کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4058697 | 1265732 | 2006 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Visualisation of gait data with Kohonen self-organising neural maps
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
ارتوپدی، پزشکی ورزشی و توانبخشی
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چکیده انگلیسی
Self-organising artificial neural networks were used to reduce the complexity of joint kinematic and kinetic data, which form part of a typical instrumented gait assessment. Three-dimensional joint angles, moments and powers during the gait cycle were projected from the multi-dimensional data space onto a topological neural map, which thereby identified gait stem-patterns. Patients were positioned on the map in relation to each other and this enabled them to be compared from their gait patterns. The visualisation of large amounts of complex data in a two-dimensional map labelled with gait patterns is a step towards more objective analysis protocols which may enhance decision making.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Gait & Posture - Volume 24, Issue 1, August 2006, Pages 46–53
Journal: Gait & Posture - Volume 24, Issue 1, August 2006, Pages 46–53
نویسندگان
Gabor Barton, Adrian Lees, Paulo Lisboa, Steve Attfield,