Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data.

Ogasawara T, Mukaino M, Matsunaga K, Wada Y, Suzuki T, Aoshima Y, Furuzawa S, Kono Y, Saitoh E, Yamaguchi M, Otaka Y, Tsukada S

Open source

DOI: 10.3389/fbioe.2023.1285945
Published: 2023
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.2023.1285945,
  title = {Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data.},
  author = {Ogasawara T and Mukaino M and Matsunaga K and Wada Y and Suzuki T and Aoshima Y and Furuzawa S and Kono Y and Saitoh E and Yamaguchi M and Otaka Y and Tsukada S},
  year = {2023},
  journal = {Frontiers in bioengineering and biotechnology},
  doi = {10.3389/fbioe.2023.1285945},
  url = {https://doi.org/10.3389/fbioe.2023.1285945}
}

RIS

TY  - JOUR
TI  - Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data.
AU  - Ogasawara T
AU  - Mukaino M
AU  - Matsunaga K
AU  - Wada Y
AU  - Suzuki T
AU  - Aoshima Y
AU  - Furuzawa S
AU  - Kono Y
AU  - Saitoh E
AU  - Yamaguchi M
AU  - Otaka Y
AU  - Tsukada S
PY  - 2023
JO  - Frontiers in bioengineering and biotechnology
DO  - 10.3389/fbioe.2023.1285945
UR  - https://doi.org/10.3389/fbioe.2023.1285945
ER  -

APA

T, O., M, M., K, M., Y, W., T, S., Y, A., S, F., Y, K., E, S., M, Y., Y, O., & S, T. (2023). Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data.. Frontiers in bioengineering and biotechnology. https://doi.org/10.3389/fbioe.2023.1285945

Source records

pubmed · retrieved 2026-09-27T11:01:38.082Z