How Far Are We from Achieving Self-Powered Flexible Health Monitoring Systems: An Energy Perspective

The rapid development of flexible electronics and sensing technologies have made it possible for the detection of various human vital signs and biomarkers through an extremely light-weight and soft device attached to the skin. To support such sensing devices for multi-parameter tracking and continuous operation, a powerful energy supply unit, which is compact, mobile, and with high energy density and self-charging capability, is desired. The recently emerged energy harvesting devices have demonstrated the potential of utilizing ambient and human-based energy sources to power sensor systems. In this context, this review aims to investigate the question of whether the capacity of current flexible energy devices can meet the energy demand of wireless flexible sensor systems in long-term health monitoring applications. First, the total energy demand of typical sensor systems is estimated by analyzing the energy consumption of each building block of the relevant systems. The design of the energy supply architecture is discussed by considering batteries/supercapacitors as the energy storage unit and photovoltaic, thermoelectric, piezoelectric, and triboelectric devices as the energy-harvesting unit. Based on the analysis, health monitoring protocols that could be readily realized with self-powered system designs are suggested and the core challenges for further development of the technologies for practical applications are identified.

Automated summary

The review investigates whether current flexible energy devices can meet the energy demand of wireless flexible sensor systems in long-term health monitoring applications. It estimates the total energy demand of typical sensor systems and discusses the design of the energy supply architecture. Health monitoring protocols that could be realized with self-powered system designs are suggested, and core challenges for further development of the technologies for practical applications are identified.