The invention discloses a personalized physical
training load intelligent regulation and
control system based on multi-
modal physiological data fusion, and relates to the technical field of intelligent physical training and health monitoring. The
system comprises a multi-
modal data acquisition module, an intelligent fusion analysis module, a personalized decision module and a real-time regulation and control module. The method comprises the following steps: acquiring physiological, motion and environmental parameters of a user, and performing multi-
modal data fusion by using a
time sequence-causal attention mechanism to generate a comprehensive physiological state
feature vector; a dynamic personalized baseline is established based on a meta-learning framework, a load adjustment decision is generated by adopting a hierarchical
reinforcement learning algorithm, and regulation and control safety is ensured through
causal reasoning verification; and finally, load adjustment is executed through the real-time regulation and control module to form closed-
loop control. According to the method, the problems that in the prior art,
training load regulation depends on a single physiological parameter, the individuation degree is insufficient, and
decision making is lack of scientificity are solved, and accurate, self-adaptive and safe individualized physical training management is achieved.