Optimizing wearable IMU configurations for running gait analysis: a machine learning-based sensor fusion approach.

Yuan Y, Yu Y, Cai S, Cheng W

DOI: 10.3389/fbioe.2026.1762919
Published: 2026
Container: Frontiers in bioengineering and biotechnology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fbioe.2026.1762919,
  title = {Optimizing wearable IMU configurations for running gait analysis: a machine learning-based sensor fusion approach.},
  author = {Yuan Y and Yu Y and Cai S and Cheng W},
  year = {2026},
  journal = {Frontiers in bioengineering and biotechnology},
  doi = {10.3389/fbioe.2026.1762919},
  url = {https://doi.org/10.3389/fbioe.2026.1762919}
}

RIS

TY  - JOUR
TI  - Optimizing wearable IMU configurations for running gait analysis: a machine learning-based sensor fusion approach.
AU  - Yuan Y
AU  - Yu Y
AU  - Cai S
AU  - Cheng W
PY  - 2026
JO  - Frontiers in bioengineering and biotechnology
DO  - 10.3389/fbioe.2026.1762919
UR  - https://doi.org/10.3389/fbioe.2026.1762919
ER  -

APA

Y, Y., Y, Y., S, C., & W, C. (2026). Optimizing wearable IMU configurations for running gait analysis: a machine learning-based sensor fusion approach.. Frontiers in bioengineering and biotechnology. https://doi.org/10.3389/fbioe.2026.1762919

Source records

pubmed · retrieved 2026-09-26T17:55:42.458Z