Haoxuan Li

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The success of applying dry sensor technology in measuring electroencephalogram (EEG) signals will have a significant impact on a wider adoption of brain activity monitoring in ambulatory as well as real life solutions. The presence of motion artifacts is the major obstacle in applying dry sensors for long-term EEG monitoring. In this paper we assess the(More)
A new method for automatically fitting the Liljencrants-Fant (LF) model to the time domain waveform of the glottal flow derivative is presented in this paper. By applying an extended Kalman filter (EKF) to track the LF-model shape-controlling parameters and dynamically searching for a globally minimal fitting error, the algorithm can accurately fit the(More)
A new approach to robust tracking of glottal LF-model parameters is presented. The approach does not rely on a new glottal source estimation algorithm, but instead introduces a new extensible multi-estimate fusion framework. Within this framework several existing algorithms are applied in parallel to extract glottal LF-model parameter estimates which are(More)
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