کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
382390 660760 2014 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Gait modification and optimization using neural network–genetic algorithm approach: Application to knee rehabilitation
ترجمه فارسی عنوان
اصلاح هدایت و بهینه سازی با استفاده از روش الگوریتم ژنتیک شبکه عصبی: کاربرد در توانبخشی زانو
کلمات کلیدی
اصلاح هدایت، مفصل زانو تیبوفومورال، شبکه عصبی تاخیر زمان الگوریتم ژنتیک، فشار تماس
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• Neural network and genetic algorithm were employed to design gait modification.
• A gait pattern was designed which decreased knee contact pressure up to 25%.
• The proposed methodology was cost-effective and easy to recreate for any subject.

Gait modification strategies play an important role in the overall success of total knee arthroplasty. There are a number of studies based on multi-body dynamic (MBD) analysis that have minimized knee adduction moment to offload knee joint. Reducing the knee adduction moment, without consideration of the actual contact pressure, has its own limitations. Moreover, MBD-based framework that mainly relies on iterative trial-and-error analysis, is fairly time consuming. This study embedded a time-delay neural network (TDNN) in a genetic algorithm (GA) as a cost effective computational framework to minimize contact pressure. Multi-body dynamic and finite element analyses were performed to calculate gait kinematics/kinetics and the resultant contact pressure for a number of experimental gait trials. A TDNN was trained to learn the nonlinear relation between gait parameters (inputs) and contact pressures (output). The trained network was then served as a real-time cost function in a GA-based global optimization to calculate contact pressure associated with each potential gait pattern. Two optimization problems were solved: first, knee flexion angle was bounded within the normal patterns and second, knee flexion angle was allowed to be increased beyond the normal walking. Designed gait patterns were evaluated through multi-body dynamic and finite element analyses.The TDNN-GA resulted in realistic gait patterns, compared to literature, which could effectively reduce contact pressure at the medial tibiofemoral knee joint. The first optimized gait pattern reduced the knee contact pressure by up to 21% through modifying the adjacent joint kinematics whilst knee flexion was preserved within normal walking. The second optimized gait pattern achieved a more effective pressure reduction (25%) through a slight increase in the knee flexion at the cost of considerable increase in the ankle joint forces. The proposed approach is a cost-effective computational technique that can be used to design a variety of rehabilitation strategies for different joint replacement with multiple objectives.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 16, 15 November 2014, Pages 7466–7477
نویسندگان
, , ,