Optimal Lead Position in Patch-Type Monitoring Sensors for Reconstructing 12-Lead ECG Signals with Universal Transformation Coefficient.

The aim of this study was to reconstruct a 12-lead electrocardiograph (ECG) with a universal transformation coefficient and find the appropriate electrode position and shape for designing a patch-type ECG sensor. A 35-channel ECG monitoring system was developed, and 14 subjects were recruited for the experiment. A feedforward neural network with one hidden layer was applied to train the transformation coefficient. Three electrode shapes (5 cm × 5 cm square, 10 cm × 10 cm square, and right-angled triangle) were considered for the patch-type ECG sensor. The mean correlation coefficient (CC) and minimum CC methods were applied to evaluate the reconstruction performance. The average CCs between the standard 12-lead ECG and reconstructed 12-lead ECG were 0.860, 0.893, and 0.893 for a 5 cm × 5 cm square, 10 cm × 10 cm square, and right-angled triangle shape. The right-angled triangle showed the highest performance among the considered shapes. The results also suggested that the bottom of the central area of the chest was the most suitable position for attaching the patch-type ECG sensor.

Beat-to-Beat Continuous Blood Pressure Estimation Using Bidirectional Long Short-Term Memory Network.

Continuous blood pressure (BP) monitoring is important for patients with hypertension. However, BP measurement with a cuff may be cumbersome for the patient. To overcome this limitation, various studies have suggested cuffless BP estimation models using deep learning algorithms. A generalized model should be considered to decrease the training time, and the model reproducibility should be taken into account in multi-day scenarios. In this study, a BP estimation model with a bidirectional long short-term memory network is proposed. The features are extracted from the electrocardiogram, photoplethysmogram, and ballistocardiogram. The leave-one-subject-out (LOSO) method is incorporated to generalize the model and fine-tuning is applied. The model was evaluated using one-day and multi-day tests. The proposed model achieved a mean absolute error (MAE) of 2.56 and 2.05 mmHg for the systolic and diastolic BP (SBP and DBP), respectively, in the one-day test. Moreover, the results demonstrated that the LOSO method with fine-tuning was more compatible in the multi-day test. The MAE values of the model were 5.82 and 5.24 mmHg for the SBP and DBP, respectively.

Detection of Copper(II) Ions Using Glycine on Hydrazine-Adsorbed Gold Nanoparticles via Raman Spectroscopy.

A facile, selective, and sensitive detection method for the Cu2+ ions in environmental and biological solutions has been newly developed by observing the unique CN stretching peaks at ~2108 cm-1 upon the dissociative adsorption of glycine (GLY) in hydrazine buffer on gold nanoparticles (AuNPs). The relative abundance of Cu species on AuNPs was identified from X-ray photoelectron spectroscopy analysis. UV-Vis spectra also indicated that the Au particles aggregated to result in the color change owing to the destabilization induced by the GLY-Cu2+ complex. The CN stretching band at ~2108 cm-1 could be observed to indicate the formation of the CN species from GLY on the hydrazine-covered AuNP surfaces. The other ions of Fe3+, Fe2+, Hg2+, Mg2+, Mn2+, Ni2+, Zn2+, Cr3+, Co2+, Cd2+, Pb2+, Ca2+, NH4⁺, Na⁺, and K⁺ at high concentrations of 50 µM did not produce such spectral changes. The detection limit based on the CN band for the determination of the Cu2+ ion could be estimated to be as low as 500 nM in distilled water and 1 µM in river water, respectively. We attempted to apply our method to estimate intracellular ion detection in cancer cells for more practical purposes.

The Design and Analysing Heating Effect of Spiral Planar Coil in COMSOL Multiphysics for Implantable Artificial Retina.

In this paper, simulation data and heat generation due to electromagnetic from spiral planar pair of coils for arti-ficial retinal implant were analyzed by COMSOL Multiphysics. Planar spiral outer and inner coils for an implantable artificial retina were designed and analyzed. The whole geometry was designed in a transplant situation. The parameters of the coil were set within the design limits due to the limitations of im-plant space. The inductance for the coil and the thermal change due to the electromagnetic force generated in the inductively coupled coil were calculated. Analysis of heat transfer in a biological model showed that the maximum heat did not exceed the internal tissue damage temperature. The results showed that a pair of coils designed for artificial retinas can be implanted in vivo without destruction of body tissues.

Manually wound coil fabrication process based on cyclic olefin copolymer substrate.

Neural prostheses are systems that interact with the human nervous system to recover function lost as a result of disease by recording or stimulating neural signals. Neural implants have a variety of components, but among them, designing highly efficient wireless power transmission systems is particularly important. However, there is a problem that it is difficult to design a wireless power transmission system with high transmission efficiency because power transmission efficiency is affected by various coil parameters. In addition, nerve implants are mainly designed based on polymer substrates, but studies have not been conducted on the process of manufacturing coils based on polymer substrates. In this study, to overcome the mentioned problems, an easy and fast manufacturing process was proposed before designing a precise coil on a polymer substrate. Coil was made by manually winding the 200um copper wire, and the coil was packaged using COC. The coil feasibility test was conducted after fabrication to evaluate the performance of fabrication process. It did not fit the expected frequency because the wire was manually wound to make a small size coil. However, the wire wound coil is expected to be more efficient than the coil made through the PCB process, and if the sophistication is supplemented, it can be used as a highly efficient coil for wireless power transmission.

Wireless-Powered Chemical Sensor by 2.4 GHz Wi-Fi Energy-Harvesting Metamaterial.

Metamaterial Sensors show significant potential for applications ranging from hazardous chemical detection to biochemical analysis with high-quality sensing properties. However, they require additional measurement systems to analyze the resonance spectrum in real time, making it difficult to use them as a compact and portable sensor system. Herein, we present a novel wireless-powered chemical sensing system by using energy-harvesting metamaterials at microwave frequencies. In contrast to previous studies, the proposed metamaterial sensor utilizes its harvested energy as an intuitive sensing indicator without complicated measurement systems. As the spectral energy-harvesting rate of the proposed metamaterial sensor can be varied by changing the chemical components and their mixtures, we can directly distinguish the chemical species by analyzing the resulting output power levels. Moreover, by using a 2.4 GHz Wi-Fi source, we experimentally realize a prototype chemical sensor system that wirelessly harvests the energy varying from 0 mW up to 7 mW depending on the chemical concentration of the water-based binary mixtures.