Neuromechanical Cost Functionals Governing Motor Control for Early Screening of Motor Disorders

Autor: Aniruddha Sinha, Abhijit Das, Debatri Chatterjee, Kingshuk Chakravarty, Midhun P. Unni
Rok vydání: 2017
Předmět:
Zdroj: Frontiers in Bioengineering and Biotechnology, Vol 5 (2017)
Frontiers in Bioengineering and Biotechnology
ISSN: 2296-4185
DOI: 10.3389/fbioe.2017.00078
Popis: Developing a quantifier of the neural control of motion is extremely useful in characterizing motor disorders and personalizing the model equations using data. We approach this problem using a top down optimal control methodology, with an aim that the quantity estimated from the collected data is representative of the underlying neural controller. For this purpose, we assume that during the flexion of an arm, human brain optimizes a functional. A functional is defined as a function of a function which returns a scalar. Generally, in forward problems this functional is chosen to be a function of metabolic energy spent, jerkiness, variance of motion etc. integrated throughout the trajectory of motion. Current states (Angular configuration and velocity) and torque applied can approximately determine the motion of a joint. Therefore any internal cost-functional optimized by the brain has to have its effect in the control of the torque. In this work we study the flexion of the arm in normals and patient groups and intend to find the cost functionals governing the motion. To achieve this, we parametrize the cost functional governing the motion into the variables theta_p and omega_p which are then estimated using marker data obtained from the subjects. These parameters are shown to vary significantly for the normal and patient populations.The theta_p values were shown to be significantly higher in the case of patients than in the case of normals and omega_p values showed an exactly opposite trend. We also studied how these cost-functionals govern the applied torques in both subject groups and how is it affected while perturbed with sinusoidal frequencies. A time frequency analysis of the resulting solutions revealed a distinguishing pattern for the normals compared to the patient groups.
Databáze: OpenAIRE