Non-Invasive Sensors Integration for NCDs with AIoT Based Telemedicine System.

Thailand's hospitals face overcrowding, particularly with non-communicable disease (NCD) patients, due to a doctor shortage and an aging population. Most literature showed implementation merely on web or mobile application to teleconsult with physicians. Instead, in this work, we developed and implemented a telemedicine health kiosk system embedded with non-invasive biosensors and time-series predictors to improve NCD indicators over an eight-month period.

Empowering an Acute Kidney Injury 3D Graphene-Based Sensor Using Extreme Learning Machine.

This study reports on the application of an extreme learning machine (ELM) in near-real-time kidney monitoring via urine neutrophil gelatinase-associated lipocalin (NGAL) detection with a 3D graphene electrode. This integration marks the first instance of combining a graphene-based electrode with machine learning to enhance the NGAL detection accuracy, building on our group's 2020 research. The methodology involves two key components: a graphene electrode functionalized with a lipocalin-2 antibody for NGAL detection and the ELM application for improved prediction accuracy by using urine analysis data.

Enhancing modulation performance by design of hybrid plasmonic optical modulator integrating multi-layer graphene and TiOon silicon waveguides.

A novel way to enhance modulation performance is through the design of a hybrid plasmonic optical modulator that integrates multi-layer graphene and TiOon silicon waveguides. In this article, a design is presented of a proposed modulator based on the use of the two-dimensional finite difference eigenmode solver, the three-dimensional eigenmode expansion solver, and the CHARGE solver. Leveraging inherent graphene properties and utilizing the subwavelength confinement capabilities of hybrid plasmonic waveguides (HPWs), we achieved a modulator design that is both compact and highly efficient.

Anomalous Current Steps in 3D Graphene Electrochemical Systems at Room Temperature.

In this work, we report a new phenomenon in electrochemical systems whereby uniform current steps of 1 mA per 0.5 × 0.5 × 0.

Electrical performance enhancement of a triboelectric nanogenerator based on epoxy resin/BaTiOby Al nanopowder addition for low power electronic devices.

Triboelectric nanogenerators (TENGs) are crucial for applications such as smart sensors and bio-electronics. In the current work, we aimed for improved performance of TENGs with incorporation of BaTiOpowder, which is known for its strong ferroelectric properties, combining it with epoxy resin to improve the flexibility of our devices. We observed that our TENGs can operate for over 24 000 cycles with no degradation of function.

Nanoflowers on Microporous Graphene Electrodes as a Highly Sensitive and Low-Cost As(III) Electrochemical Sensor for Water Quality Monitoring.

In this work, we report a low-cost and highly sensitive electrochemical sensor for detecting As(III) in water. The sensor uses a 3D microporous graphene electrode with nanoflowers, which enriches the reactive surface area and thus enhances its sensitivity. The detection range achieved was 1-50 ppb, meeting the US-EPA cutoff criteria of 10 ppb.

Optimization of the Chronic Kidney Disease-Peritoneal Dialysis App to Improve Care for Patients on Peritoneal Dialysis in Northeast Thailand: User-Centered Design Study.

Background: The prevalence of peritoneal dialysis (PD) in Thailand is increasing rapidly in part because of Thailand's Peritoneal Dialysis First policy. PD is a home-based renal replacement therapy in which patients with chronic kidney disease perform up to 4 exchanges of dialysate fluid per day in the peritoneal cavity. Overhydration is one of the most common complications in patients on PD and is associated with increased morbidity and mortality.

Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features.

Non-invasive and accurate method for continuous blood glucose monitoring, the self-testing of blood glucose is in quest for better diagnosis, control and the management of diabetes mellitus (DM). Therefore, this study reports a multiple photonic band near-infrared (mbNIR) sensor augmented with personalized medical features (PMF) in Shallow Dense Neural Networks (SDNN) for the precise, inexpensive and pain free blood glucose determination. Datasets collected from 401 blood samples were randomized and trained with ten-fold validation.

Highly-Sensitive Surface-Enhanced Raman Spectroscopy (SERS)-based Chemical Sensor using 3D Graphene Foam Decorated with Silver Nanoparticles as SERS substrate.

In this work, a novel platform for surface-enhanced Raman spectroscopy (SERS)-based chemical sensors utilizing three-dimensional microporous graphene foam (GF) decorated with silver nanoparticles (AgNPs) is developed and applied for methylene blue (MB) detection. The results demonstrate that silver nanoparticles significantly enhance cascaded amplification of SERS effect on multilayer graphene foam (GF). The enhancement factor of AgNPs/GF sensor is found to be four orders of magnitude larger than that of AgNPs/Si substrate.