تعیین نیرو در کاراندازهای عضله ‌تاندون مختلف با استفاده از شبکه‌ی عصبی

نوع مقاله : مقاله های پژوهشی

نویسندگان

1 استادیار، گروه مهندسی مکانیک، دانشکده‌ی مهندسی، دانشگاه بوعلی سینا، همدان

2 کارشناس ارشد، گروه مهندسی معدن، گروه مهندسی، دانشگاه بوعلی سینا همدان

چکیده

مقدمه: وابستگی نیروی عضلانی به عوامل متعدد، باعث ایجاد محدودیت‌هایی در ارایه‌ی یک رابطه‌ی ریاضی صریح به منظور پیش‌بینی نیروی عضلانی گشته است. به علت اهمیت این رابطه در مسایل مختلف اسکلت عضلانی و در زمینه‌ی آنالیز حرکت، ارایه‌ی راهکارهایی برای تخمین تئوری نیروی عضلانی امری ضروری است. هر چند در مطالعات مختلف، روابط گوناگونی برای این منظور مطرح شده است، اما پیچیدگی ارتباط میان نیروی ایجاد شده در عضله و عوامل مؤثر در آن، باعث شده است تا تلاش برای ارایه‌ی یک رابطه‌ی ریاضی جامع با بازده محاسباتی بالا با مشکلات زیادی روبه‌رو شود. بنابراین روابط ارایه شده یا جامعیت لازم برای کاربرد در کاراندازهای عضله تاندون مختلف را ندارند و یا به شدت غیر خطی و حجیم هستند و دارای بازده محاسباتی مناسبی نیستند.روش‌ها: در این پژوهش پس از مرور روابط ریاضی مختلف ارایه شده برای پیش‌بینی نیروی عضلانی، از یک شبکه‌ی عصبی برای تخمین نیرو در کاراندازهای عضله تاندون استفاده شده است.یافته‌ها: در این پژوهش یک مدل با بازده محاسباتی بالا و پارامترهای محدود ارایه گردید که می‌تواند برای برآورد نیروی ایجاد شده در کاراندازهای عضله تاندون در طول و سرعت‌های انقباض متفاوت مورد استفاده قرار گیرد.نتیجه‌گیری: به کارگیری شبکه‌ی عصبی مصنوعی ما را قادر به برآورد سریع‌تر و دقیق‌تر نیروی عضلانی در شرایط مختلف می‌سازد. در اصل، این روش باعث افزایش راندمان محاسباتی و یا به عبارتی کاهش زمان حل خواهد شد.

کلیدواژه‌ها

عنوان مقاله [English]

Utilizing an Artificial Neural Network for Musculotendon Actuator Force Estimation

نویسندگان [English]

  • Mohsen Sadeghimehr 1
  • Davood Naderi 1
  • Mesbaholreza Sharifi 2
1 Assistant Professor, Department of Mechanical Engineering, School of Engineering, Bu-Ali Sina University, Hamadan, Iran
2 Department of Mining Engineering, School of Engineering, Bu-Ali Sina University, Hamadan, Iran
چکیده [English]

Background: Since muscle force depends on various factors, presenting explicit equations for predicting it is difficult. Due to the importance of these equations in different musculoskeletal problems and analysis of motion, proposing solutions for estimating muscle force is indisputable. Although numerous relations have been suggested, the complexity of relations between the caused musculotendon force and the effective factors leads to a lot of problems in suggesting efficient comprehensive computational equations. Thus, the previous proposed relations either do not have universality for estimating muscle force, or are too nonlinear, massive and inefficient.Methods: In this study, after reviewing previous mathematical relations for predicting muscle force, an artificial neural network was implemented to predict force in musculotendon actuators.Findings: The present study provided an appropriate and computationally efficient mathematical model with limited parameters. The model can be used to determine the forces generated by musculotendon actuators in various lengths and contraction velocities. Conclusion: Utilizing a neural network lets us estimate muscle force quicker and more accurately. This could fundamentally increase the computational efficiency in different musculoskeletal problems.

کلیدواژه‌ها [English]

  • Artificial Neural Network
  • Mathematical modeling
  • Musculotendon actuator muscle model

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  • تاریخ دریافت: 03 مرداد 1390
  • تاریخ بازنگری: 31 فروردین 1403
  • تاریخ پذیرش: 17 فروردین 1401

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