Nowadays physiological monitoring systems are becoming completely wearable devices, in healthcare, which are smart and power efficient devices for healthcare remote monitoring, diagnosis and prevention. The design and development of a new generation of sustainable and low-cost medical wearable devices present several challenges that need to be addressed from a global perspective. The ultimate intention of this PhD is to propose a novel solution for specific needs of medical wearables and exploit the characteristics of bio-signals to develop energy-efficient strategies using AI. PPG is an attractive bio-signal, especially for wearable applications used for PPG signal data collection and analysis.
The goal of my PhD is to optimize the power efficiency for the use of AI on wearables medical devices. This study addresses not only low power consumption but also sustainability, low cost and embedded intelligence while proposing an innovative solution for medical applications as use cases.