mHealth System for the Early Detection of Infectious Diseases Using Biomedical Signals

Abstract

Early detection of infectious diseases is a major clinical challenge. When diagnosis comes after symptoms has a bad effect in health, but also spread a contagious approach towards other people. The proposed e-Health system supports the pre-diagnosis of these diseases. It gathers vital signs simultaneously (Electrodermal Activity, Body Temperature, Blood Pressure, Heart Beat Rate and Oxygen Saturation) from residents with a portable and easy-to-use biomedical sensors kit and managed with an Android App once a day. The processed data is uploaded to an online database for being used as SaaS to build the predicting models. The mHealth system may be operated by the same personnel on site not requiring to be medical or computational skilled at all. A real implementation has been tested and results confirm that the sampling process can be done very fast and steadily The same experiment showed that the manipulation of the App had a fast learning curve and no significant differences are observable in learning time by people with different skills or age. These usability factors are key for the mHealth system success.