Hasan Al-Nashash

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Our proposed algorithm for seizure prediction is based on the principle that seizure build-up is always preceded by constantly changing bursting levels. We use a novel measure of residual subband wavelet entropy (RSWE) to directly estimate the entropy of bursts, which is otherwise obscured by the ongoing background activity. Our results are obtained using a(More)
In this paper, subband wavelet entropy (SWE) is used for the segmentation of electroencephalographic signals (EEG) recorded during injury and recovery following global cerebral ischemia. Wavelet analysis is used to decompose the EEG into standard clinical subbands followed by computation of the Shannon entropy. The EEG was measured from rodent brains in a(More)
In this paper, we propose a novel technique for extracting fetal electrocardiogram (FECG) from a thoracic ECG recording and an abdominal ECG recording of a pregnant woman. The polynomial networks technique is used to nonlinearly map the thoracic ECG signal to the abdominal ECG signal. The FECG is then extracted by subtracting the mapped thoracic ECG from(More)
Laser speckle imaging has increasingly become a viable technique for real-time medical imaging. However, the computational intricacies and the viewing experience involved limit its usefulness for real-time monitors such as those intended for neurosurgical applications. In this paper, we propose a new technique, tLASCA, which processes statistics primarily(More)
In this paper, spectral coherence (SC) is used to study the somatosensory evoked potential (SEP) signals in rodent model before and after spinal cord injury (SCI). The SC technique is complemented with the Basso, Beattie, and Bresnahan (BBB) behavior analysis method to help us assess the status of the motor recovery. SC can be used to follow the effects of(More)
This paper represents an ongoing investigation for surface myoelectric signal segmentation and classification. The classical moving average technique augmented with principal components analysis and time-frency analysis were used for segmentation. Multiresolution wavelet analysis was adopted as an effective feature extraction technique while artificial(More)
In this paper, the subband wavelet entropy (SWE) and its time difference are proposed as two quantitative measures for analyzing and segmenting the electroencephalographic (EEG) signals. SWE for EEG subbands, namely Delta, Theta, Alpha, Beta, and Gamma, is calculated and segmented using wavelet analysis. In addition, a time difference entropy measure was(More)
— Somatosensory evoked potentials (SEPs) were obtained from 15 rats that were inflected with graded injury using the NYU Impactor. SEPs, in response to stimuli to the nerves in the limbs, were recorded from the cranium. Spectral coherence was used to analyze these signals. Results obtained from the investigation show that this technique is capable of(More)
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Graded spinal cord injury was induced in rats using the NY-Impactor. Somatosensory evoked potentials (SEPs), in response to stimuli to the nerves in the limbs, were recorded from the cranium. These signals were analyzed using spectral coherence analysis. Results obtained from 15 rats show information that was missed when other techniques are used.