基于光纤传感器心冲击信号的疲劳监测方法OA

To overcome the limitations of traditional fatigue detection methods based on behavioral or electrical signals,we pro-posed a fatigue monitoring method for ballistocardiogram(BCG)based on optical fiber Fabry-Perot pressure sensors.A"dual-channel denoising"strategy combining wavelet decomposition with high-pass and band-pass filtering was employed,and an adaptive beat-by-beat feature extraction algorithm was designed to enhance signal quality.Three volunteers were recruited complete the N-back task un-der sleep deprivation conditions,their electrocardiogram(ECG)and BCG signals were collected for comparative analysis.The results showed that the heart rate variability(HRV)indicators of ECG did not change significantly under the fatigue state,while the character-istic parameters of BCG showed a downward trend in the slope of the ascending line and fluctuations in the reflex index,indicated weakened cardiac contractile function and unstable autonomic nerve regulation.The proposed method demonstrates higher sensitivity to mild fatigue,with strong resistance to electromagnetic interference and good stability.It can provide a new approach for fatigue monito-ring in aviation and transportation safety applications.