Method and system for brain activity signal-based treatment and/or control of user devices

1. A system for translating analog event-related desynchronization (ERD) signals from a user into an identifiable intended activity (IA), the system comprising:

a. at least one input to receive one or more ERD signals;

b. at least one output to send device action instructions to a user device to carry out a device action corresponding to the IA; and

c. a controller to communicate with the at least one input and the at least one output of the user device, the controller including at least one special purpose processor configured to run at least one computer program:

i. to record an ERD signal received from the at least one input, the ERD signal corresponding to an uncharacterized IA of the user for each time value of one or more successive time values,

ii. for each time value:

1. to access one or more ERD templates of coefficients for one or more characterized IA's, the ERD templates of coefficients being formed by correlating a plurality of time resolved frequency ERD signal values with a function approximating a synthetic ERD signal;

2. to update an ERD table for the uncharacterized IA and to compare the updated ERD table with the ERD templates to determine whether the uncharacterized IA is an instance of one of the characterized IA's; and

iii. to initiate a corresponding device action instruction on at the at least one output after a minimum number of time values necessary to determine whether the uncharacterized IA is an instance of one of the characterized IA's.

2. The system of claim 1 , wherein the at least one computer program is configured to identify the IA in response to achievement of a predetermined correlation count, wherein each count corresponds to a correlation between corresponding segments of the ERD templates of the characterized IA's and the updated ERD table of the uncharacterized IA.

3. The system of claim 2 , wherein the at least one computer program is configured to advance the correlation count in response to a minimum distance being recorded between corresponding segments of the ERD templates and updated ERD table of the characterized IA's and the uncharacterized IA respectively.

4. The system of claim 1 , further comprising the user device, wherein the user device includes a robotic arm or device, a full or partial limb prosthesis, an orthotic device, an electrical stimulation device, or an interface to a virtual device.

5. The system of claim 1 , wherein the at least one computer program is configured to initiate the device action instruction before the expiry of a pre-motor phase of a user action corresponding to the IA.

6. The system of claim 1 , wherein the ERD signal is an electroencephalographic (EEG) or an electrocorticographic (ECoG) signal, a magnetic signal, or a chemical signal.

7. The system of claim 1 , wherein the at least one input includes a single electrode.

8. A method for translating analog event-related desynchronization (ERD) signals from a user into an identifiable intended activity (IA) to form one or more ERD templates for use in associating an updated ERD table of an uncharacterized IA therewith to identify and initiate a corresponding intended device action by a user device, the method comprising:

a. recording one or more ERD signals from one or more electrodes operatively placed on the user, wherein each of the ERD signals corresponds to a characterized intended activity (IA) of the user for each time value of one or more successive time values;

b. for each time value, forming a temporo-spectral decomposition of the ERD signal, to form a plurality of time resolved frequency ERD signal values;

c. associating each ERD signal value with a function approximating a synthetic ERD signal to form at least one ERD table of coefficients collectively representative of the characterized IA;

d. repeating step c for a number of instances of the characterized IA to form a number of at least one ERD tables; and

e. forming the ERD template for the characterized IA from the number of ERD tables for the characterized IA.

9. The method of claim 8 , wherein the recording of the one or more ERD signals includes collecting one or more electrode signals from one or more electrodes, with one or more of the ERD tables being associated with a corresponding electrode signal.

10. The method of claim 8 , wherein the time values correspond to overlapping or non-overlapping time intervals.

11. The method of claim 8 , further comprising:

a. recording the ERD signal corresponding to an uncharacterized IA for a number of successive time values and updating an ERD table for the uncharacterized IA for each time value; and

b. associating the updated ERD table for the uncharacterized IA with the ERD template of the characterized IA to determine whether the uncharacterized IA is an instance of the characterized IA.

12. The method of claim 11 , further comprising issuing a device action instruction after a minimum number of time values necessary to determine whether the uncharacterized IA is an instance of the characterized IA.

13. The method of claim 12 , further comprising affirming that the uncharacterized IA is an instance of one of the characterized IA's in response to achievement of a predetermined correlation count, wherein each count corresponding to a correlation between corresponding segments of the updated ERD table of the uncharacterized IA and the ERD template of the characterized IA.

14. The method of claim 13 , further comprising advancing the correlation count in response to a minimum distance being recorded between corresponding segments of the updated ERD table and the ERD template.

15. The method of claim 14 , wherein the device action instruction occurs before an expiry of a pre-motor phase of an action corresponding to the affirmed IA.

16. The method of claim 15 , wherein the time duration between the device action instruction and the expiry of the pre-motor phase, is minimized and/or optimized.

17. The method of claim 16 , wherein the user device is one of a robotic arm or device, full limb prosthesis, partial limb prosthesis, or a user treatment device, a neuroprosthesis or functional electrical stimulation (FES) device that actuates a paralyzed limb, an orthotic device, or a virtual activity device.