Online Motion-Artifact Removal in fNIRS Signals: Combined Square-Root Cubature Kalman Filter and Weighted Moving Average Model Approach
| Autor: | Kunqiang Qing, Dalin Yang, Ruisen Huang, Keum-Shik Hong |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Artifact (error) business.industry Computer science 020208 electrical & electronic engineering 02 engineering and technology Filter (signal processing) Kalman filter Motion (physics) Software portability 020901 industrial engineering & automation Square root Moving average 0202 electrical engineering electronic engineering information engineering Computer vision Artificial intelligence business Optical filter |
| Zdroj: | 2020 20th International Conference on Control, Automation and Systems (ICCAS). |
| DOI: | 10.23919/iccas50221.2020.9268412 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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