Characteristic extraction of tai chi movement data—based on self-powered wearable sensors

HIGHLIGHTS

• What: The authors propose a CM-WOA-based automatic dynamic sensor deployment optimization method for the feature extraction of Tai Chi action data. In view of the above problems, this paper will start with the integration of self-powered wearable sensors, a multilevel decision behavior recognition method with high recognition accuracy and high fault tolerance is studied. This research provided detailed insights into the postures of Tai Chi movements, contributing to a better understanding of the biomechanics involved. If the authors implement a duty cycle of 50% (i.e., the sensor is active for half of the . . .
  

   

  

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