Purpose: We aimed to design, develop, and evaluate an internet of things-enabled patch (IoT patch) for real-time remote monitoring of adherence (or patch wear time) during patch treatment in child participants in clinical trials. This study provides healthcare providers with a tool for objective, real-time, and remote assessment of adherence and for making required adjustments to treatment plans.
Methods: The IoT patch had two temperature microsensors and a wireless chip. One sensor was placed closer to the skin than the other, resulting in a temperature difference depending on whether the patch was worn. When the patch was worn, it measured temperatures every 30 seconds and transmitted temperature data to a cloud server via a mobile application every 15 seconds. The patch was evaluated via 2 experiments with 30 healthy adults and 40 children with amblyopia.
Results: Excellent monitoring accuracy was observed in both adults (mean delay of recorded time data, 0.4 minutes) and children (mean, 0.5 minutes). The difference between manually recorded and objectively recorded patch wear times showed good agreement in both groups. Experiment 1 showed accurate monitoring over a wide range of temperatures (from 0 to 30°C). Experiment 2 showed no significant differences in wearability (ease-of-use and comfort scores) between the IoT and conventional patches.
Conclusions: The IoT patch offers an accurate, real-time, and remote system to monitor adherence to patch treatment. The patch is comfortable and easy to use. The utilization of an IoT patch may increase adherence to patch treatment based on accurate monitoring.
Translational Relevance: Results show that the IoT patch can enable real-time adherence monitoring in clinical trials, improving treatment precision, and patient compliance to enhance outcomes.
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http://dx.doi.org/10.1167/tvst.13.5.18 | DOI Listing |
Front Plant Sci
November 2024
Department of Mechanical Engineering, Iowa State University, Ames, IA, United States.
Introduction: Effective monitoring of insect-pests is vital for safeguarding agricultural yields and ensuring food security. Recent advances in computer vision and machine learning have opened up significant possibilities of automated persistent monitoring of insect-pests through reliable detection and counting of insects in setups such as yellow sticky traps. However, this task is fraught with complexities, encompassing challenges such as, laborious dataset annotation, recognizing small insect-pests in low-resolution or distant images, and the intricate variations across insect-pests life stages and species classes.
View Article and Find Full Text PDFHeliyon
October 2024
Department of Information and Communication Engineering, Chungbuk National University, Cheongju, 28644, South Korea.
Vehicular Internet of Things (IoT) is facilitated by efficient RF front ends with suppressed mutual coupling for enhanced spatial diversity and increased channel capacity. This paper presents a mutual coupling suppressed MIMO antenna with a hybrid decoupling technique for Vehicle-to-Everything (V2X) communications, enabling IoT in automotive systems. The single elements consist of a radiating patch with a cleaving circular slot to introduce a capacitive effect on the radiating structure.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Interdisciplinary Courses in Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Two two-element slotted patch multiple-input multiple-output (MIMO) antenna with coplanar waveguide (CPW) feed is proposed for deployment in implantable medical devices. Implantable devices are compact and demand high-gain antennae with unidirectional radiation patterns. Regarding compactness, the antenna has a size of 16 × 6×0.
View Article and Find Full Text PDFThis study introduces StressFit, a novel hybrid wearable sensor system designed to simultaneously monitor electromyogram (EMG) signals and sweat cortisol levels. Our approach involves the development of a noninvasive skin patch capable of monitoring skin temperature, sweat pH, cortisol levels, and corresponding EMG signals using a combination of physical and electrochemical sensors integrated with EMG electrodes. StressFit was optimized by enhancing sensor output and mechanical resilience for practical application on curved body surfaces, ensuring accurate acquisition of cortisol, pH, body temperature, and EMG data without sensor interference.
View Article and Find Full Text PDFACS Nano
October 2024
Nanosensor Bioplatforms Laboratory, Chemistry and Chemical Engineering Research Center of Iran, Tehran 14335-186, Iran.
Despite substantial progress in the diagnosis of jaundice/hyperbilirubinemia as the most common disease and cause of hospitalization of newborns, on the eve of Industry/Healthcare 5.0, the development of accurate and reliable wearable diagnostic sensors for noninvasive smart monitoring of bilirubin (BIL) is still in high demand. Aiming to fabricate a smart wearable sensor for early diagnosis of neonatal jaundice and its therapeutic monitoring, we here report a fluorescent dermal nanotattoo that further coupled with an IoT-integrated wearable optoelectronic reader for minimally invasive, continuous, and real-time monitoring of BIL in interstitial fluid.
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