Application US20200206503

MOTOR FUNCTION NEURAL CONTROL INTERFACE FOR SPINAL CORD INJURY PATIENTS
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US20200206503

1. An apparatus for assisting a patient having a spinal cord injury, the apparatus comprising: (4) (4)

an electrical brain signal monitoring interface configured to record at least one electrical brain signal of the patient;

a functional electrical stimulation (FES) device configured to connect via FES electrodes with a paralyzed portion of the patient that is paralyzed due to the spinal cord injury and to control the paralyzed portion of the patient by applying FES to the paralyzed portion of the patient via the FES electrodes;

an electronic processor operatively connected with the electrical brain signal monitoring interface to receive the at least one electrical brain signal and with the FES device to control the FES applied to the paralyzed portion of the patient; and

a non-transitory storage medium storing instructions readable and executable by the electronic processor, the instructions including: electrical brain signal demultiplexing instructions that are executable by the electronic processor to demultiplex the at least one electrical brain signal into an efferent motor intention signal and at least one afferent sensory signal; and

FES control instructions that are executable by the electronic processor to control the FES applied to the paralyzed portion of the patient by the FES device based on at least the efferent motor intention signal.

2. The apparatus of claim 1 wherein the electrical brain signal demultiplexing instructions are executable by the electronic processor to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal including at least an afferent touch sense signal generated by a touch sense of the paralyzed portion of the patient. (2) (0)

3. The apparatus of claim 2 further comprising: (0) (3)

4. The apparatus of claim 2 wherein the FES control instructions are executable by the electronic processor to control the FES applied to the paralyzed portion of the patient by the FES device based on at least the efferent motor intention signal and the afferent touch sense signal. (1) (0)

6. The apparatus of claim 1 wherein the electrical brain signal demultiplexing instructions are executable by the electronic processor to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal including at least an afferent proprioception sense signal generated by a proprioception sense of the paralyzed portion of the patient. (1) (0)

8. The apparatus of claim 1 wherein the FES control instructions are executable by the electronic processor to control the FES applied to the paralyzed portion of the patient by the FES device based on the efferent motor intention signal and not based on the at least one afferent sensory signal; or (0) (1)

9. The apparatus of claim 1 wherein the electrical brain signal demultiplexing instructions are executable by the electronic processor to apply a machine learning component to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal. (1) (0)

10. The apparatus of claim 9 wherein the instructions further include: (0) (3)

11. A non-transitory storage medium storing instructions readable and executable by an electronic processor that is operatively connected to receive at least one electrical brain signal from a patient and to operate a functional electrical stimulation (FES) device to apply FES to control a paralyzed portion of the patient that is paralyzed due to a spinal cord injury of the patient, the stored instructions including: (4) (2)

electrical brain signal demultiplexing instructions that are executable by the electronic processor to demultiplex the at least one electrical brain signal into an efferent motor intention signal and at least one afferent sensory signal; and

12. The non-transitory storage medium of claim 11 wherein the electrical brain signal demultiplexing instructions are executable by the electronic processor to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal including at least an afferent touch sense signal generated by a touch sense of the paralyzed portion of the patient. (2) (0)

13. The non-transitory storage medium of claim 12 wherein the electronic processor is further operatively connected with a haptic device to control a haptic signal delivered to the patient via the haptic device, and wherein the instructions further include touch sensory feedback instructions that are executable by the electronic processor to control the haptic signal delivered to the patient via the haptic device based on the afferent touch sense signal. (0)

14. The non-transitory storage medium of claim 12 wherein the FES control instructions are executable by the electronic processor to control the FES applied to the paralyzed portion of the patient by the FES device based on at least the efferent motor intention signal and the afferent touch sense signal. (1) (0)

16. The non-transitory storage medium of claim 11 wherein the electrical brain signal demultiplexing instructions are executable by the electronic processor to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal including at least an afferent proprioception sense signal generated by a proprioception sense of the paralyzed portion of the patient. (1) (0)

18. The non-transitory storage medium of claim 11 wherein the FES control instructions are executable by the electronic processor to control the FES applied to the paralyzed portion of the patient by the FES device based on the efferent motor intention signal and not based on the at least one afferent sensory signal. (0)

19. The non-transitory storage medium of claim 11 wherein the electrical brain signal demultiplexing instructions are executable by the electronic processor to apply a machine learning component to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal. (1) (0)

20. The non-transitory storage medium of claim 19 wherein the instructions further include: (0) (3)

21. A method comprising: (5) (4)

receiving at least one electrical brain signal from a patient;

by an electronic processor, demultiplexing the at least one electrical brain signal into an efferent motor intention signal and at least one afferent sensory signal; and

by the electronic processor, controlling a functional electrical stimulation (FES) device to apply FES to control a paralyzed portion of the patient that is paralyzed due to a spinal cord injury of the patient;

wherein the controlling of the FES device is based on at least the efferent motor intention signal.

22. The method of claim 21 wherein the demultiplexing comprises demultiplexing the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal including at least an afferent touch sense signal generated by a touch sense of the paralyzed portion of the patient. (1) (0)

24. The method of claim 21 wherein the controlling of the FES device is based on at least the efferent motor intention signal and the afferent touch sense signal. (1) (0)

25. The method of claim 24 wherein the controlling of the FES device includes: (0) (3)

26. The method of claim 21 wherein the demultiplexing comprises demultiplexing the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal including at least an afferent proprioception sense signal generated by a proprioception sense of the paralyzed portion of the patient. (1) (0)

28. The method of claim 21 wherein the controlling of the FES device is based on the efferent motor intention signal and is not based on the at least one afferent sensory signal. (0)

29. The method of claim 21 wherein the demultiplexing comprises applying a machine learning component to demultiplex the at least one electrical brain signal into the efferent motor intention signal and the at least one afferent sensory signal. (1) (0)

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Application US20200206503

MOTOR FUNCTION NEURAL CONTROL INTERFACE FOR SPINAL CORD INJURY PATIENTS

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