2019年7月
Prediction of Plantar Forces During Gait Using Wearable Sensors and Deep Neural Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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- 巻
- 2019
- 号
- 開始ページ
- 3629
- 終了ページ
- 3632
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1109/EMBC.2019.8857752
- 出版者・発行元
- IEEE
To enable on-time and high-fidelity lower-limb exoskeleton control, it is effective to predict the future human motion from the observed status. In this research, we propose a novel method to predict future plantar force during the gait using IMU and plantar sensors. Deep neural networks (DNN) are used to learn the non-linear relationship between the measured sensor data and the future plantar force data. Using the trained network, we can predict the plantar force not only during walking but also at the start and end of walking. In the experiments, the performance of the proposed method is confirmed for different prediction time.
- リンク情報
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- DOI
- https://doi.org/10.1109/EMBC.2019.8857752
- DBLP
- https://dblp.uni-trier.de/rec/conf/embc/NagashimaC0RTO19
- PubMed
- https://www.ncbi.nlm.nih.gov/pubmed/31946662
- URL
- https://www.wikidata.org/entity/Q92697698
- URL
- https://dblp.uni-trier.de/rec/conf/embc/2019
- URL
- https://dblp.uni-trier.de/db/conf/embc/embc2019.html#NagashimaC0RTO19
- ID情報
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- DOI : 10.1109/EMBC.2019.8857752
- ISBN : 9781538613115
- DBLP ID : conf/embc/NagashimaC0RTO19
- PubMed ID : 31946662