The present application relates to the technical field of
neural activity detection, in particular to a meditation sleep-aiding method and
system based on brain wave feedback, comprising the following steps: obtaining meditation
frequency band electroencephalogram
raw data, extracting amplitude extreme value and identifying wave peak trend, adjusting detection interval boundary, extracting micro-amplitude change to judge micro-structure, analyzing
dominant frequency drift trend to identify linkage characteristics, judging sleep-aiding
transition state to adjust ear side
signal, and monitoring wave amplitude trend to complete environment
mode switching. In the present application, the meditation depth change is identified through the linkage relationship between the
dominant frequency and the meditation degree, supplemented by real-
time perception of the hemispheric activity difference and linkage regulation of the ear side sound
signal parameters, so that targeted neural feedback intervention is effectively realized, while in the
stable state, multi-dimensional adjustment of sleep-aiding environment elements is driven, the precision and
feedback effect of
brain state regulation are enhanced, and the synchronous adaptability and dynamic response capability of meditation guidance and sleep-aiding intervention are effectively improved.