Upper Extremity Joint Torque Estimation Through an Electromyography-Driven Model
Por:
Tahmid, S, Font-Llagunes JM and Yang, J
Publicada:
1 jun 2023
Resumen:
Cerebrovascular accidents like a stroke can affect the lower limb as
well as upper extremity joints (i.e., shoulder, elbow, or wrist) and
hinder the ability to produce necessary torque for activities of daily
living. In such cases, muscles' ability to generate forces reduces, thus
affecting the joint's torque production. Understanding how muscles
generate forces is a key element to injury detection. Researchers have
developed several computational methods to obtain muscle forces and
joint torques. Electromyography (EMG) driven modeling is one of the
approaches to estimate muscle forces and obtain joint torques from
muscle activity measurements. Musculoskeletal models and EMG-driven
models require necessary muscle-specific parameters for the calculation.
The focus of this study is to investigate the EMG-driven approach along
with an upper extremity musculoskeletal model to determine muscle forces
of two major muscle groups, biceps brachii and triceps brachii,
consisting of seven muscle-tendon units. Estimated muscle forces are
used to determine the elbow joint torque. Experimental EMG signals and
motion capture data are collected for a healthy subject. The
musculoskeletal model is scaled to match the geometric parameters of the
subject. Then, the approach calculates muscle forces and joint moment
for two tasks: simple elbow flexion extension and triceps kickback.
Individual muscle forces and net joint torques for both tasks are
estimated. The study also has compared the effect of muscle-tendon
parameters (optimal fiber length and tendon slack length) on the
estimated results.
Filiaciones:
Tahmid, S:
Texas Tech Univ, Dept Mech Engn, Human Ctr Design Res Lab, Lubbock, TX 79409 USA
Font-Llagunes JM:
Univ Politecn Cataluna, Dept Mech Engn, Biomech Engn Lab, Barcelona 08034, Catalonia, Spain
Univ Politecn Cataluna, Biomed Engn Res Ctr, Barcelona 08034, Catalonia, Spain
Inst Recerca St Joan Deu, Hlth Technol & Innovat, Esplugas de Llobregat, Catalonia, Spain
Yang, J:
Texas Tech Univ, Dept Mech Engn, Human Ctr Design Res Lab, Lubbock, TX 79409 USA
Green Published
|