Kyungmin Su

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The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing(More)
Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral(More)
This paper introduces a prototype framework for content-based EEG retrieval (CBER). Like content-based image retrieval, the proposed framework retrieves EEG segments similar to the query EEG segment in a large database. Such retrieval of EEG can be used to assist data mining of brain signals by allowing researchers to understand the association between(More)
CBER (content-based-EEG-retrieval) systems present short data segments as query samples for similar segments in EEG databases. These systems have many applications in large-scale data-mining, but require effective and verifiable retrieval strategies. This paper introduces a new feature strategy based on class probabilities calculated by LIBSVM(More)
Domain adaptation methods can be highly sensitive to class balance, particularly the usually unknown balance of the unlabeled test set. In this work, we analyze the effect of imbalance on a well-known algorithm, ARTL (Adaptation Regularization Transfer Learning) and propose four approaches for mitigating the adverse effects of imbalance. These include (1)(More)
Common Spatial Patterns (CSP) is a popular feature extraction method for single-trial multichannel EEG classification in BCI applications. CSP generates spatial filters that optimize the distinction between two classes. The performance of CSP is highly dependent on how many filters are selected. However, in most BCI applications the number of filters is(More)
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