In-home patient-focused rehabilitation system

• US 10,130,311 B1
• Filed: 05/18/2016
• Issued: 11/20/2018
• Est. Priority Date: 05/18/2015
• Status: Active Grant

• Current Assignee: HRL Laboratories LLC (The Boeing Co.)
• Original Assignee: HRL Laboratories LLC (The Boeing Co.)
• Inventors: De Sapio, Vincent, Chelian, Suhas E., Bhattacharyya, Rajan, Phillips, Matthew E., Ziegler, Matthias, Payton, David W.
• Primary Examiner(s): YEN, JASON TAHAI
• Application Number:
  US15/158,478
• Time in Patent Office: 916 Days
• Field of Search: None
• CPC Class Codes: A61B 2505/07 Home care
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/168 Evaluating attention deficit, hyperactivity
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/7455 characterised by tactile indication, e.g. vibration or electrical stimulation
• CPC Class Codes: A61H 1/02 Stretching or bending or torsioning apparatus for exercising
• CPC Class Codes: A61H 3/00 Appliances for aiding patients or disabled persons to walk about apparatus for helping babies to walk A47D13/04 ; applying electrical currents by contact electrodes for stimulating motor muscles, e.g. walking assistance A61N1/36003
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: G09B 19/003 Repetitive work cycles; Sequence of movements
• CPC Class Codes: G09B 5/02 with visual presentation of the material to be studied, e.g. using film strip
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Described is a system for patient-specific rehabilitation that can be performed outside a clinic. The system monitors a patient in real-time to generate a quantitative assessment of a physical state and a motivational state of the patient using sensor data obtained from sensors. Predictions related to the patient are generated utilizing patient-specific biomechanical and neurocognitive models implemented with predictive simulations. Video feed of the patient is registered with sensor data and a set of simulation data. Rehabilitation guidance instructions are conveyed to the patient through dialog-based interactions.

Claims

1. A system for patient user-specific rehabilitation, the system comprising:

one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of;

monitoring, using a Mobile Patient Monitor (MPM), sensor data obtained from a plurality of sensors in real-time to generate a quantitative assessment of a physical state and a motivational state of a user;

generating, using a Virtual Patient (VP) unit, predictions related to the user utilizing user-specific biomechanical and neurocognitive models implemented with predictive simulations;

generating rehabilitation guidance using a Virtual Coach (VC) unit through real-time communication with the VP unit;

registering, using an Augmented Reality (AR) unit, video feed of the user with sensor data from the MPM and a set of simulation data from the VP unit; and

conveying rehabilitation guidance instructions to the user through dialog-based user-VC interactions; and

a lightweight exoskeleton worn by the user configured to convey real-time rehabilitation guidance to the user.

2. The system as set forth in claim 1, wherein the one or more processors further performs an operation of generating at least one biomechanical state prediction with the VP unit using a set of motion and force measurements obtained with the MPM.

3. The system as set forth in claim 1, wherein the one or more processors further performs operations of:

processing the sensor data and a set of user profile data for use as simulation inputs to the VP unit;

generating model-based quantitative assessments of the user'"'"'s physical state and motivational state using the simulation inputs;

storing the model-based quantitative assessments in a user data archive; and

performing simulations to reveal biomechanical and neurocognitive information related to the user.

4. The system as set forth in claim 1, wherein the one or more processors further perform operations of:

abstracting a set of multi-dimensional time series vectors from the sensor data;

processing, by a Virtual Patient Cognitive Model (VPCM) of the VP unit, the set of multi-dimensional time series vectors;

generating a set of cognitive state estimates from the set of multi-dimensional time series vectors;

determining how the set of cognitive state estimates affect rehabilitation treatment outcomes through processing of the set of cognitive state estimates by the VC unit in order to choose a strategy for desired user results; and

storing a dynamic user profile, comprising the determined effect of the set of cognitive state estimates, in a rehabilitation knowledge base.

5. The system as set forth in claim 1, wherein the one or more processors further performs operations of:

guiding the user, with the VC unit, through rehabilitation treatment by applying a set of rehabilitation knowledge to the user'"'"'s specific needs through interaction with the VC unit;

generating candidate therapeutic actions using the set of rehabilitation knowledge; and

evaluating, with the user-specific biomechanical and neurocognitive models, likely outcomes if the candidate therapeutic actions are taken.

6. The system as set forth in claim 1, wherein the one or more processors further perform operations of:

generating, with the VP unit, a plurality of simulation feeds related to the user,

wherein a first simulation feed represents a user reference avatar, mirroring the user'"'"'s motion, and

wherein a second simulation feed represents a user goal avatar, representing motion that the VC unit is guiding the user toward.

7. A computer-implemented method for user-specific rehabilitation, comprising:

an act of causing one or more processors to execute instructions stored on a non-transitory memory such that upon execution, the one or more processors perform operations of;

monitoring, using a Mobile Patient Monitor (MPM), sensor data obtained from a plurality of sensors in real-time to generate a quantitative assessment of a physical state and a motivational state of a user;

generating, using a Virtual Patient (VP) unit, predictions related to the user utilizing user-specific biomechanical and neurocognitive models implemented with predictive simulations;

generating rehabilitation guidance using a Virtual Coach (VC) unit through real-time communication with the VP unit;

registering, using an Augmented Reality (AR) unit, video feed of the user with sensor data from the MPM and a set of simulation data from the VP unit;

conveying rehabilitation guidance instructions to the user through dialog-based user-VC interactions; and

conveying real-time rehabilitation guidance to the user via a lightweight exoskeleton worn by the user.

8. The method as set forth in claim 7, wherein the one or more processors further performs an operation of generating at least one biomechanical state prediction with the VP unit using a set of motion and force measurements obtained with the MPM.

9. The method as set forth in claim 7, wherein the one or more processors further performs operations of:

processing the sensor data and a set of user profile data for use as simulation inputs to the VP unit;

generating model-based quantitative assessments of the user'"'"'s physical state and motivational state using the simulation inputs;

storing the model-based quantitative assessments in a user data archive; and

performing simulations to reveal biomechanical and neurocognitive information related to the user.

10. The method as set forth in claim 7, wherein the one or more processors further perform operations of:

abstracting a set of multi-dimensional time series vectors from the sensor data;

processing, by a Virtual Patient Cognitive Model (VPCM) of the VP unit, the set of multi-dimensional time series vectors;

generating a set of cognitive state estimates from the set of multi-dimensional time series vectors;

determining how the set of cognitive state estimates affect rehabilitation treatment outcomes through processing of the set of cognitive state estimates by the VC unit in order to choose a strategy for desired user results; and

storing a dynamic user profile, comprising the determined effect of the set of cognitive state estimates, in a rehabilitation knowledge base.

11. The method as set forth in claim 7, wherein the one or more processors further perform operations of:

guiding the user, with the VC unit, through rehabilitation treatment by applying a set of rehabilitation knowledge to the user'"'"'s specific needs through interaction with the VC unit;

generating candidate therapeutic actions using the set of rehabilitation knowledge; and

evaluating, with the user-specific biomechanical and neurocognitive models, likely outcomes if the candidate therapeutic actions are taken.

12. The method as set forth in claim 7, wherein the one or more processors further perform operations of:

generating, with the VP unit, a plurality of simulation feeds related to the user,

wherein a first simulation feed represents a user reference avatar, mirroring the user'"'"'s motion, and

wherein a second simulation feed represents a patient user goal avatar, representing motion that the VC unit is guiding the user toward.

13. A computer program product for user-specific rehabilitation, the computer program product comprising:

computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having one or more processors for causing the processor to perform operations of;

monitoring, using a Mobile Patient Monitor (MPM), sensor data obtained from a plurality of sensors in real-time to generate a quantitative assessment of a physical state and a motivational state of a user;

generating, using a Virtual Patient (VP) unit, predictions related to the user utilizing user-specific biomechanical and neurocognitive models implemented with predictive simulations;

generating rehabilitation guidance using a Virtual Coach (VC) unit through real-time communication with the VP unit;

registering, using an Augmented Reality (AR) unit, video feed of the user with sensor data from the MPM and a set of simulation data from the VP unit; and

conveying rehabilitation guidance instructions to the user through dialog-based user-VC interactions; and

conveying real-time rehabilitation guidance to the user via a lightweight exoskeleton worn by the user.

14. The computer program product as set forth in claim 13, further comprising instructions for causing the one or more processors to perform an operation of generating at least one biomechanical state prediction with the VP unit using a set of motion and force measurements obtained with the MPM.

15. The computer program product as set forth in claim 13, further comprising instructions for causing the one or more processors to perform operations of:

processing the sensor data and a set of user profile data for use as simulation inputs to the VP unit;

generating model-based quantitative assessments of the user'"'"'s physical state and motivational state using the simulation inputs;

storing the model-based quantitative assessments in a user data archive; and

performing simulations to reveal biomechanical and neurocognitive information related to the user.

16. The computer program product as set forth in claim 13, further comprising instructions for causing the one or more processors to perform operations of:

abstracting a set of multi-dimensional time series vectors from the sensor data;

processing, by a Virtual Patient Cognitive Model (VPCM) of the VP unit, the set of multi-dimensional time series vectors;

generating a set of cognitive state estimates from the set of multi-dimensional time series vectors;

determining how the set of cognitive state estimates affect rehabilitation treatment outcomes through processing of the set of cognitive state estimates by the VC unit in order to choose a strategy for desired user results; and

storing a dynamic user profile, comprising the determined effect of the set of cognitive state estimates, in a rehabilitation knowledge base.

17. The computer program product as set forth in claim 13, further comprising instructions for causing the one or more processors to perform operations of:

guiding the user, with the VC unit, through rehabilitation treatment by applying a set of rehabilitation knowledge to the user'"'"'s specific needs through interaction with the VC unit;

generating candidate therapeutic actions using the set of rehabilitation knowledge; and

evaluating, with the user-specific biomechanical and neurocognitive models, likely outcomes if the candidate therapeutic actions are taken.