The present application belongs to the technical field of biometric identification and
data processing, and particularly relates to a physiological
data monitoring and intelligent analysis
system for a kayak athlete. The
system comprises: an intelligent sensing
paddle device for collecting mechanical data and solving flow field characteristics; a multi-
modal physiological
information acquisition patch for analyzing
muscle recruitment sequence and limb posture; a core
data processing terminal for stripping
noise through adaptive filtering and constructing a fatigue efficiency model based on a deep neural network; and a biomechanical feedback execution component for inducing
muscle recruitment timing through
transcutaneous electrical stimulation. The present application introduces
underwater turbulent flow as a sensing pre-variable, realizes pre-forecasting of the fatigue inflection point and quantification of invisible
energy consumption, constructs a human-
machine integrated closed-loop intervention mechanism, and realizes real-time
impedance matching of
physiology and
mechanics. The present application can quantify
underwater propulsion efficiency and correct force action in real time without increasing the
cognitive load of the athlete, thereby improving training precision and avoiding sports injuries.