Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model-Reference-Cited by-同舟云学术

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Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model

Published:2018-06-29 Issue:1 Volume:8 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Mun Kyung-Ryoul,Song Gyuwon,Chun Sungkuk,Kim Jinwook

Funder

Sports Promotion Fund of Seoul Olympic Sports Promotion Foundation from Ministry of Culture, Sports, and Tourism

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41598-018-28222-2.pdf

Reference34 articles.

1. Perry, J. & Davids, J. R. Gait analysis: normal and pathological function. J. Pediatr. Orthoped. 12, 815 (1992).

2. Hannink, J. et al. Sensor-based gait parameter extraction with deep convolutional neural networks. IEEE J. Biomed. Health. 21, 85–93 (2017).

3. Yu, Z. & Lee, M. Human motion based intent recognition using a deep dynamic neural model. Robot. Auton. Syst. 71, 134–149 (2015).

4. Rueterbories, J., Spaich, E. G., Larsen, B. & Andersen, O. K. Methods for gait event detection and analysis in ambulatory systems. Med. Eng. Phys. 32, 545–552 (2010).

5. Muro-De-La-Herran, A., Garcia-Zapirain, B. & Mendez-Zorrilla, A. Gait analysis methods: An overview of wearable and non-wearable systems, highlighting clinical applications. Sensors. 14, 3362–3394 (2014).

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