Shared / assistive control

Shared or assistive control blends the user's decoded command with autonomy supplied by the effector, so the machine handles part of the task and the neural signal need not specify every degree of freedom moment to moment. In a robotic-arm reach, computer vision can identify a target object and plan the fine approach and grasp, while the decoded intent chooses which object and roughly where to go; the system arbitrates between the two continuously. This reduces the effective control dimensionality the decoder must supply and makes complex manipulation feasible with imperfect neural signals.

The term also covers training-time assistance, where during calibration the cursor or arm is nudged toward the target by an assist vector mixed with the decoded command, so early sessions succeed even before the decoder is good. Assistance is typically faded out as control improves. The central design question is arbitration: how much autonomy to grant, when, and how to keep the user feeling in control rather than overridden — too much assistance produces good task scores but a loss of agency and generalization, while too little makes the task exhausting.