Perspectives of AI-enabled wearable
Research on exposome has been extended to personal exposures, and full assessment of personal exposures is of great significance to personal health monitoring and epidemiological studies. Compared to static measurement instruments, wearable sensors are more suitable for dynamic personal exposures assessment. The development of flexible wearable sensors with the features of human friendliness and ease-of-use can be a promising solution to the measurement of personal exposures. With the support of big data and AI, large-scale personal exposures assessment could foster the transition from population-based to individual-based epidemiological studies and upgrade the intelligence level of medical services.
Currently, over seven billion humans live on this planet, and individuals are simultaneously exposed to multifactorial stressors during their daily life. Regardless of the natural or artificial environments, changes in physical or chemical conditions in the environment may affect human health. Investigations of adverse health effects and their etiology, as well as suggestions for a healthier lifestyle, require an assessment of multifactorial personal exposures. The concept of the exposome was developed to assess the impact of multi-environmental exposures on the development of epidemiology.1 For example, it has been proved that urban air pollution can adversely affect the health of citizens. To assess the impact of the exposome on human health, some government projects have been initiated, for instance, the Human Early Life Exposome (HELIX) initiated in Europe.2 Sensor technology is the key fundamental entity to measure the exposome. In particular, intelligent wearable sensors, which are also called smart wearable sensors, can acquire, process, store, and transmit the electric signals generated by physical and/or chemical changes occurring in the environment, making them excellent recorders of personal exposures. Moreover, the development of wearable sensors makes it possible to assess local and dynamic personal exposures.3 Several advancements have been reported based on the development of multi-functional devices, particularly wearable and flexible electronics,4,5 in healthcare monitoring. However, the higher the number of sensors, the higher the requirements for both physical comfort and ease-of-use, which are difficult to achieve using the traditional silicon-based sensors. By wearing multi-functional flexible sensors, personal exposures and physical activities of individuals can be monitored,5 including larger movements, such as bending of elbows and legs, and smaller movements, such as heartbeat, breathing, swallowing, blood pressure, and muscle vibration. Moreover, with the support of artificial intelligence (AI) and big data,6 the effect of multi-personal exposures could be assessed, and personal physical health management can be optimized.
As a product of epidemiological studies, the exposome is a complement of the genome and refers to the measurement and assessment of environmental exposures over the course of a lifetime. Non-genetic exposures can be generally divided into three categories: internal, specific external, and general external. To clarify further, the specific external exposures refer to radiation, environmental pollutants, acoustic noise, heat stress, PM2.5, and so forth.
Cite this article
Shan, G., Li, X. and Huang, W. AI-Enabled Wearable and Flexible Electronics for Assessing Full Personal Exposures. The Innovation 1 (2), 100031 (2020). doi: 10.1016/j.xinn.2020.100031