Fabio Oliva

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To propose a new feature extraction method with canonical solution for multi-class brain-computer interfaces (BCI). The proposed method should provide a reduced number of canonical discriminant spatial patterns (CDSP) and rank the channels sorted by power discriminability (DP) between classes. The feature extractor relays in canonical variates analysis(More)
This paper presents an application of Neural Networks (NNs) and Support Vector Machines (SVMs) for the detection and classification of heartbeats in electrocardiogram (ECG) signals. The preprocessing algorithm for the beats detection is based on well-known Pan-Tompkins' algorithm. The proposed approach is robust to different types of noise and shows good(More)
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