The present application relates to the technical field of intelligent
medical health monitoring, in particular to a new-born low
blood sugar early warning method in mother-infant room based on multi-parameter fusion, comprising the following steps: analyzing the heat production process and
oxygen consumption quantitative basal metabolic equivalent, evaluating the cold
exposure and high-frequency movement
energy consumption stress increment data, tracking the
swallowing reflex to evaluate
sugar intake combined with increment calculation energy gap to generate deficiency index, monitoring
microcirculation compensation and
muscle tremor amplitude to generate early warning intervention
instruction set. In the present application, the bottom
glycolysis dynamic evaluation mechanism is constructed to significantly strengthen the implicit
energy consumption quantitative tracking accuracy, the whole physiological
energy deficiency index is solved to effectively avoid the
physiological model distortion problem, the cross-
coupling mapping analysis is carried out combined with the
microcirculation compensation state and the
peripheral neuropathological tremor characteristics, the purity of the early warning
signal extraction in the
decompensation period is comprehensively improved, the
false alarm probability is greatly reduced, the intervention instruction triggering sensitivity is effectively enhanced, and the safety of the new-born is ensured.