A Novel Approach to Obtain PAR with a Multi-Channel Spectral Microsensor, Suitable for Sensor Node Integration

Spicy Recipe for At-Home Diagnostics: Smart Salivary Sensors for Point-of-Care Diagnosis of Jaundice

Even though significant advances have been made, there is still a lack of reliable sensors capable of noninvasively monitoring bilirubin and diagnosing jaundice as the most common neonatal disease, particularly at the point-of-care (POC) where blood sampling from infants is accompanied by serious challenges and concerns. Herein, for the first time, using an easy-to-fabricate/use assay, we demonstrate the capability of curcumin embedded within paper for noninvasive optical monitoring of bilirubin in saliva. The highly selective sensing of the developed sensor toward bilirubin is attributed to bilirubin photoisomerization under blue light exposure, which can selectively restore the bilirubin-induced quenched fluorescence of curcumin. We also fabricated an IoT-enabled hand-held optoelectronic reader to measure and quantify the fluorescence and color signals of our sensor. Clinical analysis on the saliva of 18 jaundiced infants by using our developed smart salivary sensor proved that it is amenable to be widely exploited in POC applications for bilirubin monitoring as there are good correlations between its results with those of reference methods in saliva and blood. Meeting all WHO's REASSURED criteria by our developed sensor makes it a highly promising sensor for smart noninvasive diagnosis and therapeutic monitoring of jaundice, hepatitis, and other bilirubin-induced neurologic diseases at the POC.

Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks

The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate multi-channel spectral sensor AS7341. Additionally, we present a method for processing and filtering the gathered data, which enables very high accuracy measurements with an nRMSE of only 0.098, compared to the manually-operated state-of-the-art instrument LAI-2200C (LiCor). The sensor that is embedded on a sensor node has been tested in long-term experiments, proving its suitability for continuous deployment over an entire season. It permits the estimation of both the plant area index (PAI) and leaf area index (LAI) and provides the first wireless system that obtains the LAI solely powered by solar cells. Its energy autonomy and wireless connectivity make it suitable for a massive deployment over large areas and at different levels of the tree crown. It may be upgraded to allow the parallel measurement of photosynthetic active radiation (PAR) and light quality, relevant parameters for monitoring processes within tree canopies.