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Online Motion-Artifact Removal in fNIRS Signals: Combined Square-Root Cubature Kalman Filter and Weighted Moving Average Model Approach | IEEE Conference Publication | IEEE Xplore

Online Motion-Artifact Removal in fNIRS Signals: Combined Square-Root Cubature Kalman Filter and Weighted Moving Average Model Approach


Abstract:

One of the advantages of fNIRS systems is their portability for real-world applications. Therefore, the online rejection of the motion artifacts in functional near-infrar...Show More

Abstract:

One of the advantages of fNIRS systems is their portability for real-world applications. Therefore, the online rejection of the motion artifacts in functional near-infrared spectroscopy (fNIRS) signals is one of the essential research topics. We proposed a square-root cubature Kalman filter using a weighted moving average model to tract the dynamics of motion artifacts. The rationale and feasibility of the method were discussed using simulated data generated using a Balloon model. The results show that the proposed filter has a good suppression of spike-like motion artifacts. Finally, conclusions and further study are discussed.
Date of Conference: 13-16 October 2020
Date Added to IEEE Xplore: 01 December 2020
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Conference Location: Busan, Korea (South)

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