**1. Introduction**

Wearable technologies are becoming increasingly popular as personal health system, enabling continuous real-time monitoring of human health on a daily basis and outside clinical environments [1–3]. The wearable device market is currently having a worldwide profit of around \$34 billion and is expected to reach above \$50 billion by 2022 owing to wearables' ease of use, flexibility, and convenience [4]. Real-time monitoring, operational efficiency, and fitness tracking are reported as main factors supporting the market growth of health wearable devices such as smart watches, smart glasses, and other wellness gadgets, with expected \$12.1 billion world market by 2021 [5].

In the past decade, the recent progress in developing wearable devices was more focused on monitoring physical parameters, such as motion, respiration rate, etc. [3, 6, 7]. Today, there is a great interest in evolving wearable sensors capable of detecting chemical markers relevant to the status of health. Different approaches have been applied by researchers to design and fabricate wearable biosensors for remote monitoring of metabolites and electrolytes in body fluids including tear, sweat, and saliva [3, 8–10]. A great example would be the development of small and reliable sensors that would allow continuous glucose monitoring in diabetic patients [11, 12]. Diabetes is a chronic disease that can significantly impact on quality of life and reduce life expectancy. However, diabetics can stay one step ahead of the disease by monitoring their blood glucose level to minimize the complication of the disease by proper administration of insulin. Currently, blood analysis is the gold standard method for measuring the level of glucose in patient's blood. However, this technique cannot be applied without penetrating the skin, which can be painful and inconvenient, and requires user obedience. Therefore, current research focuses on the development of portable and wearable devices capable of continuous glucose sensing through noninvasive detection techniques.
