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Traitement parcimonieux de signaux biologiques

Paul Chollet 1, 2
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : Body area sensor networks gained great focused through the promiseof better quality and cheaper medical care system. They are used todetect anomalies and treat them as soon as they arise. Sensors are under heavy constraints such as reliability, sturdiness, size and power consumption. This thesis analyzes the operations perform by a body area sensor network. The different energy requirements are evaluated in order to choose the focus of the research to improve the battery life of the sensors. A sensor for arrhythmia detection is proposed. It includes some signal processing through a clique-based neural network. The system simulations allow a classification between three types of arrhythmia with 95 % accuracy. The prototype, based on a 65 nm CMOS mixed signal circuit, requires only 1.4 μJ. To further reduce energy consumption, a new sensing method is used. A converter architecture is proposed for heart beat acquisition. Simulations and estimation show a 1.18 nJ energy requirement for parameter acquisition while offering 98 % classification accuracy. This work leads the way to the development of low energy sensor with a lifetime battery life.
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Submitted on : Tuesday, May 22, 2018 - 5:59:05 PM
Last modification on : Friday, September 25, 2020 - 3:35:51 AM


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  • HAL Id : tel-01797809, version 1


Paul Chollet. Traitement parcimonieux de signaux biologiques. Electronique. Ecole nationale supérieure Mines-Télécom Atlantique, 2017. Français. ⟨NNT : 2017IMTA0024⟩. ⟨tel-01797809⟩



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