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The Deductive Health Solutions FitAssess Musculoskeletal Assessment System is a SaaS, cloud-based software application that utilizes advanced AI, Deep-Learning, Neural Networking algorithms to accurately uncover muscular compensations and movement restrictions in the body that hinder muscular function and physical activity performance. The System has increased the muscular functionality and performance capabilities in hundreds of cases with professional, collegiate and amateur athletes as well as sport and fitness enthusiasts.

FitAssess is web-based and operates on computers and tablets. It operates in conjunction with WellnessLiving Management Software System, providing additional functionality with workouts, nutrition and deeper fitness routines.

FitAssess can be administered by a personal or physical trainer, sports clinician, or chiropractor. It can be learned in a short amount of time and requires no additional devices or exercise equipment. The FitAssess Assessment requires about twenty minutes to complete and the results are quickly available by email or pdf.

The resulting FitAssess Personal Stability Report includes detailed specifics about impacted muscular limitations and compensations that prevent high level physical activity and performance along with a visual Neuro-Mapping of potential spinal anomalies and stresses. It provides a detailed Prescriptive Workout "Plan-of-Action" to allow a trainer to schedule stretch-band exercises to correct the impacted muscular structure


Muscular Compensations

FitAssess is based on the concept that the body strives for equilibrium and balance - so that when one part of the body is limited or restricted, the body compensates by adding more activity and stress to another part.

Muscular Compensation, then, is an innovative way that the body adapts to a unstable musculoskeletal movement pattern. This compensation is part of an effort by the body to help reduce potential injuries until the root cause of the real movement impact is addressed.

FitAssessuncovers these muscular compensations and accurately reports the true causes of instability and deficiency in the body. The proprietary AI, Deep-Learning algorithms continously analyze and recalculates muscular movements to identify areas of muscular limitation and compensation.


AI Deep_Learning

FitAssess utilizes sophisticated, "state-of-the-art" musculoskeletal algorithms which interact with a cloud-based, complex anatomical deep-learning, neural network engine database. They continuously analyze the results of "Range-of-Motion" examinations to show musculoskeletal impacted areas.

The deep learning algorithms dynamically run, in real-time, through various layers of a proprietary muscular neural network, which is designed to continuously analyze all muscles and muscle groups which fail or deficiently respond under a Range-of-Motion tests. As each test is completed, the algorithms accurately predict potential musculoskeletal instabilities and record the results in an Output Queue.

The algorithms methodically search and cross reference:

All Potential Muscular Deficiencies in the Body
All Limitations identified by the Range-of-Motion Tests
All Joint Instabilities Contributing to the Identified Compensations
All current and/or Potential Spinal Abnormalities


FitAssess consists of 44 proprietary, individual "Range-of-Motion" tests developed to accurately measure the total scope of all muscular structures and compensations and restrictions in the body. With each successive test the System analyzes and recalculates all possible muscle and muscle group movements and their interactions across 700 possible affiliations.

Cervical Extension

Open and Closed Kinetic Chains

Open_Closed Chains

FitAssess also analyzes both Open and Closed Kentic Chains to track possible muscle movement deficiencies and compensations throughout the body.

A “Kinetic Chain” refers to the idea that the body is a system of interrelated segments that work together to produce everyday actions such as walking, running, jumping, and lifting.

In Closed chain movements, the end of the chain - the limb or limbs doing the movement - is fixed in place on the ground. For example, the squat, deadlift, pushup, and pull-up, in which your hands or feet remain stationary.

In Open chain movements the ends of the chain are not stationary. For example, the bench press, biceps curl, triceps extension, lateral raise)

AI, Deep-Learning, Neural Network Processing

FitAssess utilizes the most advanced AI, Deep-Learning Neural Network algorithms to analyze and predict muscular instabilities, weaknesses and deficiencies throughout the body.

The FitAssess AI, Deep-Learning Neural Network is comprised of a variety of node layers, containing an input layer, one or more hidden process layers, and an output layer. Each node within the network or "artificial neuron" represents an individual muscle or muscle group and connects to other nodes throughout the network. A single Range-of-Motion test might connect to a variety of other nodes modifying their results and their associated data weights and layer thresholds.

AI Neural Network

Contact Information

469-882-2654 Phone
18484 Preston Road
Suite 102-184
Dallas, Texas 75252


Based on AI, Deep-Learning, Neural Network Technology
A Proprietary Musculoskeletal Algorithm Which Analyzes and Cross References:

All Potential Muscular Deficiencies at Each of the Joints in the Body
All Limitatations Indentified by Range-Of-Motion Examinations
All Joint Instabilities Contributing to the Identified Deficiencies