SpasticSim: a synthetic data generation method for upper limb spasticity modelling in neurorehabilitation.

ABSTRACT: In neurorehabilitation, assessment of functional problems is essential to define optimal rehabilitation treatments. Usually, this assessment process requires distinguishing between impaired and non-impaired behavior of limbs. One of the common muscle motor disorders affecting limbs is spasticity, which is complicated to quantify objectively due to the complex nature of motor control. Thus, the lack of heterogeneous samples of patients constituting an acceptable amount of data is an obstacle which is relevant to understanding the behavior of spasticity and, consequently, quantifying it. In this article, we use the 3D creation suite Blender combined with the MBLab add-on to generate synthetic samples of human body models, aiming to be as sufficiently representative as possible to real human

SUBMITTER: de-la-Torre R 

PROVIDER: S-EPMC10796340 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature