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Cureus Sep 2023Background Atrial fibrillation (AFIB) is a common atrial arrhythmia that affects millions of people worldwide. However, most of the time, AFIB is paroxysmal and can pass...
Background Atrial fibrillation (AFIB) is a common atrial arrhythmia that affects millions of people worldwide. However, most of the time, AFIB is paroxysmal and can pass unnoticed in medical exams; therefore, regular screening is required. This paper proposes machine learning (ML) methods to detect AFIB from short-term electrocardiogram (ECG) and photoplethysmography (PPG) signals. Aim Several experiments were conducted across five different databases, with three of them containing ECG signals and the other two consisting of only PPG signals. Experiments were conducted to investigate the hypothesis that an ML model trained to predict AFIB from ECG segments could be used to predict AFIB from PPG segments. Materials and methods A random forest (RF) ML algorithm achieved the best accuracy and achieved a 90% accuracy rate on the University of Mississippi Medical Center (UMMC) dataset (216 samples) and a 97% accuracy rate on the Medical Information Mart for Intensive Care (MIMIC)-III datasets (2,134 samples). Results A total of 269,842 signal segments were analyzed across all datasets (212,266 were of normal sinus rhythm (NSR) and 57,576 corresponded to AFIB segments). Conclusions The ability to detect AFIB with significant accuracy using ML algorithms from PPG signals, which can be acquired via non-invasive contact or contactless, is a promising step forward toward the goal of achieving large-scale screening for AFIB.
PubMed: 37842400
DOI: 10.7759/cureus.45111 -
Polymers Sep 2023Dual-pulsed (DPL) laser deposition using oyster shells as targets was studied in order to find out if this method can replace the use of high-power pulsed lasers....
Dual-pulsed (DPL) laser deposition using oyster shells as targets was studied in order to find out if this method can replace the use of high-power pulsed lasers. Aspects related to changes in the morphological structure of the thin layer but also to the chemical composition of the obtained thin layer were analyzed and compared with the target as well as with the thin layers obtained with a higher power pulsed laser in a single-pulsed (SPL) regime. Orthorhombic structures were noticed with Scanning Electron Microscopy for the thin film obtained in DPL mode compared to the irregular particles obtained in SPL mode. The deacetylation process during ablation was evidenced by Fourier Transform Infrared spectroscopy, resulting in chitosan-based thin films. The effect of the obtained thin films of chitosan on the cells of baker's yeast () was studied. Restoration of the yeast paste into initial yeast was noticed mainly when the hemp fabric was used as support for the coating with yeas which was after that coated with chitosan thin film produced by DPL method.
PubMed: 37836002
DOI: 10.3390/polym15193953 -
Frontiers in Ecology and Evolution Jun 2023Since nanofibers have a high surface-to-volume ratio, van der Waals forces render them attracted to virtually any surface. The high ratio provides significant advantages...
Since nanofibers have a high surface-to-volume ratio, van der Waals forces render them attracted to virtually any surface. The high ratio provides significant advantages for applications in drug delivery, wound healing, tissue regeneration, and filtration. Cribellate spiders integrate thousands of nanofibers into their capture threads as an adhesive to immobilize their prey. These spiders have antiadhesive nanoripples on the calamistrum, a comb-like structure on their hindmost legs, and are thus an ideal model for investigating how nanofiber adhesion can be reduced. We found that these nanoripples had similar spacing in the cribellate species , and , independent of phylogenetic relation and size. Ripple spacing on other body parts (i.e., cuticle, claws, and spinnerets), however, was less homogeneous. To investigate whether a specific distance between the ripples determines antiadhesion, we fabricated nanorippled foils by nanosecond UV laser processing. We varied the spatial periods of the nanoripples in the range ~203-613 nm. Using two different pulse numbers resulted in ripples of different heights. The antiadhesion was measured for all surfaces, showing that the effect is robust against alterations across the whole range of spatial periods tested. Motivated by these results, we fabricated irregular surface nanoripples with spacing in the range ~130-480 nm, which showed the same antiadhesive behavior. The tested surfaces may be useful in tools for handling nanofibers such as spoolers for single nanofibers, conveyor belts for producing endless nanofiber nonwoven, and cylindrical tools for fabricating tubular nanofiber nonwoven. Engineered fibers such as carbon nanotubes represent a further candidate application area.
PubMed: 37786452
DOI: 10.3389/fevo.2023.1149051 -
Life (Basel, Switzerland) Aug 2023Atypical clinical and dermoscopic findings, or changes in pigmented melanocytic lesions located on body areas treated with lasers or intense pulsed light (IPL) for hair... (Review)
Review
Atypical clinical and dermoscopic findings, or changes in pigmented melanocytic lesions located on body areas treated with lasers or intense pulsed light (IPL) for hair removal (photoepilation), have been described in the literature. There are three prospective studies in a total of 79 individuals with 287 melanocytic nevi and several case reports reporting the dermoscopic findings and changes after photoepilation. Clinical changes have been reported in 20-100% of individuals, while dermoscopic changes have been observed in 48% to 93% of nevi. More frequent dermoscopic changes included bleaching, the development of pigmented globules, and irregular hyperpigmented areas and regression structures, including gray areas, gray dots/globules, and whitish structureless areas. The diagnostic approach for pigmented lesions with atypical dermoscopic findings and changes after photo-epilation included reflectance confocal microscopy, sequential digital dermoscopy follow-up, and/or excision and histopathology. Challenges pertaining to these diagnostic steps in the context of photoepilation include the detection of findings that may warrant a biopsy to exclude melanoma (ugly duckling, irregular hyperpigmented areas, blue-gray or white areas, and loss of pigment network), the potential persistence of changes at follow-up, and that a histopathologic diagnosis may not be possible due to the distortion of melanocytes or complete regression of the lesion. Furthermore, these diagnostic approaches can be time-consuming, require familiarization of the physician with dermoscopic features, may cause anxiety to the individual, and highlight that avoiding passes of the laser or IPL devices over pigmented lesions is key.
PubMed: 37763236
DOI: 10.3390/life13091832 -
Diagnostics (Basel, Switzerland) Sep 2023A 36-year-old professional marathon runner reported sudden irregular palpitations occurring during competitions, with heart rates (HR) up to 230 bpm recorded on a sports...
A 36-year-old professional marathon runner reported sudden irregular palpitations occurring during competitions, with heart rates (HR) up to 230 bpm recorded on a sports HR monitor (HRM) over 4 years. These episodes subsided upon the cessation of exercise. Electrocardiograms, echocardiography, and cardiac magnetic resonance imaging results were borderline for athlete's heart. Because an electrophysiology study and standard exercise tests provoked no arrhythmia, doctors suspected Munchausen syndrome. Ultimately, an exercise test that simulated the physical effort of a competition provoked tachyarrhythmia consistent with the HRM readings. This case demonstrates the diagnostic difficulties related to exercise-induced arrhythmia and the diagnostic usefulness of sports HRMs.
PubMed: 37761288
DOI: 10.3390/diagnostics13182917 -
Diagnostics (Basel, Switzerland) Sep 2023Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals' lives....
Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals' lives. Globally, arrhythmias are recognized as a significant health concern, accounting for nearly 12 percent of all deaths. As a result, there has been a growing focus on utilizing artificial intelligence for the detection and classification of abnormal heartbeats. In recent years, self-operated heartbeat detection research has gained popularity due to its cost-effectiveness and potential for expediting therapy for individuals at risk of arrhythmias. However, building an efficient automatic heartbeat monitoring approach for arrhythmia identification and classification comes with several significant challenges. These challenges include addressing issues related to data quality, determining the range for heart rate segmentation, managing data imbalance difficulties, handling intra- and inter-patient variations, distinguishing supraventricular irregular heartbeats from regular heartbeats, and ensuring model interpretability. In this study, we propose the Reseek-Arrhythmia model, which leverages deep learning techniques to automatically detect and classify heart arrhythmia diseases. The model combines different convolutional blocks and identity blocks, along with essential components such as convolution layers, batch normalization layers, and activation layers. To train and evaluate the model, we utilized the MIT-BIH and PTB datasets. Remarkably, the proposed model achieves outstanding performance with an accuracy of 99.35% and 93.50% and an acceptable loss of 0.688 and 0.2564, respectively.
PubMed: 37761234
DOI: 10.3390/diagnostics13182867 -
Translational Vision Science &... Sep 2023To evaluate the efficacy of topical losartan after blast injury-simulating irregular phototherapeutic keratectomy (PTK) in rabbits.
PURPOSE
To evaluate the efficacy of topical losartan after blast injury-simulating irregular phototherapeutic keratectomy (PTK) in rabbits.
METHODS
Twelve NZW rabbits underwent 100 pulse 6.5 mm diameter PTK over a metal screen to generate severe surface irregularity and inhibit epithelial basement membrane regeneration. Corneas were treated with 0.8 mg/mL losartan in balanced salt solution (BSS) or BSS 50 µL six times per day for six weeks after PTK. All corneas had slit lamp photography, with and without 1% fluorescein at two, four, and six weeks after PTK, and were analyzed using immunohistochemistry for the myofibroblast marker α-smooth muscle actin (α-SMA), keratocyte marker keratocan, mesenchymal cell marker vimentin, transforming growth factor (TGF)-β1, and collagen type IV.
RESULTS
Topical 0.8 mg/mL losartan six times a day significantly decreased anterior stromal α-SMA intensity units compared to BSS at six weeks after anterior stromal irregularity-inducing screened PTK (P = 0.009). Central corneal opacity, however, was not significantly different between the two groups. Keratocan, vimentin, TGF-β1, or collagen type IV levels in the anterior stroma were not significantly different between the two groups.
CONCLUSIONS
Topical losartan effectively decreased myofibroblast generation after surface blast simulation irregular PTK. However, these results suggest initial masking-smoothing PTK, along with adjuvant topical losartan therapy, may be needed to decrease corneal stromal opacity after traumatic injuries that produce severe surface irregularity.
TRANSLATIONAL RELEVANCE
Topical losartan decreased scar-producing stromal myofibroblasts after irregular PTK over a metal screen but early smoothing of irregularity would also likely be needed to significantly decrease corneal opacity.
Topics: Rabbits; Animals; Losartan; Myofibroblasts; Vimentin; Collagen Type IV; Corneal Opacity
PubMed: 37750746
DOI: 10.1167/tvst.12.9.20 -
Sensors (Basel, Switzerland) Aug 2023At present, a medium-level microcontroller is capable of performing edge computing and can handle the computation of neural network kernel functions. This makes it...
At present, a medium-level microcontroller is capable of performing edge computing and can handle the computation of neural network kernel functions. This makes it possible to implement a complete end-to-end solution incorporating signal acquisition, digital signal processing, and machine learning for the classification of cardiac arrhythmias on a small wearable device. In this work, we describe the design and implementation of several classifiers for atrial fibrillation detection on a general-purpose ARM Cortex-M4 microcontroller. We used the CMSIS-DSP library, which supports Naïve Bayes and Support Vector Machine classifiers, with different kernel functions. We also developed Python scripts to automatically transfer the Python model (trained in Scikit-learn) to the C environment. To train and evaluate the models, we used part of the data from the PhysioNet/Computing in Cardiology Challenge 2020 and performed simple classification of atrial fibrillation based on heart-rate irregularity. The performance of the classifiers was tested on a general-purpose ARM Cortex-M4 microcontroller (STM32WB55RG). Our study reveals that among the tested classifiers, the SVM classifier with RBF kernel function achieves the highest accuracy of 96.9%, sensitivity of 98.4%, and specificity of 95.8%. The execution time of this classifier was 720 μs per recording. We also discuss the advantages of moving computing tasks to edge devices, including increased power efficiency of the system, improved patient data privacy and security, and reduced overall system operation costs. In addition, we highlight a problem with false-positive detection and unclear significance of device-detected atrial fibrillation.
Topics: Humans; Atrial Fibrillation; Bayes Theorem; Algorithms; Heart Rate; Neural Networks, Computer
PubMed: 37687975
DOI: 10.3390/s23177521 -
Materials (Basel, Switzerland) Aug 2023Commonly used tool materials for machining wood-based materials are WC-Co carbides. Although they have been known for a long time, there is still much development in the...
Commonly used tool materials for machining wood-based materials are WC-Co carbides. Although they have been known for a long time, there is still much development in the field of sintered tool materials, especially WC-Co carbides and superhard materials. The use of new manufacturing methods (such as FAST-field-assisted sintering technology), which use pulses of electric current for heating, can improve the properties of the materials used for cutting tools, thereby increasing the cost-effectiveness of machining. The ability to increase tool life without the downtime associated with tool wear allows significant cost savings, particularly in mass production. This paper presents the results of a study of the effect of grain size and cobalt content of carbide tool sinters on the tribological properties of the materials studied. The powders used for consolidation were characterised by irregular shape and formed agglomerates of different sizes. Tribological tests were carried out using the T-01 (ball-on-disc) method. In order to determine the wear kinetics, the entire friction path was divided into 15 cycles of 200 m and the weight loss was measured after each stage. In order to determine the mechanism and intensity of wear of the tested materials under technically dry friction conditions, the surface of the tested sinters was observed before the test and after 5, 10, and 15 cycles. The conclusions of the study indicate that the predominant effect of surface cooperation at the friction node is abrasion due to the material chipping that occurs during the process. The results confirm the influence of sintered grain size and cobalt content on durability. In the context of the application of the materials in question for cutting tools, it can be pointed out that sintered WC(0.4)_4 has the highest potential for use in the manufacture of cutting tools.
PubMed: 37687529
DOI: 10.3390/ma16175836