Design and development of an impedimetric-based system for the remote monitoring of home-based dialysis patients.

A key clinical challenge is to determine the desired 'dry weight' of a patient in order to terminate the dialysis procedure at the optimal moment and thus avoid the effects of over- and under-hydration. It has been found that the effects of haemodialysis on patients can be conveniently monitored using whole-body bioimpedance measurements. The identified need of assessing the hydrational status of patients undergoing haemodialysis at home gave rise to the present Dialydom (DIALYse à DOMicile) project. The aim of the project is to develop a convenient miniaturised impedance monitoring device for localised measurements (on the calf) in order to estimate an impedimetric hydrational index of the home-based patient, and to transmit this and other parameters to a remote clinical site. Many challenges must be overcome to develop a robust and valid home-based device. Some of these are presented in the paper.

An integrated device to evaluate a driver's functional state.

In the field of cognitive ergonomics, research on car drivers requires multimodal in-vehicle systems for recording not only driving-related behavior, but also contextual information from their surroundings. In addition, reliable information concerning a driver's functional state should be obtained. In this article, we describe an integrated device simultaneously recording specific physiological data, video recordings of the driver and environment, parameters from the vehicle, and contextual data. Physiological signals from the autonomic nervous system provide objective and quantitative information on the driver's alertness and his/her ability to process specific driving-related stimuli or other nonspecific information. Consequently, recorded physiological responses can be related to individual driving events. Electrodermal and cardiac activities are sensitive to time-dependent variations in arousal level and to certain external stimuli, so there is great interest in studying drivers' behavior via measured physiological signals that have been established as suitable behavioral indicators. The present integrated device is capable of processing the relevant indices from raw measured data in real time.