Odin: um modelo de coleta adaptativa de sinais vitais

Abstract

Wearable devices emerged from the advancement of communication technology and the miniaturization of electronic components. These devices periodically monitor the user’s vital signs and generally have low battery life. This work proposes ODIN, a model for optimized collection of vital signs based on adaptive strategies. The comparison with related works indicates that ODIN is the only proposal that presents an adaptive collection of vital signs, which allows the optimized generation of context history. A prototype was implemented and in three groups. In the first group, simulations were performed in different scenarios, through requisition control, an increase of 114 % in battery life was obtained in the adaptive scenario compared to a collection without adaptivity. In the second group, the ODIN model was applied to a real physiological database and allowed for a reduction in the number of requests due to the adaptability of the collection. This reduction optimized battery consumption by 66 % compared to a collection without adaptability. Finally, in the third group, the model was applied in collecting data through an Arduino and also a cardiac monitoring strap available on the market (Polar H7). During this third part of the evaluation, savings of 18 % were observed in the power consumption of the mobile devices involved in the data collection.