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BY 4.0 license Open Access Published by De Gruyter September 18, 2019

Simulation of Breathing Patterns and Classification of Sensor Data for the early detection of impending Sudden Infant Death

  • Michael Munz and Nicolas Wolf

Abstract

In this work, a methodology for the classification of breathing patterns in order to prevent sudden infant death (SID) incidents is presented. The basic idea is to classify breathing patterns which might lead to SID prior to an incident. A thorax sensor is proposed, which is able to simulate breathing patterns given by certain parameters. A sensor combination of conductive strain fabric and an inertial measurement unit is used for data acquisition. The data is then classified using a neural network.

Published Online: 2019-09-18
Published in Print: 2019-09-01

© 2019 by Walter de Gruyter Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 Public License.

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