System and method of generating control commands based on operator's bioelectrical data

A treatment method comprising:

• administering a treatment to a patient identified as having brain damage, traumatic brain injury, or a condition resulting in decreased and/or disturbed physical activity, including conditions associated with prolonged loss of mobility following surgery, injury, or accident, the treatment comprising steps of:
• a) providing a processor;
• b) providing a non-transitory computer readable storage medium having stored program instructions, the program instructions executable by the processor to:
• A) compute a dynamically adjustable virtual environment comprising a character of said patient located within said dynamically adjustable virtual environment;
• B) compute a virtual task to be performed by said patient using at least one imaginary movement within said dynamically adjustable virtual environment;
• C) collect bioelectrical data via electrodes configured to detect current from a body of said patient during said at least one imaginary movement, wherein said bioelectrical data comprises at least one of the following:
• i) said patient's electroencephalogram data being a set of actively signals of said patient's nervous system;
• said set characterized by a signal registration time and a signal amplitude thereof;
• and
• ii) said patient's electromyogram data being a set of activity signals of said patient's nervous system;
• said set characterized by a signal registration time and a signal amplitude thereof;
• D) extract at least one characteristic feature of said bioelectrical data collected during said at least one imaginary movement, wherein the at least one characteristic feature is selected from:
• a spectral characteristic, a time-series characteristic, a wavelet decomposition characteristic, a spatiotemporal characteristic and any combination thereof;
• E) classify said extracted characteristic features into an action pattern using an action pattern classification model configured to recognized imaginary movements based on patterns of actions configured in advance;
• F) compute a control command for said dynamically adjustable virtual environment based on said action pattern, by calculating parameters of the control command based on corresponding parameters of the action pattern and operation of a user interface;
• G) present on a display and within the user interface, the character performing an action in the dynamically adjustable virtual environment based on the control command;
• H) evaluate execution performance of the patient's at least one imaginary movement by calculating correlation values between actions performed by the character based on said control command corresponding to said patient's at least one imaginary movement and an expected state of the character defining accurate performance;
• and
• I) according to said correlation values, dynamically adapt a real-time visual feedback presented within the user interface, for indicating real-time performance of the executed virtual task of said patient within the dynamically adjustable virtual environment according to said patient's at least one imaginary movement.

A method of dynamic interaction with a user interface for real time rehabilitation and/or training of an operator via a dynamically adjustable virtual environment and using the operator's bioelectrical data, the method comprising steps of:

• a) providing a processor;
• b) providing a non-transitory computer readable storage medium having stored program instructions, the program instructions executable by the processor to:
• A) compute a dynamically adjustable virtual environment comprising a character of said operator located within said dynamically adjustable virtual environment;
• B) compute a virtual task to be performed by said operator using at least one imaginary movement within said dynamically adjustable virtual environment;
• C) collect bioelectrical data via electrodes configured to detect current from a body of said operator during said at least one imaginary movement, wherein said bioelectrical data comprises at least one of the following:
• i) said operator's electroencephalogram data being a set of actively signals of said operator's nervous system;
• said set characterized by a signal registration time and a signal amplitude thereof;
• and
• ii) said operator's electromyogram data being a set of activity signals of said operator's nervous system;
• said set characterized by a signal registration time and a signal amplitude thereof;
• D) extract at least one characteristic feature of said bioelectrical data collected during said at least one imaginary movement, wherein the at least one characteristic feature is selected from:
• a spectral characteristic, a time-series characteristic, a wavelet decomposition characteristic, a spatiotemporal characteristic and any combination thereof;
• E) classify said extracted characteristic features into an action pattern using an action pattern classification model configured to recognized imaginary movements based on patterns of actions configured in advance;
• F) compute a control command for said dynamically adjustable virtual environment based on said action pattern, by calculating parameters of the control command based on corresponding parameters of the action pattern and operation of a rehabilitation and/or training graphical user interface (GUI);
• G) present on a display and within the rehabilitation and/or training GUI, the character performing an action in the dynamically adjustable virtual environment based on the control command;
• H) evaluate execution performance of the operator's at least one imaginary movement by calculating correlation values between actions performed by the character based on said control command corresponding to said operator's at least one imaginary movement and an expected state of the character defining accurate performance;
• and
• I) according to said correlation values, dynamically adapt a real-time visual feedback presented within the adaptive rehabilitation and/or training GUI, for indicating real-time performance of the executed virtual task of said operator within the dynamically adjustable virtual environment according to said operator's at least one imaginary movement, thereby providing rehabilitation and/or training of said operator based on the at least one imaginary movement.