1. A system for accelerating learning of a task using real-time data acquisition and analysis of real-time psychophysiological signals obtained from a user, the system comprising: one or more hardware processors; a monitoring module configured to, when executed by the one or more hardware processors, continuously monitor psychophysiological signal data collected from a plurality of sensors attached to a user during a pre-shot period of the task to be learned; an expertise profiler module configured to analyze the psychophysiological signal data to generate a current psychophysiological state of the user by computing one or more power spectral density indices from electroencephalographic activity of the user and converting the one or more power spectral density indices into one or more probabilities that the user's level of mental effort and engagement belongs to one of a plurality of classes using a discriminant function, compare the current psychophysiological state of the user to one or more goal states associated with expert performance of the task to be learned, and generate a set of control signals based on difference between the current psychophysiological state of the user to one or more goal states; and a real-time feedback generator configured to, when executed by the one or more hardware processors, during the pre-shot period, receive the control signals from the expertise profiler module, and generate at least one multimodality feedback signal to provide feedback to guide the user toward the one or more goal states, wherein the multimodality feedback signal is based on the control signals received from the expertise profiler module, wherein the feedback comprises a tactile indication to the user of the user's current psychophysiological state at a pace that replicates the user's heartbeat, and wherein the tactile indication of the user's current psychophysiological state decreases as the user's current psychophysiological state approaches an ideal shooting state for the task to be learned.