Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques
- DOI
- 10.3390/s20236737
- Published
- 2020-11-25
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s20236737,
title = {Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques},
author = {Stephanie R. Moore and Christina Kranzinger and Julian Fritz and Thomas Stӧggl and Josef Krӧll and Hermann Schwameder},
year = {2020},
journal = {Sensors},
doi = {10.3390/s20236737},
url = {https://doi.org/10.3390/s20236737}
}RIS
TY - JOUR TI - Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques AU - Stephanie R. Moore AU - Christina Kranzinger AU - Julian Fritz AU - Thomas Stӧggl AU - Josef Krӧll AU - Hermann Schwameder PY - 2020 JO - Sensors DO - 10.3390/s20236737 UR - https://doi.org/10.3390/s20236737 ER -
APA
Moore, S. R., Kranzinger, C., Fritz, J., Stӧggl, T., Krӧll, J., & Schwameder, H. (2020). Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques. Sensors. https://doi.org/10.3390/s20236737
Source records
- crossref · retrieved 2026-09-25T06:57:56.419Z