MRI-based aortic blood flow model in 3D ballistocardiography.

Ballistocardiography (BCG) is a non-invasive technique which measures the acceleration of a body induced by cardiovascular activity, namely the force exerted by the beating heart. A one dimensional aortic flow model based on the transmission lines theory is developped and applied to the simulation of three dimensional BCG. A four-element Windkessel model is used to generate the pressure-wave. Using transverse MRI slices of a human subject, a reconstruction of the aorta allows the extraction of parameters used to relate the local change in mass of the 1D flow model to 3D acceleration BCG. Simulated BCG curves are then compared qualitatively with the ensemble average curves of the same subject recorded in sustained microgravity. Confirming previous studies, the main features of the y-axis are well simulated. The simulated z-axis, never attempted before, shows important similarities. The simulated x-axis is less faithful and suggests the presence of reflections.

Spike detection algorithm automatically adapted to individual patients applied to spike-and-wave percentage quantification.

OBJECTIVE: To report an innovative spike detection algorithm that tailors its detection to the patient. Interictal epileptiform activity quantification was accomplished in the setting of epileptic syndromes with continuous spike and waves during slow sleep, which is a time-consuming task for the EEG analysis. METHODS: The algorithm works in three steps. Firstly, a first spike detection is made with generic parameters. Secondly, the detected spikes are used to tailor the detection algorithm to the patient; and thirdly, the resulting patient-specific detection algorithm is used to analyze individual patient with high-quality detection. Therefore, the algorithm produces a patient-specific template -hence exhibiting improved performance metrics, without the need of a priori knowledge from the experts. RESULTS: The system was first evaluated for EEG of three patients, against the scoring of three EEG experts, demonstrating similar performance. Later, it was evaluated against the spike and wave percentage evaluation of another expert for 17 additional records. The difference between the two evaluations was 4.4% on average, which is almost the same as the interexpert difference (4.7%). CONCLUSIONS: We designed a fully automated and efficient spike detection algorithm, which is liable to trim down the specialist's diagnostic time.

Reduction of power line interference using active electrodes and a driven-right-leg circuit in electroencephalographic recording with a minimum number of electrodes.

Unwanted power line interference is one of the most common problems in electroencephalographic recording. This paper examines how the use of active electrodes together with a driven-right-leg circuit can significantly improve interference reduction, even when the same electrode is used for common and reference which is attractive because it saves an electrode. General conclusions about the active electrodes and the driven-right-leg circuits were obtained thanks to a prototype that uses the same electrode for both common and reference. Measurements were performed both on a subject and on an electrical equivalent model.