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Big Data Approach for Managing the Information from Genomics, Proteomics, and Wireless Sensing in E-health

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Big Data for Remote Sensing: Visualization, Analysis and Interpretation

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Abstract

This chapter aims to show that big data techniques can serve for dealing with the information coming from medical signal devices such as bio-arrays, electro-physiologic recorders, mass spectrometers and wireless sensors in e-health applications, in which data fusion is needed for the personalization of Internet services allowing chronic patients, such as patients suffering cardio-respiratory diseases, to be monitored and educated in order to maintain a comfortable lifestyle at home or at their place of life. Therefore, after describing the main tools available in the big data approach for analyzing and interpreting data, several examples of medical signal devices are presented, such as physiologic recorders and actimetric sensors used to monitor a person at home. The information provided by the pathologic profiles detected and clustered thanks to big data algorithms, is exploited to calibrate the surveillance at home, personalize alarms and give adapted preventive and therapeutic education.

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Acknowledgements

We acknowledge the Projects PHC Maghreb SCIM (Systèmes Complexes et Ingénierie Médicale), ANR e-swallhome and H3ABioNet for their financial support.

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Authors and Affiliations

  1. AGEIS, EA 7407, Faculty of Medicine, University Grenoble Alpes, 38700, La Tronche, France

    J. Demongeot

  2. RIADI, National Engineering School of Computer Sciences, Manouba University, 2010, Manouba, Tunisia

    M. Jelassi

  3. Escuela de Ingeniería Civil en Informática, Universidad de Valparaíso, General Cruz 222, Valparaíso, Chile

    C. Taramasco

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  1. J. Demongeot
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Editors and Affiliations

  1. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  2. Charotar University of Science and Technology, Changa, Gujarat, India

    Chintan Bhatt

  3. Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

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Demongeot, J., Jelassi, M., Taramasco, C. (2019). Big Data Approach for Managing the Information from Genomics, Proteomics, and Wireless Sensing in E-health. In: Dey, N., Bhatt, C., Ashour, A. (eds) Big Data for Remote Sensing: Visualization, Analysis and Interpretation. Springer, Cham. https://doi.org/10.1007/978-3-319-89923-7_1

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