Mark G. Frei

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PURPOSE We describe an algorithm for rapid real-time detection, quantitation, localization of seizures, and prediction of their clinical onset. METHODS Advanced digital signal processing techniques used in time-frequency localization, image processing, and identification of time-varying stochastic systems were used to develop the algorithm, which operates(More)
The need for novel, efficacious, antiseizure therapies is widely acknowledged. This study investigates in humans the feasibility, safety, and efficacy of high-frequency electrical stimulation (HFES; 100-500 Hz) triggered by automated seizure detections. Eight patients were enrolled in this study, which consisted of a control and an experimental phase. HFES(More)
PURPOSE Automated seizure detection and blockage requires highly sensitive and specific algorithms. This study reassessed the performance of an algorithm by using a more extensive database than that of a previous study and its suitability for safety/efficacy closed-loop studies to block seizures in humans. METHODS Up to eight electrocorticography (EcoG)(More)
Relevant and timely questions such as regarding the predictability of seizures and their capacity to trigger more seizures remain the subject of debate in epileptology. The present study endeavors to gain insight into these dynamic issues by adopting a non-reductionist approach and via the use of mathematical tools. Probability distribution functions of(More)
A dynamical analogy supported by five scale-free statistics (the Gutenberg-Richter distribution of event sizes, the distribution of interevent intervals, the Omori and inverse Omori laws, and the conditional waiting time until the next event) is shown to exist between two classes of seizures ("focal" in humans and generalized in animals) and earthquakes.(More)
The time-varying dynamics of epileptic seizures and the high inter-individual variability make their detection difficult. Osorio et al. [Osorio, I, Frei, MG, Wilkinson, SB. Real-time automated detection and quantitative analysis of seizures and short-term prediction of clinical onset. Epilepsia 1998;39(6):615-27] developed an algorithm that has had success(More)
We focus on an anomalous scaling region in correlation integral [C(epsilon)] analysis of electrocorticogram in epilepsy patients. We find that epileptic seizures typically are accompanied by wide fluctuations in the slope of this scaling region. An explanation, based on analyzing the interplay between the autocorrelation and C(epsilon), is provided for(More)
OBJECTIVE To examine the seizure prediction and detection abilities of the accumulated energy on multi-center data submitted to the First International Collaborative Workshop on Seizure Prediction. METHODS The accumulated energy (AE), windowed average power, and FHS seizure detection algorithm were applied to a single channel of ECoG data taken from the(More)
Substantive advances in clinical epileptology may be realized through the judicious use of real-time automated seizure detection, quantification, warning, and delivery of therapy in subjects with pharmacoresistant seizures. Materialization of these objectives is likely to elevate epileptology to the level of a mature clinical science.
PURPOSE The purpose of this study was to determine if stimulation of the left vagus nerve (LVNS) with the neurocybernetic prosthesis (NCP) in humans is, as claimed in the literature, without cardiac chronotropic actions. METHODS We analyzed 228 h of ECG recorded from five subjects with intractable epilepsy who had not benefited from LVNS, for effects on(More)