Biofeedback: e-health prediction based on evolving fuzzy neural network and wearable technologies

Abstract Recent advances in wearable microelectronics and new neural networks paradigms, capable to evolve learn online such as the Evolving Fuzzy Neural Network (EFuNN), enable deploy of biofeedback-based applications. The missed physiologic response could be recovered by measuring uninvasively vital signs heart rate, bio impedance, body temperature, motion activity, blood pressure, oxygenation respiration rate. Then, prediction performed applying evolving ANN paradigms. simulation a biofeedback system has been executed (EFuNN) paradigm for prediction. An highly integrated microelectronic device measurement deployed. Simulation results demonstrate that control model an effective reference design enables short long-term e-health framework was then defined.