Remote physical therapy and assessment of patients

1. A method for remote physical therapy and assessment, the method executed by an at least one processor, comprising:

notifying a patient of a scheduled prescribed activity via an on-location at least one client device or console;

identifying the patient with one or more sensors connected to or part of the at least one client device or console;

confirming, via the at least one client device or console, the patient's acknowledgment of the notification;

demonstrating, via a graphical interactive avatar displayed on the at least one client device or console, the prescribed activity to be carried out by the patient;

confirming, via the at least one client device or console, that the patient is undertaking or will be undertaking the prescribed activity;

capturing, via the one or more sensors, frames of the patient undertaking the prescribed activity;

processing the frames of the patient undertaking the prescribed activity;

the capturing of the frames being undertaken by a left sensor and a right sensor; and

the processing of the frames comprising:

transmitting the captured frames to an internal depth image processor, wherein the captured frames consist of pixel data of one or more captured scenes;

calculating, by the internal depth image processor, a depth of each pixel, to produce depth pixel values;

processing, by the internal depth image processor, of the depth pixel values to create a depth frame;

combining, by the internal depth image processor, the depth frames into a depth video stream;

applying a point cloud over the depth video stream; and

estimating position and orientation of the patient's body joint centers.

2. The method of claim 1 , wherein the frames are depth scene frames.

3. The method of claim 1 , wherein the one or more sensors are cameras, imagers, image capture devices, or depth cameras.

4. The method of claim 1 , wherein the processing occurs on the client device or console.

5. The method of claim 1 , further comprising:

instructing the patient to get into a specific position or orientation.

6. The method of claim 1 , further comprising:

transmitting the results of the processing of the frames to an AI game engine or a backend system, wherein the AI game engine or the backend system can analyze trends or changes in a movement of the patient; and

presenting the analyzed results to the patient via a graphical user interface on the client device or console.

7. The method of claim 1 , wherein failure to confirm patient's acknowledgment, or that the patient is undertaking or will be undertaking the prescribed activity, causes a notification to be sent to a care circle.

8. A system for remote therapy and assessment of patients, comprising:

one or more sensors to capture and transmit visual data;

an at least one on-location client device or console to display personalized instructions, having or connected to the one or more sensors, the at least one on-location client device or console having an at least one processor and a memory communicatively coupled to the at least one processor, the memory storing instructions executable by the processor to:

notify a patient of a scheduled prescribed activity via the on-location at least one client device or console;

identify the patient with the one or more sensors;

confirm, via the at least one client device or console, the patient's acknowledgment of the notification;

demonstrate, via a graphical interactive avatar displayed on the at least one client device or console, the prescribed activity to be carried out by the patient;

confirm, via the at least one client device or console, that the patient is undertaking or will be undertaking the prescribed activity;

capture frames of the patient undertaking the prescribed activity via the one or more sensors; and

process the frames of the patient undertaking the prescribed activity;

an interactive graphical user interface to display the personalized instructions on the at least one on-location client device; and

an AI virtual game engine, to analyze the captured frame data and produce updated personalized instructions;

the capturing of the frames being undertaken by a left sensor and a right sensor; and

the processing of the frames, comprising:

transmitting the captured frames to an internal depth image processor, wherein the captured frames consist of pixel data of one or more captured scenes;

calculating, by the internal depth image processor, a depth of each pixel, to produce depth pixel values;

processing, by the internal depth image processor, of the depth pixel values to create a depth frame;

combining, by the internal depth image processor, the depth frames into a depth video stream;

applying a point cloud over the depth video stream; and

estimating position and orientation of the patient's body joint centers.

9. The system of claim 8 , further comprising:

a network, whereby the network is connected to at least one of the one or more sensors, the at least one on-location client device or console, and the AI virtual game engine.

10. The system of claim 8 , wherein the frames are depth scene frames.

11. The system of claim 8 , wherein the one or more sensors are cameras, imagers, image capture devices, or depth cameras.

12. The system of claim 8 , wherein the processing occurs on the client device or console.

13. The system of claim 8 , further comprising:

instructing the patient to get into a specific position or orientation.

14. The system of claim 8 , further comprising:

transmitting the results of the processing of the frames to the AI virtual game engine or a backend system, wherein the AI virtual game engine or the backend system can analyze trends or changes in a movement of the patient; and

presenting the analyzed results to the patient via a graphical user interface on the at least one client device or console.

15. The system of claim 8 , wherein failure to confirm patient's acknowledgment, or that the patient is undertaking or will be undertaking the prescribed activity, causes a notification or alert to be sent to a care circle.

16. The system of claim 8 , further comprising:

instructing the patient to get into a specific position or orientation.

17. A non-transitory media having instructions for executing a method by a processor, the method comprising:

notifying a patient of a scheduled prescribed activity via an on-location at least one client device or console;

identifying the patient with one or more sensors connected to or part of the at least one client device or console;

confirming, via the at least one client device or console, the patient's acknowledgment of the notification;

demonstrating, via a graphical interactive avatar displayed on the at least one client device or console, the prescribed activity to be carried out by the patient;

instructing the patient to get into a specific position or orientation;

confirming, via the at least one client device or console, that the patient is undertaking or will be undertaking the prescribed activity;

capturing, via the one or more sensors, frames of the patient undertaking the prescribed activity; and

processing the frames of the patient undertaking the prescribed activity, wherein the processing comprises:

transmitting the captured frames to an internal depth image processor, wherein the captured frames consist of pixel data of one or more captured scenes;

calculating, by the internal depth image processor, a depth of each pixel, to produce depth pixel values;

processing, by the internal depth image processor, of the depth pixel values to create a depth frame;

combining, by the internal depth image processor, the depth frames into a depth video stream;

applying a point cloud over the depth video stream; and

estimating position and orientation of the patient's body joint centers;

transmitting the results of the processing of the frames to an AI game engine or a backend system, wherein the AI game engine or the backend system can analyze trends or changes in a movement of the patient; and

presenting the analyzed data to the patient via a graphical user interface on the at least one client device or console;

the capturing of the frames is undertaken by a left sensor and a right sensor.