Clinical-oriented three-dimensional gait analysis method for evaluating gait disorder

Masahiko Mukaino, Kei Ohtsuka, Hiroki Tanikawa, Fumihiro Matsuda, Junya Yamada, Norihide Itoh, Eiichi Saitoh

研究成果: Article

4 引用 (Scopus)

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Three-dimensional gait analysis (3DGA) is shown to be a useful clinical tool for the evaluation of gait abnormality due to movement disorders. However, the use of 3DGA in actual clinics remains uncommon. Possible reasons could include the time-consuming measurement process and difficulties in understanding measurement results, which are often presented using a large number of graphs. Here we present a clinician-friendly 3DGA method developed to facilitate the clinical use of 3DGA. This method consists of simplified preparation and measurement processes that can be performed in a short time period in clinical settings and intuitive results presentation to facilitate clinicians' understanding of results. The quick, simplified measurement procedure is achieved by the use of minimum markers and measurement of patients on a treadmill. To facilitate clinician understanding, results are presented in figures based on the clinicians' perspective. A Lissajous overview picture (LOP), which shows the trajectories of all markers from a holistic viewpoint, is used to facilitate intuitive understanding of gait patterns. Abnormal gait pattern indices, which are based on clinicians' perspectives in gait evaluation and standardized using the data of healthy subjects, are used to evaluate the extent of typical abnormal gait patterns in stroke patients. A graph depicting the analysis of the toe clearance strategy, which depicts how patients rely on normal and compensatory strategies to achieve toe clearance, is also presented. These methods could facilitate implementation of 3DGA in clinical settings and further encourage development of measurement strategies from the clinician's point of view.

元の言語English
記事番号e57063
ジャーナルJournal of Visualized Experiments
2018
発行部数133
DOI
出版物ステータスPublished - 04-03-2018

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All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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