***Errors in compiling and prototype uploads have prevented biomachina from being publicly available at this time. The first demo video above is outdated and lacks the most recent features.

How do the physics of this project work?

Vectors drawn from superior to inferior joints (or to bodily axis) are repeatedly multiplied to find the time in the joint-angle range of motion where the external moment arm peaks. The direction vector for motion is then multiplied with template vectors to find the path it most closely matches.

Based on the limb’s direction of movement, the angle at the time of peak external moment is cross referenced with anatomical studies on internal moment arms. Using neuromechanical matching, we then determine the muscle receiving the greatest relative stimulus.

What is left before the project is fully uploaded in it’s final form?

• Vector/moment visualizations for maximum usability

• Rectifying upload issues with AWS

• Graphing capabilities for data analysis

Contact: lmaridgefield@icloud.com or machinabiodev@gmail.com for updated information about biomachina.

Neuromechanical matching is an expertimental theory that emphasizes the preferential activation of motor units,

but what does that mean?

To fully stimulate a muscle, one must recruit as many units as possible.

However, the CNS (central nervous system) can only do this for so many muscle groups.

Pursuant to neuromechanical matching, the muscles with best leverage (or greatest internal moment arm length) will be most recruited because they host the fibers best suited to exert torque.

As such, neuromechanical matching is a principle of efficiency. It does not state the prime mover—rather, it determines which muscle has the greatest number of its fibers recruited, and thus grows more.