SISSY: An efficient and automatic algorithm for the analysis of EEG sources based on structured sparsity.

Over the past decades, a multitude of different brain source imaging algorithms have been developed to identify the neural generators underlying the surface electroencephalography measurements. While most of these techniques focus on determining the source positions, only a small number of recently developed algorithms provides an indication of the spatial extent of the distributed sources. In a recent comparison of brain source imaging approaches, the VB-SCCD algorithm has been shown to be one of the most promising algorithms among these methods. However, this technique suffers from several problems: it leads to amplitude-biased source estimates, it has difficulties in separating close sources, and it has a high computational complexity due to its implementation using second order cone programming. To overcome these problems, we propose to include an additional regularization term that imposes sparsity in the original source domain and to solve the resulting optimization problem using the alternating direction method of multipliers. Furthermore, we show that the algorithm yields more robust solutions by taking into account the temporal structure of the data. We also propose a new method to automatically threshold the estimated source distribution, which permits to delineate the active brain regions. The new algorithm, called Source Imaging based on Structured Sparsity (SISSY), is analyzed by means of realistic computer simulations and is validated on the clinical data of four patients.

Enhancing audiovisual experience with haptic feedback: a survey on HAV.

Haptic technology has been widely employed in applications ranging from teleoperation and medical simulation to art and design, including entertainment, flight simulation, and virtual reality. Today there is a growing interest among researchers in integrating haptic feedback into audiovisual systems. A new medium emerges from this effort: haptic-audiovisual (HAV) content. This paper presents the techniques, formalisms, and key results pertinent to this medium. We first review the three main stages of the HAV workflow: the production, distribution, and rendering of haptic effects. We then highlight the pressing necessity for evaluation techniques in this context and discuss the key challenges in the field. By building on existing technologies and tackling the specific challenges of the enhancement of audiovisual experience with haptics, we believe the field presents exciting research perspectives whose financial and societal stakes are significant.

[Optical spectroscopy: a new approach to assess urological tumors]. / La spectroscopie optique : une nouvelle approche pour l'étude des tumeurs urologiques.

INTRODUCTION: Optical spectroscopy refers to a group of novel technologies that uses interaction of light with tissues to analyze their structure and chemical composition. The objective of this article is to describe these technologies and detail their potential for assessing urological tumors. MATERIAL AND METHODS: It has been shown that optical spectroscopy can accurately analyse multiple solid tumors. Several publications specifically aimed at assessing prostate cancers, renal carcinomas and urothelial tumors. RESULTS: There are three types of spectroscopy that all use light focussed on a tissue and thereafter collect a specific reflected optical signal. Optical spectroscopy can differentiate benign (adenoma or inflammation) and malignant (adenocarcinoma) prostatic tissues. It can also distinguish normal bladder tissue from inflammatory or cancerous cells. Regarding renal tumors, spectroscopy can identify normal and tumoral tissue and differentiate benign and malignant tumors. Its diagnostic accuracy is about 85%. However, reported studies only concentrate on in vitro or ex vivo specimen and the numbers of patients are quite small. CONCLUSION: Optical spectroscopy can be envisioned as an "optical biopsy" tool. Potential applications in the clinical field are promising. Larger studies on in vivo specimen need to be undertaken to confirm phase I preliminary reports.