Human-motion-training system

• US 20110275042A1
• Filed: 02/22/2011
• Published: 11/10/2011
• Est. Priority Date: 02/22/2010
• Status: Abandoned Application

• Current Assignee: Progyr, Inc.
• Original Assignee: Progyr, Inc.
• Inventors: Warman, David J., Handel, Peter A., Rasco, Bertis Charles
• Application Number:
  US12/932,335
• Publication Number:
  US 20110275042A1
• Time in Patent Office: Days
• US Class Current: 434/247
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: G06F 2218/00 Aspects of pattern recognition specially adapted for signal processing
• CPC Class Codes: G06V 40/23 Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G09B 19/0038 Sports
• CPC Class Codes: G09B 7/04 characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

Certain embodiments of the present invention are directed to automated human-motion-training systems. These automated human-motion-training systems include a hardware platform that provides for stored-instruction processing and that includes memory, an I/O interface, and an audio-signal generation and output component, and an operating system or control program that executes on the hardware platform and that provides a program-execution environment. The automated human-motion-training systems further include components of the human-motion-training system that provide for automated proctoring of human-motion exercises and training regimes, including monitoring of a user'"'"'s body position, producing feedback corresponding to a user'"'"'s body position, and determining a user'"'"'s performance in order to modify the exercises and training regimes so that they provide optimal-challenge-point-based training over the course of multiple repetitions and training sessions.

Claims

1. A human-motion-training system comprising:

a hardware platform that provides for stored-instruction processing and that includes memory, an I/O interface, and an audio-signal generation and output component;

an operating system or control program that executes on the hardware platform and that provides a program-execution environment; and

components of the human-motion-training system that provide for automated proctoring of human-motion exercises and training regimes, including monitoring of a user'"'"'s body position, producing feedback corresponding to a user'"'"'s body position, and determining a user'"'"'s performance in order to modify the exercises and training regimes so that they provide optimal-challenge-point-based training over the course of multiple repetitions and training sessions.

2. The human-motion-training system of claim 1

wherein the components of the human-motion-training system include a scheduler and a number of finite-state-machine-implementing plug-in modules or dynamic-library routines;

and

wherein the scheduler calls a routine for each finite state machine during each scheduler cycle, the routine returning a function pointer or reference through which the scheduler calls the finite state machine in a subsequent scheduler cycle.

3. The human-motion-training system of claim 2 wherein the finite state machines include:

a sensor finite state machine;

an analysis finite state machine; and

a synthesis finite state machine.

4. The human-motion-training system of claim 3 wherein the sensor finite state machine receives sensor output from one or more sensors , normalizes the received sensor output, and packages the normalized sensor output into sensor-information messages that the sensor finite state machine queues to a first first-in-first-out queue.

5. The human-motion-training system of claim 4 wherein the analysis finite state machine:

dequeues sensor-information messages from the first-in-first-out queue;

uses the sensor information contained in the dequeued sensor-information messages to prepare information messages regarding feedback appropriate for the current sensor positions and relative time within an exercise; and

queues the prepared information messages to a second first-in-first-out queue.

6. The human-motion-training system of claim 5 wherein the synthesis finite state machine:

dequeues information messages from the second first-in-first-out queue;

uses the analysis information contained in the dequeued information messages to launch a script that generates commands to control the audio-signal generation and output component to produce feedback.

7. The human-motion-training system of claim 1 wherein the components of the human-motion-training system prepare and store one or more computational envelopes and one or more time sequences of sensor positions to describe each exercise.

8. A human-motion-training system comprising:

one or more sensors mounted to known locations on a trainee'"'"'s body;

a sensor-data-acquisition-and-processing component that receives data from the one or more sensors to continuously monitor the trainee'"'"'s body position and compare the trainee'"'"'s body position to a computational envelope and time sequence of body positions, stored in an electronic memory, that define an exercise or training session and that generates one or more feedback signals that represent conformance of the trainee'"'"'s current body position to a current range of body positions specified by the computational envelope and time sequence of body positions stored in the electronic memory; and

a feedback component that receives the one or more feedback signals from the sensor-data-acquisition-and-processing component and renders the received one or more feedback signals into signals that can be perceived by the trainee.

9. The human-motion-training system of claim 8 wherein the one or more sensors are one or more of:

an accelerometer;

a gyroscope; and

a relative-position-determining device.

10. The human-motion-training system of claim 8 wherein the sensor-data-acquisition-and-processing component includes:

a number of finite-state-machine components; and

a scheduler that repeatedly cycles through the finite-state-machine components, invoking, in a particular scheduling cycle, each finit-state-machine component once.

11. The human-motion-training system of claim 10 wherein the finite-state-machine components include:

a sensor finite-state-machine component;

an analysis finite-state-machine component; and

a synthesis finite-state-machine component.

12. The human-motion-training system of claim 11 wherein the sensor finite-state-machine component continuously monitors the one or more sensors and prepares normalized sensor-data messages that are queued to a first input queue for the analysis finite-state-machine component.

13. The human-motion-training system of claim 12 wherein the analysis finite-state-machine component continuously monitors the first input queue for sensor-data messages and analyzes sensor data received in the sensor-data messages to determine the trainee'"'"'s body position, compare the trainee'"'"'s body position to the computational envelope and time sequence of body positions stored in the electronic memory to determine whether a feedback-related body-positioning event has occurred, and, when feedback-related body-positioning event has occurred, prepares an information message that the analysis finite-state-machine queues to a second input queue.

14. The human-motion-training system of claim 13 wherein the synthesis finite-state-machine component continuously monitors the second input queue for information messages and launches a feedback-signal-generating script to generate an appropriate feedback signal for the feedback-related body-positioning event indicated by one or more received information messages.

15. The human-motion-training system of claim 14 wherein the feedback-signal-generating script inputs control parameters to a signal-generating interface, such as a MIDI interface.

16. The human-motion-training system of claim 8 wherein the computational envelope represents the maximal extent of body position expected during the exercise.

17. The human-motion-training system of claim 8 wherein the time sequence of body positions represent the body motion that comprises the exercise.