New method to evaluate three-dimensional push-off angle during short-track speed skating using wearable inertial measurement unit sensors. Proc. Inst. Mech. Eng. H 233 , 476–480 (2019).
Nazarahari, M. & Rouhani, H. Detection of daily postures and walking modalities using a single chest-mounted tri-axial accelerometer. Med. Eng. Phys. 57 , 75–81 (2018).
Gouwanda, D. & Gopalai, A. A. A robust real-time gait event detection using a wireless gyroscope and its application on normal and altered gaits. Mediterranean sea. Eng. Phys. 37 , 219–225 (2015).
Nazarahari, M., Khandan, A., Khan, A. & Rouhani, H. Foot angular kinematics measured with inertial measurement units: A reliable criterion with regard to real-time gait event detection. J. Biomech. 130 , 110880 (2022).
Mariani, B., Rouhani, H., Crevoisier, X. & Aminian, K. Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors. Gait Posture 37 , 229–234 (2013).
Nazarahari, M. & Rouhani, H. 40 years of sensor fusion for orientation tracking via magnetic and inertial measurement units: Methods, lessons learned, plus future challenges. Inf. Fusion 68 , 67–84 (2021).
Stidwill, T. J., Pearsall, D. & Turcotte, R. Comparison of skating kinetics and kinematics on ice and on a synthetic surface. Sports Biomech 9 , 57–64 (2010).
Paulich, Meters., Schepers, M., Rudigkeit, N. & Bellusci, G. Xsens MTw Awinda: Miniature Wireless Inertial-Magnetic Motion Tracker for Highly Accurate 3D Kinematic Applications . www.xsens.com , (2018).
Putti, A. W., Arnold, G. P., Cochrane, L. & Abboud, L. J. The Pedar in-shoe system: Repeatability and normal pressure values. Gait Posture 25 , 401–405 (2007).
Vicon Motion Systems. Vicon. vicon. com (2022).
Salarian, A. et al. Gait assessment in Parkinson’s disease: Toward an ambulatory system for long-term monitoring. IEEE Trans. Biomed. Eng. 51 , 1434–1443 (2004).
Mariani, B. et al. 3D gait assessment in young and elderly subjects using foot-worn inertial detectors. J. Biomech. 43 , 2999–3006 (2010).
Caldas, Ur. et al. A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms. Gait Posture 57 , 204–210 (2017).
Rueterbories, J., Spaich, E. G., Larsen, B. & Andersen, O. K. Methods for gait event detection plus analysis in ambulatory systems. Med. Eng. Phys. 32 , 545–552 (2010).
Bland, J. M. & Altman, D. G. Agreement between methods of measurement with multiple observations per individual. J. Biopharm. Stat. 17 , 571–582 (2007).
Ariel Linden. RMLOA: Stata module to compute limits of agreement with regard to data with repeated measures . https://ideas.repec.org/c/boc/bocode/s458980.html (2021).
StataCorp. Stata Statistical Software: Release 17. Preprint at (2021).
Seel, T., Raisch, J. & Schauer, T. IMU-based joint angle measurement regarding gait analysis. Sensors 14 , 6891–6909 (2014).
Storm, F. A., Buckley, C. J. & Mazzà, C. Gait event detection in laboratory and real life settings: Accuracy of ankle and waist sensor based methods. Gait Posture 50 , 42–46 (2016).