Development of a mobile e-Health care system for rapid detection of emergent situations

In recent years, one of the common issues is an e-Health care system which makes available health management and medical services at any time and in any place. This study describes the development of an e-Health care system that can promptly detect and cope with emergent situations happening to chronic disease patients in their everyday life. If a patient's emergent situation is detected by a personal mobile host composed of acceleration and vibration sensors, GPS, and a code division multiple access communication module, a text message on the patient's current location is transmitted to the hospital and the guardian's mobile terminal, so that they can cope with the situation immediately. Particularly through a back-propagation network, the system analyzes data from sensors and determines emergent situations, such as fainting and seizures, promptly. The automatic diagnostic performance is measured by precision and recall from the data of a back-propagation neural network. The number of experiments for a normal walking state, seizure, and fainting situation is 200 each, respectively. Out of these experiments, fainting can be best diagnosed, with 90% precision. In that case, recall is 97%. The experiments show that this system is very effective in finding emergencies promptly for chronic disease patients who cannot take care of themselves, and it is expected to save many lives. The exact location of patients can also be found on the electronic map by using GPS information.