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ELIZA cgi-bash version rev. 1.90
- Medical English LInking keywords finder for the PubMed Zipped Archive (ELIZA) -
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486851 occurrences (No.30 in the rank) during 5 years in the PubMed. [no cache] 500 found
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486851 occurrences (No.30 in the rank) during 5 years in the PubMed. [no cache] 500 found
| 243) The aim of this study was to present a new training algorithm using artificial neural networks called multi-objective least absolute shrinkage and selection operator (MOBJ-LASSO) applied to the classification of dynamic gait patterns. |
| PMID:23768190 DOI:10.1080/10255842.2013.803081 |
| 2015 Computer methods in biomechanics and biomedical engineering |
| * A new training algorithm using artificial neural networks to classify gender-specific dynamic gait patterns. |
| - The aim of this study was to present a new training algorithm using artificial neural networks called multi-objective least absolute shrinkage and selection operator (MOBJ-LASSO) applied to the classification of dynamic gait patterns. The movement pattern is identified by 20 characteristics from the three components of the ground reaction force which are used as input information for the neural networks in gender-specific gait classification. The classification performance between MOBJ-LASSO (97.4%) and multi-objective algorithm (MOBJ) (97.1%) is similar, but the MOBJ-LASSO algorithm achieved more improved results than the MOBJ because it is able to eliminate the inputs and automatically select the parameters of the neural network. Thus, it is an effective tool for data mining using neural networks. From 20 inputs used for training, MOBJ-LASSO selected the first and second peaks of the vertical force and the force peak in the antero-posterior direction as the variables that classify the gait patterns of the different genders. |
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