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Big Data Approach for Managing the Information from Genomics, Proteomics, and Wireless Sensing in Ehealth
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.