The invention discloses a
pain management method based on bioelectrical impedance data and a
machine learning
algorithm, and relates to the technical field of
medical health, and the method comprises the steps: carrying out the phase
delay analysis of an impedance
phase spectrum matrix, calculating the change rate of a
phase angle of each frequency point along with time, and obtaining the
maximum phase lag time; according to the temperature field sequence and the
maximum phase lag time, time-space registration is carried out through a multi-
modal data fusion method and impedance modulus changes of the corresponding areas, and a pain biomarker feature
library is generated; through a bidirectional LSTM and a cross attention fusion method,
time sequence modeling and cross-
modal correlation analysis are carried out on bioelectricity
signal characteristics extracted by a sliding window and historical pain data, a dynamic
evolution rule of pain development is captured, a
pain management triple containing pain intensity, intervention response and prognosis evaluation is generated, and a
pain management result is obtained. And a quantitative basis is provided for
personalized treatment.