In order to analyze the effect of sports training in real time and improve the output balance of data acquisition,a real-time data acquisition method for sports training based on wearable devices was proposed.The multi-sensor node information fusion method is adopted for real-time data fusion of sports training,the oscillation characteristics of real-time data output of sports training wearable devices are analyzed under different movement frequencies,and the amplitude analysis and quantitative fusion tracking and recognition of real-time data acquisition process of sports training wearable devices are carried out according to the peak measurement method.The feature extraction model of real-time data of sports training wearable devices is established,and the fusion processing af-ter data acquisition of sports training wearable devices is carried out in the Internet of Things environment,so as to realize online de-tection and output control of data.The simulation results show that the output balance of real-time data acquisition in sports training using this method is good,and the accuracy of data acquisition is close to 1.The amplitude of the proposed method fluctuates between-1 and 1,and the output bit error rate of the proposed method is 10-3 when the frequency offset is 0Hz and there is no single fre-quency interference.When the interference frequency is 2 000 kHz,it can reach 40 dB,which improves the ability of analyzing and sorting the real-time data of sports training.
维普
万方数据