When Deductive Health Solutions started the overriding goal was to create a highly accurate Assessment System that showed a person's true musculoskeletal instabilities, weaknesses and deficiencies AND was easy to administer for the trainer. The process of creating the underlying AI, Deep-Learning algorithms took over four years to perfect and test..
The QLD Assessment System was created from extensive, detailed physiological data such as muscular associations to ranges of motion, neuro-muscular associations as well as muscle associations for joint stability.
After we consolidated all of the musculoskeletal data into an advanced neural network, we had to identify how we would accurately assess individuals. We discovered was that while goniometers, and other measuring devices were great for documenting the degree at which a joint was able to move, it did not provide the ability to know where the root cause of the deficiency was located.
For this reason, the QLD System documents which ranges of motion demonstrate compensations, and the proprietary AI algorithms do the rest. This results is a testing method that analyzes the body with the understanding that when joints have the same movement capabilities on both sides, the body will create and absorb forces equally. Compensations in movement patterns disrupt the body's ability to create and absorb forces equally thus creating more stress on the muscles, tendons, and joints leading to injuries and loss of balance