کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
928849 922398 2009 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Motion pattern analysis of gait in horseback riding by means of Principal Component Analysis
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Motion pattern analysis of gait in horseback riding by means of Principal Component Analysis
چکیده انگلیسی

As a consequence of the three interacting systems of horse, saddle, and rider, horseback riding is a very complex movement that is difficult to characterize by a limited number of biomechanical parameters or characteristic curves. Principal Component Analysis (PCA) is a technique for reducing multidimensional datasets to a minimal (i.e., optimally economic) set of dimensions. To apply PCA to horseback riding data, a “pattern vector” composed of the horizontal velocities of a set of body markers was determined. PCA was used to identify the major dynamic constituents of the three natural gaits of the horse: walk, trot, and canter. It was found that the trot is characterized by only one major component accounting for about 90% of the data’s variance. Based on a study involving 13 horses with the same rider, additional phase plane analyses of the order parameter dynamics revealed a potential influence of the saddle type on movement coordination for the majority of horses.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Human Movement Science - Volume 28, Issue 3, June 2009, Pages 394–405
نویسندگان
, , ,