Potential of the genetic algorithm neural network in the assessment of gait patterns in ankle arthrodesis

Wen Lan Wu, Fong Chin Su, Yuh Min Cheng, You Li Chou

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

A genetic algorithm (GA)-based network model was developed for the assessment of gait patterns in ankle arthrodesis. The accuracy of the model was tested in categorizing different gait patterns. Further, the prediction ability of the GA-based model was compared with that of the stepwise variant of the linear discriminant method. Finally, the clinical implications of the results were interpreted.

Original languageEnglish
Pages (from-to)83-91
Number of pages9
JournalAnnals of biomedical engineering
Volume29
Issue number1
DOIs
Publication statusPublished - 2001 Jan 1

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Fingerprint Dive into the research topics of 'Potential of the genetic algorithm neural network in the assessment of gait patterns in ankle arthrodesis'. Together they form a unique fingerprint.

  • Cite this