Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics

Abstract

Wearable contact lenses which can monitor physiological parameters have attracted substantial interests due to the capability of direct detection of biomarkers contained in body fluids. However, previously reported contact lens sensors can only monitor a single analyte at a time. Furthermore, such ocular contact lenses generally obstruct the field of vision of the subject. Here, we developed a multifunctional contact lens sensor that alleviates some of these limitations since it was developed on an actual ocular contact lens. It was also designed to monitor glucose within tears, as well as intraocular pressure using the resistance and capacitance of the electronic device. Furthermore, in-vivo and in-vitro tests using a live rabbit and bovine eyeball demonstrated its reliable operation. Our developed contact lens sensor can measure the glucose level in tear fluid and intraocular pressure simultaneously but yet independently based on different electrical responses.

Figure 1. Schematic illustration and properties of the wearable contact lens sensor.

(a) Schematic of the wearable contact lens sensor, integrating the glucose sensor and intraocular pressure sensor. (b) A photograph of the contact lens sensor. Scale bar, 1 cm. (Inset: close-up image of the antenna on the contact lens. Scale bar, 1 cm.) (c) Optical transmittance and haze spectra of the bare graphene, AgNWs film and their hybrid structures. (d) Relative changes in resistance as a function of outer radius of cylindrical supports (e) Relative changes in resistance as a function of tensile strain. (f) Relative change in resistance of the graphene FET for 10,000 cycles of stretching and relaxation. Each data point indicates the mean value for 20 samples, and error bars represent the s.d.

Figure 2. Real-time glucose sensing with graphene-AgNW hybrid nanostructures.

(a) Schematic illustration and principle of glucose detection with the GOD-pyrene functionalized graphene. (b) Transfer (I_D–V_G) characteristics of the sensor at varied concentrations of glucose (V_D=0.1 V). (c) Real-time continuous monitoring of glucose concentrations (V_G=0 V). (d) The calibration curve generated by averaging current values and the glucose concentration from 1 μM to 10 mM. Each data point indicates the mean value for 10 samples, and error bars represent the s.d.

Figure 3. Contact lens sensor for wireless detection of glucose.

(a) Schematic illustration of the transparent glucose sensor on contact lens. (b) Schematic of reading circuit for wireless sensing on contact lens. (c) Wireless monitoring of glucose concentrations from 1 μM to 10 mM. (d) Photographs of wireless sensor integrated onto the eyes of a live rabbit. Black and white scale bars, 1 cm and 5 cm, respectively. (e) Wireless sensing curves of glucose concentration before and after wearing contact lens on an eye of live rabbit.

Figure 4. Contact lens sensor for wireless monitoring of intraocular pressure.

(a) Schematic showing the mechanism of intraocular pressure sensing. (b) Schematic of the experimental set-up for wireless intraocular pressure sensing. (c) Photographs of the sensor transferred onto the contact lens worn by a bovine eyeball (left) and a mannequin eye (right). Scale bar, 1 cm. (d) Wireless recording of the reflection coefficients at different pressures. (e) Frequency response of the intraocular pressure sensor on the bovine eye from 5 mm Hg to 50 mmHg. (Inset: the corresponding reflection coefficients of the sensor) (f) Frequency response of the sensor during a pressure cycle.