ACTUALITÉS (tout voir)
En 2019, le CNRS fête ses 80 ans (et le laboratoire I3S ses 30 ans). La délégation régionale du CNRS Côte d'Azur (DR20) dont fait partie le laboratoire propose des manifestations pendant toute l'année 2019.
ACTUALITÉS
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En 2019, le CNRS fête ses 80 ans (et le laboratoire I3S ses 30 ans). La délégation régionale du CNRS Côte d'Azur (DR20) dont fait partie le laboratoire propose des manifestations pendant toute l'année 2019.
The I3S LABORATORY
It's on the SophiaTech campus in the heart of the Sophia Antipolis technology park our laboratory conducts research in the field of information science and communication.
"Advancing knowledge, consider the economic and technological realities, while imagining tomorrow's solutions."
The I3S laboratory is one of the largest information and communication science laboratories in the French Riviera. it was one of first ones to settle down on Sophia Antipolis Science and Technology Park. It consists of a little less than 300 people. [+...]
In partnership with CNRS and INRIA, and numerous industrial collaborations, we work on the themes of innovative research at the cutting edge of science and technology: systems and networks ubiquitous, biology and digital health, modeling for environment interactions and practices. [+...]
The laboratory is organized in 4 teams:
COMRED team (French acronym for Communications, Networks, Embedded Systems, Distributed Systems)
MDSC team (French acronym for Discrete Models for Complex System)
SIS team (Signal, Image and Systems)
SPARKS team (Scalable and Pervasive softwARe and Knowledge Systems)
The 5 latest submissions recorded in HAL
FOCUS DU MOIS
A. Siqueira, A. F. Spirandeli, R. Moraes and V. Zarzoso, "Respiratory Waveform Estimation From Multiple Accelerometers: An Optimal Sensor Number and Placement Analysis," in IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 4, pp. 1507-1515, July 2019.
Respiratory patterns are commonly measured to monitor and diagnose cardiovascular, metabolic, and sleep disorders. Electronic devices such as masks used to record respiratory waveforms usually require medical staff support and obstruct the patients' breathing, causing discomfort. New techniques are being investigated to overcome such limitations. An emerging approach involves accelerometers to estimate the respiratory waveform based on chest motion. However, most of the existing techniques employ a single accelerometer placed on an arbitrary thorax position. The present work investigates the use and optimal placement of multiple accelerometers located on the thorax and the abdomen. The study population is composed of 30 healthy volunteers in three different postures. By means of a custom-made microcontrolled system, data are acquired from an array of ten accelerometers located on predefined positions and a pneumotachograph used as reference. The best sensor locations are identified by optimal linear reconstruction of the reference waveform from the accelerometer data in the minimum mean square error sense. The analysis shows that right-hand side locations contribute more often to optimal respiratory waveform estimates, a sound finding given that the right lung has a larger volume than the left lung. In addition, the authors show that the respiratory waveform can be blindly extracted from the recorded accelerometer data by means of independent component analysis. In conclusion, linear processing of multiple accelerometers in optimal positions can successfully recover respiratory information in clinical settings, where the use of masks may be contraindicated.
