Simulated prosthetic vision: improving text accessibility with retinal prostheses.

Image processing can improve significantly the every-day life of blind people wearing current and upcoming retinal prostheses relying on an external camera. We propose to use a real-time text localization algorithm to improve text accessibility. An augmented text-specific rendering based on automatic text localization has been developed.

Detection of T-wave beat-by-beat variations prior to ventricular arrhythmias onset in ICD-stored intracardiac electrograms: the Endocardial T-Wave Alternans Study (ETWAS).

Background: The aim of the Endocardial T-Wave Alternans Study was to prospectively assess the presence of T-wave alternans (TWA) or beat-to-beat repolarization changes on implantable cardioverter-defibrillator (ICD)-stored electrograms (EGMs) immediately preceding the onset of spontaneous ventricular tachycardia (VT) or fibrillation (VF).

Methods: Thirty-seven VT/VF episodes were compared to 116 baseline reference EGMs from the same 57 patients. A Bayesian model was used to estimate the T-wave waveform in each cardiac beat and a set of 10 parameters was selected to segment each detected T wave.

T-wave alternans detection using a Bayesian approach and a Gibbs sampler.

The problem of detecting T-wave alternans (TWA) in ECG signals has received considerable attention in the biomedical community. This paper introduces a Bayesian model for the T waves contained in ECG signals. A block Gibbs sampler was recently studied to estimate the parameters of this Bayesian model (including wave locations, amplitudes and shapes).

P- and T-wave delineation in ECG signals using a Bayesian approach and a partially collapsed Gibbs sampler.

Detection and delineation of P- and T-waves are important issues in the analysis and interpretation of electrocardiogram (ECG) signals. This paper addresses this problem by using Bayesian inference to represent a priori relationships among ECG wave components. Based on the recently introduced partially collapsed Gibbs sampler principle, the wave delineation and estimation are conducted simultaneously by using a Bayesian algorithm combined with a Markov chain Monte Carlo method.

Bayesian estimation of linear mixtures using the normal compositional model. Application to hyperspectral imagery.

This paper studies a new Bayesian unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of so-called endmembers. These endmembers are supposed to be random in order to model uncertainties regarding their knowledge.

OURSES: a telemedicine project for rural areas in france. Telemonitoring of elderly people.

Several telemedicine applications are proposed within the frame of OURSES project, French acronym for Offer of Rural Use of Services by Satellite, providing services for elderly people. The main objective of this project is to show the interest of using satellites as a complement to terrestrial technologies, in areas where telecommunication infrastructure is lacking or incomplete. This paper describes one of these applications: an ECG monitoring system.

Hyperspectral image compression: adapting SPIHT and EZW to anisotropic 3-D wavelet coding.

Hyperspectral images present some specific characteristics that should be used by an efficient compression system. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity. Some wavelet-based compression algorithms have been successfully used for some hyperspectral space missions.

Lost sample recovering of ECG signals in e-health applications.

This paper shows the interest of an interpolation method based on parametric modeling to retrieve missing samples in ECG signals. This problem occurs more and more with the emergence of telemedicine applications. The different links (fixed access network (PSTN), mobile access network (GSM/GPRS and future UMTS) or satellite interfacing (DVB-RCS technology)) involved in e-health applications are liable to induce errors on the transmitted data.

End-to-end signal processing from the embedded body sensor to the medical end user through QoS-less public communication channels: the U-R-SAFE experience.

The URSafe project (IST-2001-33352) aims at creating a telemedicine care environment for the elderly and convalescent. The idea is to provide a portable device which monitors autonomously different biomedical signals and is able to send an alarm to a medical center if an abnormality is detected. In the initial version of URSafe, three sensors where included in the platform: electrocardiogram (ECG), oxygen rate (SpO2) and Fall Detector.