Development and Validation of a Real-Time Service Model for Noise Removal and Arrhythmia Classification Using Electrocardiogram Signals.

Arrhythmias range from mild nuisances to potentially fatal conditions, detectable through electrocardiograms (ECGs). With advancements in wearable technology, ECGs can now be monitored on-the-go, although these devices often capture noisy data, complicating accurate arrhythmia detection. This study aims to create a new deep learning model that utilizes generative adversarial networks (GANs) for effective noise removal and ResNet for precise arrhythmia classification from wearable ECG data. We developed a deep learning model that cleans ECG measurements from wearable devices and detects arrhythmias using refined data. We pretrained our model using the MIT-BIH Arrhythmia and Noise databases. Least squares GANs were used for noise reduction, maintaining the integrity of the original ECG signal, while a residual network classified the type of arrhythmia. After initial training, we applied transfer learning with actual ECG data. Our noise removal model significantly enhanced data clarity, achieving over 30 dB in a signal-to-noise ratio. The arrhythmia detection model was highly accurate, with an F1-score of 99.10% for noise-free data. The developed model is capable of real-time, accurate arrhythmia detection using wearable ECG devices, allowing for immediate patient notification and facilitating timely medical response.

Applications of deep learning methods in digital biomarker research using noninvasive sensing data.

Introduction: Noninvasive digital biomarkers are critical elements in digital healthcare in terms of not only the ease of measurement but also their use of raw data. In recent years, deep learning methods have been put to use to analyze these diverse heterogeneous data; these methods include representation learning for feature extraction and supervised learning for the prediction of these biomarkers. Methods: We introduce clinical cases of digital biomarkers and various deep-learning methods applied according to each data type. In addition, deep learning methods for the integrated analysis of multidimensional heterogeneous data are introduced, and the utility of these data as an integrated digital biomarker is presented. The current status of digital biomarker research is examined by surveying research cases applied to various types of data as well as modeling methods. Results: We present a future research direction for using data from heterogeneous sources together by introducing deep learning methods for dimensionality reduction and mode integration from multimodal digital biomarker studies covering related domains. The integration of multimodality has led to advances in research through the improvement of performance and complementarity between modes. Discussion: The integrative digital biomarker will be more useful for research on diseases that require data from multiple sources to be treated together. Since delicate signals from patients are not missed and the interaction effects between signals are also considered, it will be helpful for immediate detection and more accurate prediction of symptoms.

Metal-enhanced fluorescence in polymer composite films with Au@Ag@SiO2 nanoparticles and InP@ZnS quantum dots.

For white light-emitting diode (LED) applications, semiconductor quantum dots (QDs) have been widely utilized as efficient down-converters to change the blue color of the light source into different emission colors. Because QDs offer spectral tunability over the entire visible light range, as well as improved color purity, they have rapidly replaced conventional phosphor-based white LEDs. However, for the sustainable growth of QD-mediated LEDs, the amount of QDs required must be reduced by enhancing the color-conversion efficiency. For this purpose, we prepared poly(lauryl methacrylate) (PLMA) composite films by the photo-crosslinking polymerization of lauryl methacrylate monomers in the presence of Au@Ag@SiO2 nanoparticles (NPs) and InP@ZnS QDs. In the PLMA composites, the Au@Ag NPs not only amplified the blue light source but also modified the relaxation of the excited QDs via localized surface plasmon resonance. This resulted in a maximum 12.9-fold enhancement in the QD fluorescence. Because the blue light source in this study can be easily replaced by blue LEDs, the enhanced efficiency of QD emissions via the plasmonic effect could potentially increase the performance of QDs for display applications.

Short-range ordered photonic structures of lamellae-forming diblock copolymers for excitation-regulated fluorescence enhancement.

Photonic crystals can be represented by periodic nanostructures with alternating refractive indices, which create artificial stop bands with the appearance of colors. In this regard, nanodomains of block copolymers and the corresponding structural colors have been intensively studied in the past. However, the practical application of photonic crystals of block copolymers has been limited to a large degree because of the presence of large defects and grain boundaries in the nanodomains of block copolymers. The present study focuses on the alternative opportunity of short-range ordered nanodomains of block copolymers for fluorescence enhancement, which also has a direct relevance to the development of fluorescence sensors or detectors. The enhancement mechanism was found to be interconnected with the excitation process rather than the alternation of the decay kinetics. In particular, we demonstrate that randomly oriented, but regular grains of lamellae of polystyrene-block-polyisoprene, PS-b-PI, diblock copolymers and their blend with PS homopolymers can behave as Bragg mirrors to induce multiple reflections of the excitation source inside the photonic structures. This process in turn significantly increases the effective absorption of the given fluorophores inside the polymeric photonic structures to amplify the fluorescence signal.

Switching off FRET in the hybrid assemblies of diblock copolymer micelles, quantum dots, and dyes by plasmonic nanoparticles.

Recently, it has been noticed that surface plasmon resonance of metal nanoparticles can alter the intrinsic properties of nearby fluorophores. Field enhancement and radiative decay engineering are major principles for understanding a number of experimental observations such as enhanced and quenched emission of fluorophores in the vicinity of metal nanoparticles. At the same time, there are apparent similarities between surface-plasmon-coupled fluorescence and fluorescence resonance energy transfer (FRET), as both are near-field through-space interactions. From this perspective, we hypothesize that donor-acceptor interaction in the FRET can be altered by metal nanoparticles. Our approach is based on diblock copolymer micelles, which have been widely applied for nanoscale arrangement of functionalities. By applying self-assembling techniques of copolymer micelles to organize the spatial location of semiconductor quantum dots, fluorescent dyes, and metal nanoparticles, the FRET in hybrid assemblies can be switched off by plasmonic effects.

Controlled fluorescence resonance energy transfer between ZnO nanoparticles and fluorophores in layer-by-layer assemblies.

We controlled the fluorescence resonance energy transfer (FRET) between ZnO nanoparticles and rhodamine B (RB) within multilayered thin films prepared by the layer-by-layer (LbL) assembling method. Positively charged ZnO nanoparticles and RB-labeled poly(allyamine hydrochloride) (RB-PAH) were accurately incorporated into LbL assemblies of polyelectrolytes. The distance between ZnO nanoparticles and RB-PAH was adjusted by varying the number of layers of pure polyelectrolytes, leading to the controlled FRET from ZnO nanoparticles to RB-PAH.

Controlled light emission in spin-assisted layer-by-layer assemblies with fluorophores.

We report controlled light emissions from spin-assisted layer-by-layer (LbL) thin films containing a donor-acceptor pair of fluorescent dyes. Based on their spectral overlap, we selected rhodamine 123 (R123) and rhodamine B (RB) as the donor and acceptor, respectively. For the construction of multilayered thin films, a complex of each dye and poly(sodium 4-sulfonate) (PSS-R123 and PSS-RB) was prepared and then alternately spin coated with poly(allyamine hydrochloride) (PAH). LbL assemblies were fabricated with a sequence of [PAH/PSS-RB]/([PAH/PSS])n/[PAH/PSS-R123]. Since the distance between R123 and RB was precisely adjusted by the number of bilayers (n) of [PAH/PSS] between them, we were able to tune the light emission from the thin film by controlling the efficiency of the energy transfer.

Hetero-telechelic dye-labeled polymer for nanoparticle decoration.

The synthesis of poly(methyl methacrylate) (PMMA) exhibiting one fluorescent dye (Texas Red) and one methyl disulfide end group is described. It is shown that the latter end group enabled the exchange of both oleic amine on gold nanoparticles (AuNP) and of oleic acid on CdSe/ZnS quantum dots (QD), allowing for a phase transfer of both types of nanoparticles (NP) from hexane into dimethylformamide due to the solubility provided by the PMMA chains. For AuNP, a fluorescence quenching of the dye was found due to fluorescence resonance energy transfer (FRET) from the dye to the AuNP, while QDs caused a fluorescence enhancement by FRET from the QD to the attached dyes. Due to the hetero-telechelic geometry of the polymer, the separation between NP and dye is governed by the end-to-end distance of the polymer.