Abstract: High accuracy selections of grouped elements can be achieved using a brain machine interface. A neural decoding system can: receive a neural signal from a neural recording device, identify that the neural signal is representative of the user at least thinking of attempting to perform a gesture, which is one of a plurality of known gestures mapped to a plurality of commands, and output a command based on the gesture (the gesture is mapped to the command). A controller can be in communication with the neural decoding system and a display. The controller can: receive the command, if the gesture is a primary gesture, then select a group to be an active group of elements, if the gesture is a secondary gesture, then at least select an element of the active group of elements and output a response indicative of the group being activated and/or the element being selected.

Abstract: Sustained commands, such as drag and drop, scrolling, holding a position, and the like, can be performed by a user mentally controlling a controllable device via a brain-machine interface (BMI). Neural signals can be recorded by at least one neural recording device associated with a user and sent to the BMI, which can extract neural features from the neural signals. The BMI, which can include at least a Latch decoder, which can include a Gesture Type decoder and an Attempt decoder, can determine whether an action should be performed and a period of time the action should be held. If the action should be performed, then the controllable device can be controlled to perform the action for the period of time. If the action should not be performed, then the controllable device can be controlled to remain in a waiting state and/or a previous state.

Abstract: Instances of a single brain computer interface (BCI) system can be implemented on multiple devices. An active instance can control the associated device. The instances can each communicate with a neural decoding system that can receive neural signals from a user, process the neural signals, and output a command based on the processed neural signals. A device running the active instance of can be in communication with the neural decoding system to receive a command. The device can include a display, a non-transitory memory storing instructions, and a processor to execute the instructions to: run an instance of a control program; and execute the task based on the command.

Abstract: Instances of a single brain computer interface (BCI) system can be implemented on multiple devices. An active instance can control the associated device. The instances can each communicate with a neural decoding system that can receive neural signals from a user, process the neural signals, and output a command based on the processed neural signals. A device running the active instance of can be in communication with the neural decoding system to receive a command. The device can include a display, a non-transitory memory storing instructions, and a processor to execute the instructions to: run an instance of a control program; and execute the task based on the command.

Abstract: Neural signals of a subject intending certain postures can be decoded and a controllable device can be commanded to perform certain actions based on the decoded intended postures with a system, and method of use thereof, including a brain machine interface (BMI) device. The system also includes electrodes in communication with the subject's nervous system to record the neural signals and the controllable device, both in communication with the BMI device. The BMI device can store instructions and previously calibrated neural activity patterns for the certain postures and a processor for receiving the neural signals, pre-processing the neural signals, decoding the neural signals into neural activity patterns, and matching the neural activity patterns to the previously calibrated neural activity patterns. If a match is determined, then the BMI device can send a command, previously linked to the intended posture, to the controllable device to perform the action.

Abstract: Instances of a single brain computer interface (BCI) system can be implemented on multiple devices. An active instance can control the associated device. The instances can each communicate with a neural decoding system that can receive neural signals from a user, process the neural signals, and output a command based on the processed neural signals. A device running the active instance of can be in communication with the neural decoding system to receive a command. The device can include a display, a non-transitory memory storing instructions, and a processor to execute the instructions to: run an instance of a control program; and execute the task based on the command.

Abstract: The subject invention is an ECL to CMOS converter for converting high or low ECL logic signals. The converter comprises a CMOS inverter for providing low or high CMOS logic signals at its output in response to a first or second signal, respectively, applied to its input. The first signal must exceed a first predetermined value and the second signal must fall below a second predetermined value. The first and second predetermined values are such that either the low ECL signal does not fall below the second predetermined value or the high ECL signal does not exceed the first predetermined value. The converter also provides means for converting the high and low logic signals to the first and second signals, respectively.