Recursive independent component analysis (ICA)-decomposition of ictal EEG to select the best ictal component for EEG source imaging.

Objective: This study aimed to present a new ictal component selection technique, named as recursive ICA-decomposition for ictal component selection (RIDICS), for potential application in epileptogenic zone localization.

Methods: The proposed technique decomposes ictal EEG recursively, eliminates a few unwanted components in every recursive cycle, and finally selects the most significant ictal component. Back-projected EEG, regenerated from that component, was used for source estimation.

Ictal EEG Source Imaging for Presurgical Evaluation of Refractory Focal Epilepsy.

Background: Electroencephalography source imaging (ESI) is a promising tool for localizing the cortical sources of both ictal and interictal epileptic activities. Many studies have shown the clinical usefulness of interictal ESI, but very few have investigated the utility of ictal ESI. The aim of this article is to examine the clinical usefulness of ictal ESI for epileptic focus localization in patients with refractory focal epilepsy, especially extratemporal lobe epilepsy.

Smartphone-based solutions for fall detection and prevention: challenges and open issues.

This paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention.