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Foot-Healthcare Application Using Inertial Sensor: Estimating First Metatarsophalangeal Angle From Foot Motion During Walking
被引:5
|作者:
Huang, Chenhui
[1
]
Fukushi, Kenichiro
[1
]
Wang, Zhenwei
[1
]
Kajitani, Hiroshi
[1
]
Nihey, Fumiyuki
[1
]
Pokka, Hannah
[2
]
Narasaki, Hiroko
[2
]
Nakano, Hiroaki
[2
]
Nakahara, Kentaro
[1
]
机构:
[1] NEC Corp Ltd, Biometr Res Labs, Abiko, Chiba 2701174, Japan
[2] NEC Corp Ltd, Business Innovat Unit, Minato City, Tokyo 1088001, Japan
关键词:
Inertial sensor;
foot-motion;
foot health;
gait analysis;
hallux valgus;
GROUND REACTION FORCES;
HALLUX-VALGUS;
OLDER-ADULTS;
GAIT;
DEFORMITIES;
KINEMATICS;
PRESSURE;
CHILDREN;
PLANUS;
HEEL;
D O I:
10.1109/JSEN.2021.3138485
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
Our purpose was to demonstrate the possibility of providing foot-healthcare application by using an in-shoe motion sensor (IMS) throughvalidating the feasibilityof applying an IMS for measuring the first metatarsophalangeal angle (FMTPA), which is the most important parameter regarding the common foot problem hallux valgus. Methods: The IMS signals can represent foot motions when the mid-foot and hindfoot were modelled as a rigid body. FMTPAs can be estimated from the foot-motion signals measured using an IMS embedded beneath the foot arch near the calcaneus side using a machine-learning method. The foot-motion signals were collected from 50 participants with different FMTPAs. The true FMTPAs were assessed from digital photography. Correlation-based feature-selectionprocesses (significance levelp < 0.05) were used to search for the predictors from the foot-motion signals. Leave-one-subject-out cross-validation, root mean squared error, and intra-class coefficients were used for FMTPA-estimation model evaluation. Results: Eleven FMTPA-impacted gait-phase clusters, which were used to construct effective foot-motion predictors, were observed in all gait-cycle periods except terminal swing. The range of the foot motion in the sagittal and coronal planes significantly correlated with the FMTPA ( p < 0.05). Linear regression could be the best method for constructing an FMTPA estimation model with a root mean squared error and intra-class correlation coefficient of 4.2 degrees and 0.789, respectively. Conclusion: The results indicate the reliability of our FMTPA estimation model constructed from foot-motion signals and the possibility to providing foot-healthcare applications by using an IMS.
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页码:2835 / 2844
页数:10
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