Methods and systems of embodiment training in a virtual-reality environment

1 . A computerized method for extracting and interpreting features of a user's motion in a virtual reality (VR)-based exercise with specified populations comprising:

tracking a user's motion in a VR-based exercise with a head mounted display, a set of jitter sensors worn by a user, and two hand controllers;

based on a set of datapoints obtained from a sequence of positions of the two hand controllers, extracting a set of motion characteristics of the user's motion;

based on motion characteristics, determining a velocity, an acceleration, a dynamic range, and a variability of the user's motion;

determining a coefficient of variation for the velocity and the acceleration;

based on the dynamic range, determining a variability in velocity and a variability of acceleration of the user's motion;

determining the coefficient of variation for the variability in velocity and the variability of acceleration of the user's motion;

from the acceleration and velocity data, calculating a multivariate characteristic of motion;

classifying a motion based on a combinatorial statistic from the extracted features;

determining a set of features of the user's motion represented by the combinatorial statistic that correlates to another combinatorial statistic associated with a specified population;

displaying a VR view of an avatar of the user performing the VR-based exercise, wherein the avatar of the user performs the VR-based exercise at a greater range of motion than the user,

wherein the specified population comprises a population with a specified muscular skeletal injury,

comparing the set of features of the user's motion with a set of statistical parameters of the set of injured users' VR-based motions, and

determining, based on the comparing, a health, injury, or impairment state of the user;

obtaining a user range of motion (ROM) relevant to a VR-based therapeutic exercise;

comparing the user ROM against an aspirational model ROM for the VR-based therapeutic exercise; and

adjusting a VR view of an avatar of the user at one or specified portions of the VR-based therapeutic exercise to simulate the aspirational model ROM;

with a set of jitter sensors worn by the user, measuring a jitter of the user performing the VR-based exercise; and,

when a user performs a movement in a smooth manner as indicated by low jitter sensed by the jitter sensors worn by the user, placing VR targets at a greater distance for the user and expanding a degree of motion from a first degree to a second degree;

as the jitter of the user performing the VR-based exercise decreases, increasing the range of motion of the VR-based exercise;

receiving and interpreting a user voice word input to measure a boundary of user motion with respect to a pain threshold, and wherein the voice word input comprises a plurality of verbal word indicators that the user is outside of a pain free range of motion;

measuring a set of user movement characteristics that correlate with a pain value experienced by the user doing a therapeutic avatar animation exercise, wherein the set of user movement characteristics comprises pain free range of motion, angular velocity changes in 3D space, compensations, shakiness, or jitter;

comparing the set of features of the user's motion with an idealized exercise motion and determining a quality of the user's motion, wherein the quality of movement is measured by an angular velocity of a positional sensor worn by the user; and

generating a diagnostic score based on output of (i) the measuring of the set of user movement characteristics and (ii) measuring time of user reactions during the therapeutic avatar animation exercise, and displaying the diagnostic score to a clinician to adjust therapeutic avatar animation settings.

2 . The computerized method of claim 1 , wherein the dynamic range comprising a reach distance of the user reached in an x-plane, a y-plane and a z-plane.

3 . The computerized method of claim 2 , wherein the specified population comprises a healthy populations, a population with specified disease state, a population with a specified muscular skeletal injury, a population with shoulder pain or a population with an upper extremity chronic pain.

4 . The computerized method of claim 1 further comprising:

measuring the dynamic range and variability within initiation of the user's motion.