Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/121805
Title: ARTIFACT CHARACTERIZATION, DETECTION AND REMOVAL FROM NEURAL SIGNALS
Authors: MD KAFIUL ISLAM
Keywords: Artifact Detection, Artifact Removal, EEG, Neural Signal, Wavelet Transform, Seizure Detection
Issue Date: 21-Jul-2015
Citation: MD KAFIUL ISLAM (2015-07-21). ARTIFACT CHARACTERIZATION, DETECTION AND REMOVAL FROM NEURAL SIGNALS. ScholarBank@NUS Repository.
Abstract: Artifact detection and removal are important preprocessing steps for neural recordings to decode the neural signals properly and currently an active research problem. In this thesis, for the first time, artifacts found in the in-vivo neural recordings are studied and consequently a systematic artifact characterization is presented. Subsequently, three different artifact removal methods are proposed (one for in-vivo neural signals in general application and two for EEG data for two different application purposes, i.e. seizure detection and brain-computer interface (BCI) experiments). In order to evaluate the proposed methods quantitatively in comparison with available state-of-the-art methods, different artifact types have been extracted from real recordings for simulating artifact templates and hence to build a synthesized neural database on which the methods are applied. In addition, the effects of artifact removal on the later-stage processing have also been evaluated resulting significant performance improvement which proofs the efficacy of the proposed methods.
URI: http://scholarbank.nus.edu.sg/handle/10635/121805
Appears in Collections:Ph.D Theses (Open)

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