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Classification of human gait based on fine Gaussian support vector machines using a force platform.
- Source :
- AIP Conference Proceedings; 2022, Vol. 2472 Issue 1, p1-8, 8p
- Publication Year :
- 2022
-
Abstract
- A force platform prototype for human gait classification as an alternative to vision-based and wearable sensor-based gait classification technologies is proposed. The primary sensors involved in this prototype were load cells. When a volunteer walks on the force platform, the load cells record signal changes corresponding to the walking pattern of the volunteer. These signals were digitized and amplified and stored in a micro-SD card. Five gait features were extracted from the stored data in the micro-SD card, and MATLAB classification learner was used for classification. An accuracy of 94% was observed with Fine Gaussian Support Vector Machines. This shows that the force platform is a good alternative to vision-based and wearable sensor-based gait classification technologies. [ABSTRACT FROM AUTHOR]
- Subjects :
- GAIT in humans
SUPPORT vector machines
FEATURE extraction
Subjects
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 2472
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- AIP Conference Proceedings
- Publication Type :
- Conference
- Accession number :
- 158625293
- Full Text :
- https://doi.org/10.1063/5.0092635