The application provides a cerebral apoplexy postoperative sign
monitoring system, which is fused with a
nerve motor function evaluation wristband and a head-mounted brain
electrical impedance dynamic imaging device, and breaks through the blind area of
postoperative monitoring. The wristband device collects
upper limb electromyographic signals and joint motion
mechanics parameters through a microneedle
electrode array and a distributed piezoresistive sensor, drives a neural network to output a standardized motor
score based on time-
frequency domain features containing
electromyography,
joint angle, trajectory smoothness and
grip force change rate, and is related to a clinical Fugl-Meyer scale; the imaging device adopts a multi-ring
electrode array and an improved D-bar
algorithm to reconstruct a brain electrical
conductivity distribution map, constructs a multi-level
decision tree early warning model by extracting impedance change rate
Delta Z, spatial gradient entropy SGE and hemisphere
asymmetry Asym, and realizes
brain edema detection. Through multi-
modal data fusion and minute-level response, the
system solves the fragmentation problem of
postoperative monitoring and provides precise decision support for cerebral apoplexy
rehabilitation.