Multiscale Hill-type modeling of the mechanical muscle behavior driven by the neural drive in isometric conditions.

In this study, we present a new model describing the mechanical behavior of the skeletal muscle during isometric contraction. This model is based on a former Hill-inspired model detailing the electromechanical behavior of the muscle based on the Huxley formulation. However, in this new multiscale model the muscle is represented at the Motor Unit (MU) scale.

Speedup computation of HD-sEMG signals using a motor unit-specific electrical source model.

Nowadays, bio-reliable modeling of muscle contraction is becoming more accurate and complex. This increasing complexity induces a significant increase in computation time which prevents the possibility of using this model in certain applications and studies. Accordingly, the aim of this work is to significantly reduce the computation time of high-density surface electromyogram (HD-sEMG) generation.

Extraction of the brachialis muscle activity using HD-sEMG technique and canonical correlation analysis.

The Brachialis (BR) is placed under the Biceps Brachii (BB) deep in the upper arm. Therefore, the detection of the corresponding surface Electromyogram (sEMG) is a complex task. The BR is an important elbow flexor, but it is usually not considered in the sEMG based force estimation process.

Realistic motor unit placement in a cylindrical HD-sEMG generation model.

The aim of this work is to assess an automatic optimized algorithm for the positioning of the Motor Units (MUs) within a multilayered cylindrical High Density surface EMG (HD-sEMG) generation model representing a skeletal muscle. The multilayered cylinder is composed of three layers: muscle, adipose and skin tissues. For this purpose, two different algorithms will be compared: an unconstrained random and a Mitchell's Best Candidate (MBC) placements, both with uniform distribution for the MUs positions.