Identification of individual walking patterns using time discrete and time continuous data sets.
Scientific studies typically treat data by studying effects of groups. Clinical therapy typically treats patients on a subject specific basis. Consequently, scientific and clinical attempts to help patients are often not coordinated. The purposes of this study were (a) to identify subject and group specific locomotion characteristics quantitatively, using time discrete and time continuous data and (b) to assess the advantages and disadvantages of the two approaches. Kinematic and kinetic gait pattern of 13 female subjects walking in dress shoes with different heel heights (14, 37, 54 and 85 mm) were analysed. The results of this study showed that subject specific gait characteristics could be better identified with the time continuous than with the time discrete approach. Thus, the time continuous approach using artificial networks is an effective tool for identifying subject and group specific locomotion characteristics.
Schöllhorn
W I
WI
Universität Münster, Institut für Sportwissen Chaften Leonardo Campus 15, 48149 Münster, Germany. schoell@uni-muenster.de
Nigg
B M
BM
Stefanyshyn
D J
DJ
Liu
W
W
D000328:Adult; D000465:Algorithms; D016000:Cluster Analysis; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008875:Middle Aged; D016059:Range of Motion, Articular; D013997:Time Factors; D016138:Walking / Q000502:physiology*