Haein Shin

Wearable electronic devices that can monitor physiological signals of the human body to provide biomedical information have been drawing extensive interests for sustainable personal health management. Here, we report a human pilot trial of a soft, smart contact lens and a skin-attachable therapeutic device for wireless monitoring and therapy of chronic ocular surface inflammation (OSI). As a diagnostic device, this smart contact lens enables real-time measurement of the concentration of matrix metalloproteinase-9, a biomarker for OSI, in tears using a graphene field-effect transistor. As a therapeutic device, we also fabricated a stretchable and transparent heat patch attachable on the human eyelid conformably. Both diagnostic and therapeutic devices can be incorporated using a smartphone for their wireless communications, thereby achieving instantaneous diagnosis of OSI and automated hyperthermia treatments. Furthermore, in vivo tests using live animals and human subjects confirm their good biocompatibility and reliability as a noninvasive, mobile health care solution.

Herein, a wireless and soft smart contact lens that enables real-time quantitative recording of cholesterol in tear fluids for the monitoring of patients with hyperlipidemia using a smartphone is reported. This contact lens incorporates an electrochemical biosensor for the continuous detection of cholesterol concentrations, stretchable antenna, and integrated circuits for wireless communication, which makes a smartphone the only device required to operate this lens remotely without obstructing the wearer's vision. The hyperlipidemia rabbit model is utilized to confirm the correlation between cholesterol levels in tear fluid and blood and to confirm the feasibility of this smart contact lens for diagnostic application of cholesterol-related diseases. Further in vivo tests with human subjects demonstrated its good biocompatibility, wearability, and reliability as a non-invasive healthcare device.

The eye is a complex sensory organ that contains abundant information for specific diseases and pathological responses. It has emerged as a facile biological interface for wearable healthcare platforms because of its excellent accessibility. Recent advances in electronic devices have led to the extensive research of point-of-care (POC) systems for diagnosing and monitoring diseases by detecting the biomarkers within the eye. Among these systems, contact lenses, which make direct contact with the ocular surfaces, have been utilized as one of the promising candidates for non-invasive POC testing of various diseases. The continuous and long-term measurement from the sensor allows the patients to manage their symptoms in an effective and convenient way. Herein, we review the progress of contact lens sensors in terms of the materials, methodologies, device designs, and target biomarkers. The anatomical structure and biological mechanisms of the eye are also discussed to provide a comprehensive understanding of the principles of contact lens sensors. Intraocular pressure and glucose, which are the representative biomarkers found in the eyes, can be measured with the biosensors integrated with contact lenses for the diagnosis of glaucoma and diabetes. Furthermore, contact lens sensors for various general pathologies as well as other ocular diseases are also considered, thereby providing the prospects for further developments of smart contact lenses as a future POC system.

Copper indium diselenide (CuInSe2) is a prototype ternary compound and group I–III–VI semiconductor with useful optoelectronic properties. CuInSe2 nanocrystals have been of significant interest because of their size-tunable optical properties and lack of toxic heavy metals. Because of the particular vacancy and antisite substitutional point defects in CuInSe2, large stoichiometric deviations can be tolerated, sometimes leading to the so-called ordered vacancy compounds (OVCs). Here, we use Raman spectroscopy of oleylamine-capped CuInSe2 nanocrystals and ab initio lattice dynamics modeling to study the concentration and arrangements of (2vCu– + InCu2+) defect pairs in the nanocrystals. The nanocrystals have randomly distributed defect pairs that become mobile under light excitation and accumulate, as in OVCs, along the [100] direction. Because the high concentration of vacancies in CuInSe2 nanocrystals is compensated by InCu2+ antisite defects, these nanocrystals do not exhibit an optical plasmon resonance like many other copper chalcogenide nanocrystals. Annealing the nanocrystals at a high temperature (600 °C) was found to significantly reduce the defect concentration.

This article examined the spectral interference by heavy metal on the spectral signal of moisture content of heavy metal contaminated soils. Soil samples were collected from an abandoned mine area, and the chemical analysis revealed extremely high contamination amount of copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), and lead (Pb). The mineralogical analysis showed that the spectral signature of the heavy metal contaminated soils was manifested by secondary minerals. Water content suppressed the spectral reflectance of the soil samples but increased the absorption depths. Although a regression model can predict moisture content using the magnitude of the water absorption feature, the accuracy was much lower when the heavy metal concentration was extremely high. It indicates that geochemical reactions between the heavy metal cation and iron oxide/clay minerals may have affected the spectral responses of the contaminated soils at the water absorption bands. Our model also showed that there was a shift of the absorption features of moisture content if the heavy metal contamination level went up. Unlike normal soils, the absorption features of clay minerals and ferric iron were not able to accurately predict moisture in highly contaminated soils. Given the fact that the spectral bands selected in this article were associated with water absorption, the findings from this article may only be useful to a drone-based low-altitude remote sensing of soil moisture content.