On the weighted-average relationship between plasma glucose and HbA1c.
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Blood Glucose↗
Biomedical subjects
Patrick E McSharry
Publications and source records attributed to Patrick E McSharry.
Prediction of epileptic seizures: are nonlinear methods relevant?
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Electroencephalography↗
A dynamical model for generating synthetic electrocardiogram signals.
A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator can specify the mean and standard deviation of the heart rate, the morphology of the PQRST cycle, and the power spectrum of the RR tachogram. In particular, both respiratory sinus arrhythmia at the high frequencies (HFs) and Mayer waves at the low frequencies (LFs) together with the LF/HF ratio are incorporated in the model. Much of the beat-to-beat variation in morphology and timing of the human ECG, including QT dispersion and R-peak amplitude modulation are shown to result. This model may be employed to assess biomedical signal processing techniques which are used to compute clinical statistics from the ECG.
Computer Simulation↗
Comparison of predictability of epileptic seizures by a linear and a nonlinear method.
The performance of traditional linear (variance based) methods for the identification and prediction of epileptic seizures are contrasted with "modern" methods from nonlinear time series analysis. We note several flaws of design in demonstrations claiming to establish the efficacy of nonlinear techniques; in particular, we examine published evidence for precursor identification. We perform null hypothesis tests using relevant surrogate data to demonstrate that decreases in the correlation density prior to and during seizure may simply reflect increases in the variance.
Algorithms↗