http://hdl.handle.net/10362/2621 2013-06-19T23:28:04Z http://hdl.handle.net/10362/4327 Title: Potential dementia biomarkers based on the time-varying microstructure of sleep EEG spindles Authors: Ortigueira, M.D.; Ktonas, P. Y.; Golemati, S.; Xanthopoulos, P. Abstract: The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies. In this work, the sleep spindle is modeled as an AM-FM signal and parameterized in terms of six parameters, three quantifying the instantaneous envelope (IE) and three quantifying the instantaneous frequency (IF) of the spindle model. The IE and IF waveforms of sleep spindles from patients with dementia and normal controls were estimated using the time-frequency technique of Complex Demodulation (CD). Sinusoidal curve-fitting using a matching pursuit (MP) approach was applied to the IE and IF waveforms for the estimation of the six model parameters. Specific differences were found in sleep spindle instantaneous frequency dynamics between spindles from dementia subjects and spindles from controls. Description: Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale, Lyon, France August 23-26, 2007 2007-01-01T00:00:00Z http://hdl.handle.net/10362/4326 Title: Comparative analysis of time-frequency methods estimating the time-varying microstructure of sleep EEG spindles Authors: Ortigueira, M.D.; Xanthopoulos, P.; Golemati, S.; Sakkalis, V. Abstract: Parameter estimation for an assumed sleep EEG spindle model (AM-FM signal) is performed by using four time-frequency analysis methods. Results from simulated as well as from real data are presented. In simulated data, the Hilbert Transform-based method has the lowest average percentage error but produces considerable signal distortion. The Complex Demodulation and the Matching Pursuit-based methods have error rates below 10%, but the Matching Pursuit-based method produces considerable signal distortion as well. The Wavelet Transform-based method has the poorest performance. In real data, all methods produce reasonable parameter values. However, the Hilbert Transform and the Matching Pursuitbased methods may not be applicable for sleep spindles shorter than about 0.8 sec. Matching Pursuit-based curve fitting is utilized as part of the parameter estimation process. Description: Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006 2006-01-01T00:00:00Z http://hdl.handle.net/10362/4325 Title: Fractional central differences and derivatives Authors: Ortigueira, M.D. Abstract: Fractional central differences and derivatives are studied in this article. These are generalisations to real orders of the ordinary positive (even and odd) integer order differences and derivatives, and also coincide with the well known Riesz potentials. The coherence of these definitions is studied by applying the definitions to functions with Fourier transformable functions. Some properties of these derivatives are presented and particular cases studied. Description: Journal of Vibration and Control, 14(9–10): 1255–1266, 2008 2006-01-01T00:00:00Z http://hdl.handle.net/10362/4324 Title: ECG wave detector and delineation with wavelets Authors: Ortigueira, M.D.; Alves, L. B.; Batista, A. G.; Pinto, I. V. Abstract: Efficient R wave detection is a crucial preprocessing step of most of the ECG signal analysis . Likewis e, ECG delineation comprising P wave and QRS complex, is required for ECG processing, namely in High- Resolution Electrocardiography (HR-ECG). We have performed R wave detection using the Mexican Hat wavelet and achieved a sensibility Se=97.77 % and a positive prediction P+=99.46%. Our data is HR-ECG and the delineation process occurs in two steps: wavelet detection and application of the Task Force (Breithardt et al.)1 detection rules. Description: Proceedings of the International Conference on Computational Intelligence in Medicine Healthcare, CIMED 2005, Costa da Caparica, June 29 - July 1, 2005 2005-01-01T00:00:00Z