Abstract
Analysis of registered signals is often a basis for decision making in various automation or decision support systems. Signals may contain noise and artifacts that are produced either by an environment or just are due to the method of their acquisition. In many cases, when the acquired signal is too contaminated, it is simply recorded once more. In some applications however, the re-recording is not feasible due to the fast paced changes in observed environment or due to application specific reasons. This is the cease during neurosurgical Deep Brain Stimulation (DBS) surgery when signals are recorded by electrodes inserted into patient’s brain. The recording of brain tissue electrical activity is done only once at any given location. As the presence of the artifacts heavily influences the signal characteristics, they have to be removed. The removal has also to salvage as much of the original recording as possible. This paper shows different approaches to the problem of the removal of the contaminating artifacts from the DBS recordings.
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Ciecierski, K.A. (2018). Methods of Automatic Artifact Removal in Neurobiological Signals. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2018. AUTOMATION 2018. Advances in Intelligent Systems and Computing, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-319-77179-3_7
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DOI: https://doi.org/10.1007/978-3-319-77179-3_7
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