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On the quantification of Heart Rate Variability spectral parameters using time-frequency and time-varying methods
No full textIn the last decades, one of the main challenges in the study of heart rate variability (HRV) signals has been the quantification of the low-frequency (LF) and high-frequency (HF) components of the HRV spectrum during non-stationary events. At this regard,
different time–frequency and time-varying approaches have been proposed with the aim to track the modification of the HRV spectra during ischaemic attacks, provocative stress testing, sleep or daily-life activities. The quantitative evaluation of power (and frequencies) of the LF and HF components has been approached in various ways depending on the selected time–frequency method. This paper is an excursus through the
most common time–frequency/time-varying representation of the HRV signal with a special emphasis on the algorithms employed for the reliable quantification of the LF and
HF parameters and their tracking
Estimating the time-varing spectral parameters of heart rate variability using wigner distribution
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CTGAN in Augmentation of Radiomics Features Classification from Narrow Band Imaging for Laryngeal Cancer
No full textHEAD-MOUNTABLE DEVICE AND ECG DETECTION SYSTEM FOR DETECTING AN ELECTROCARDIOGRAM SIGNAL COMPRISING SAID HEAD-MOUNTABLE DEVICE
No full textThe present invention refers to an eyewear, in particular smart eyewear comprising an ECG detection system for
detecting an electrocardiogram (ECG) signal. Such ECG detection systems comprise a first electrode and a second
electrode generally mounted on a first temple and on a second temple of a frame of an eyewear respectively; in
details, the electrodes are mounted so as to face and contact the head of the user wearing the eyewear on opposite
sides. In this way the ECG signal detected by the electrodes is due to the potential difference of two head opposite
points. Moreover, thanks to this known ECG detection system the ECG signal can be continuously detected for all
time period the user wears the eyewear. However, the ECG signal so detected usually results to be weak and noisy
since potentials differences recorded on the head resulting from heart electrical activity are in the order of
microVolts and moreover the ECG signal can also be overlapped to electroencephalogram (EEG) signal.
Therefore, the monitoring based on the ECG signal detected with the known detection system is low-amplitue and
not sufficient reliable and accurate.
Another drawback of the known ECG detection systems is that the ECG detection is made continuously and so
the amount of data to be recorded is very high, thus requiring high storage space. This implies high costs.
The object of the present invention is to overcome the above-mentioned drawbacks and in particular to devise an
eyewear with an ECG detection system for detecting an ECG signal more reliable and accurate with respect to the
prior art
The Subspace Regularization Method Improves ErrP Detection by EEGNET in BCI Experiments
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