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As a new signal processing tool, a Modified frequency slice wavelet transform (MFSWT) is proposed for physiological signal time-frequency analysis in this study. The transform generates time-frequency representation from the frequency domain, and the reconstruction is independent of frequency slice function (FSF). To realize accurate time-frequency location of signal components, a bound signal-adaptive...
Electrocardiogram (ECG) signals obtained during driving simulations provide an indication of physiological response during complex driving tasks. The present study contributes to the literature on this response through the analysis of features in time-frequency representations, specifically, continuous wavelet transforms (CWTs). The main frequency band in the CWT of ECG signals, which corresponds...
In this paper we propose using the ECG bandgap storage area for coding high frequency details of the signal. Authorization-dependent access to these details allows privileged users for high precision analysis, while regular users with an access to standard resolution signal are still able to correctly calculate essential parameters. The proposed algorithm performs limited ECG interpretation, analysis...
Little attention has been paid so far to physiological signals for emotion recognition compared to audiovisual emotion channels such as facial expression or speech. This paper investigates the potential of physiological signals as reliable channels for emotion recognition. All essential stages of an automatic recognition system are discussed, from the recording of a physiological data set to a feature-based...
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