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1.
BMC Public Health ; 21(1): 1637, 2021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34493244

RESUMO

BACKGROUND: Before the COVID-19 pandemic, Sexually transmitted infections (STIs) were increasing in Europe, and Spain and Catalonia were not an exception. Catalonia has been one of the regions with the highest number of COVID-19 confirmed cases in Spain. The objective of this study was to estimate the magnitude of the decline, due to the COVID-19 pandemic, in the number of STI confirmed cases in Catalonia during the lockdown and de-escalation phases. METHODS: Interrupted time series analysis was performed to estimate the magnitude of decline in the number of STI reported confirmed cases - chlamydia, gonorrhoea, syphilis, and lymphogranuloma venereum- in Catalonia since lockdown with historical data, from March 13th to August 1st 2020, comparing the observed with the expected values. RESULTS: We found that since the start of COVID-19 pandemic the number of STI reported cases was 51% less than expected, reaching an average of 56% during lockdown (50% and 45% during de-escalation and new normality) with a maximum decrease of 72% for chlamydia and minimum of 22% for syphilis. Our results indicate that fewer STIs were reported in females, people living in more deprived areas, people with no previous STI episodes during the last three years, and in the HIV negative. CONCLUSIONS: The STI notification sharp decline was maintained almost five months after lockdown started, well into the new normality. This fact can hardly be explained without significant underdiagnosis and underreporting. There is an urgent need to strengthen STI/HIV diagnostic programs and services, as well as surveillance, as the pandemic could be concealing the real size of the already described re-emergence of STIs in most of the European countries.


Assuntos
COVID-19 , Infecções por Chlamydia , Gonorreia , Infecções por HIV , Doenças Sexualmente Transmissíveis , Sífilis , Artefatos , Infecções por Chlamydia/diagnóstico , Infecções por Chlamydia/epidemiologia , Controle de Doenças Transmissíveis , Feminino , Gonorreia/epidemiologia , Infecções por HIV/epidemiologia , Humanos , Incidência , Pandemias , SARS-CoV-2 , Doenças Sexualmente Transmissíveis/epidemiologia , Sífilis/epidemiologia
2.
Sensors (Basel) ; 21(17)2021 Sep 05.
Artigo em Inglês | MEDLINE | ID: mdl-34502848

RESUMO

The protection of artistic and cultural heritage is a major challenge due to its peculiarities and its exposure to significant natural hazards. Several methodologies exist to assess the condition of artistic heritage and to protect it from exceptional actions. Moreover, novel digital technologies offer many solutions able to deliver a digital replica of artifacts of interest, so that a reduction in the uncertainties in the analysis models can be achieved. A rational approach to the preservation and protection of artistic heritage is based on traditional approaches supported and integrated by novel technologies, so that qualitative and quantitative indicators of the current condition of artistic heritage can be defined and validated in an interdisciplinary framework. The present paper reports the results of an approach to the maintenance and preservation of art objects housed in a museum complex based on a comprehensive digital path towards a Historical Digital Twin (HDT). A workflow aimed at estimating the stress regime and the dynamic properties of two sculptures, based on the detailed three-dimensional model resulting from a laser scanner survey, is illustrated and discussed. The results highlight the great advantages resulting from the integration of traditional and novel procedures in the field of conservation of artistic assets.


Assuntos
Arte , Artefatos , Lasers , Museus , Preservação Biológica
3.
J Appl Clin Med Phys ; 22(9): 332-338, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34347931

RESUMO

OBJECTIVE: To compare conventional method and compressed-sensing (CS) accelerated 3D balanced fast field echo imaging (bFFE) of inner ear. METHODS: Twenty patients with suspected inner ear disease underwent CS accelerated 3D-bFFE (CS-bFFE) and conventional 3D-bFFE (Con-bFFE) by a 3T MRI. The overall image quality, motion artifacts, and image quality of specific structures of inner ear were assessed on ordinal scales by three radiologists who were blinded to the scan protocols. Kendall W test was used to evaluate interobserver agreement and Wilcoxon test was performed to compare the image quality and motion artifacts between CS-bFFE and Con-bFFE. RESULTS: The acquisition duration of CS-bFFE (1 min 53 s) was 49% faster than Con-bFFE. Three radiologists had good inter-observer agreement of image quality (Kendall W value of 0.829 for CS-bFFE and 0.815 for Con-bFFE) and motion artifacts evaluation (Kendall W value of 0861 for CS-bFFE and 0.707 for Con-bFFE). The better overall image quality of CS-bFFE was assessed (4.93 ± 0.23 for CS-bFFE, 4.53 ± 0.70 for Con-bFFE, Z = -2.254, p = 0.024). The image quality score of facial and cochlear nerve gained higher in CS-bFFE (4.93 ± 0.23 for CS-bFFE, 4.58 ± 0.64 for Con-bFFE, Z = -2.094, p = 0.036). No significant difference of motion artifacts (p = 0.050) between CS-bFFE and Con-bFFE. CONCLUSIONS: The CS-bFFE improves image quality and reduces acquisition time significantly, and it is a feasible MRI protocol for inner ear imaging.


Assuntos
Orelha Interna , Imageamento por Ressonância Magnética , Artefatos , Orelha Interna/diagnóstico por imagem , Humanos , Imageamento Tridimensional , Pressão
4.
Sensors (Basel) ; 21(16)2021 Aug 23.
Artigo em Inglês | MEDLINE | ID: mdl-34451104

RESUMO

This work investigates elimination methods for cardiogenic artifacts in respiratory surface electromyographic (sEMG) signals and compares their performance with respect to subsequent fatigue detection with different fatigue algorithms. The analysis is based on artificially constructed test signals featuring a clearly defined expected fatigue level. Test signals are additively constructed with different proportions from sEMG and electrocardiographic (ECG) signals. Cardiogenic artifacts are eliminated by high-pass filtering (HP), template subtraction (TS), a newly introduced two-step approach (TSWD) consisting of template subtraction and a wavelet-based damping step and a pure wavelet-based damping (DSO). Each method is additionally combined with the exclusion of QRS segments (gating). Fatigue is subsequently quantified with mean frequency (MNF), spectral moments ratio of order five (SMR5) and fuzzy approximate entropy (fApEn). Different combinations of artifact elimination methods and fatigue detection algorithms are tested with respect to their ability to deliver invariant results despite increasing ECG contamination. Both DSO and TSWD artifact elimination methods displayed promising results regarding the intermediate, "cleaned" EMG signal. However, only the TSWD method enabled superior results in the subsequent fatigue detection across different levels of artifact contamination and evaluation criteria. SMR5 could be determined as the best fatigue detection algorithm. This study proposes a signal processing chain to determine neuromuscular fatigue despite the presence of cardiogenic artifacts. The results furthermore underline the importance of selecting a combination of algorithms that play well together to remove cardiogenic artifacts and to detect fatigue. This investigation provides guidance for clinical studies to select optimal signal processing to detect fatigue from respiratory sEMG signals.


Assuntos
Artefatos , Fadiga Muscular , Algoritmos , Eletrocardiografia , Eletromiografia , Contração Muscular , Músculos Respiratórios , Processamento de Sinais Assistido por Computador
5.
Orv Hetil ; 162(34): 1383-1385, 2021 08 22.
Artigo em Húngaro | MEDLINE | ID: mdl-34428175

RESUMO

Összefoglaló. Egy 47 éves nobeteg tranziens ST-eleváció miatt került felvételre és coronarographiára. A tranziens ST-elevációnak véleményezett elektrokardiogram poroszsisak-jelnek felelt meg, amelyet egy EKG-mutermék okozott. Habár a poroszsisak-jelnek számtalan, nem coronariaeredetu oka ismert, mutermék okozta poroszsisak-jelet még nem ismertettek. Fontos a felismerése a felesleges diagnosztikai és terápiás beavatkozások elkerülése céljából. Orv Hetil. 2021; 162(34): 1383-1385. Summary. A 47-year-old female patient was admitted for coronary angiography due to transient ST elevation. The electrocardiogram rated for transient ST elevation corresponded to a spiked helmet sign caused by an ECG artifact. Although a number of non-coronary causes of the spiked helmet sign are known, not one caused by a computer artifact has been reported yet. It is important to recognize it to avoid unnecessary diagnostic and therapeutic interventions. Orv Hetil. 2021; 162(34): 1383-1385.


Assuntos
Síndrome Coronariana Aguda , Síndrome Coronariana Aguda/diagnóstico , Artefatos , Angiografia Coronária , Eletrocardiografia , Feminino , Dispositivos de Proteção da Cabeça , Humanos , Pessoa de Meia-Idade
6.
Sensors (Basel) ; 21(15)2021 Jul 28.
Artigo em Inglês | MEDLINE | ID: mdl-34372353

RESUMO

Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes' movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes' movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes' movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.


Assuntos
Artefatos , Análise de Ondaletas , Movimento (Física) , Espectroscopia de Luz Próxima ao Infravermelho , Termografia
7.
Sensors (Basel) ; 21(15)2021 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-34372396

RESUMO

Electromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data can thus be seen as a nice feature that could allow both longer battery life and more simultaneous channels at the same time. A lot of research has been done in lossy compression algorithms for EMG data, but being lossy, artifacts are inevitably introduced in the signal. Some artifacts can usually be tolerable for current applications. Nevertheless, for some research purposes and to enable future research on the collected data, that might need to exploit various and currently unforseen features that had been discarded by lossy algorithms, lossless compression of data may be very important, as it guarantees no extra artifacts are introduced on the digitized signal. The present paper aims at demonstrating the effectiveness of such approaches, investigating the performance of several algorithms and their implementation on a real EMG BLE wireless sensor node. It is demonstrated that the required bandwidth can be more than halved, even reduced to 1/4 on an average case, and if the complexity of the compressor is kept low, it also ensures significant power savings.


Assuntos
Compressão de Dados , Algoritmos , Artefatos , Eletromiografia , Humanos , Fenômenos Físicos , Processamento de Sinais Assistido por Computador
8.
Sensors (Basel) ; 21(15)2021 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-34372447

RESUMO

Non-invasive photoplethysmography (PPG) technology was developed to track heart rate during physical activity under free-living conditions. Automated analysis of PPG has made it useful in both clinical and non-clinical applications. Because of their generalization capabilities, deep learning methods can be a major direction in the search for a heart rate estimation solution based on signals from wearable devices. A novel multi-headed convolutional neural network model enriched with long short-term memory cells (MH Conv-LSTM DeepPPG) was proposed for the estimation of heart rate based on signals measured by a wrist-worn wearable device, such as PPG and acceleration signals. For the PPG-DaLiA dataset, the proposed solution improves the performance of previously proposed methods. An experimental approach was used to develop the final network architecture. The average mean absolute error (MAE) of the final solution was 6.28 bpm and Pearson's correlation coefficient between the estimated and true heart rate values was 0.85.


Assuntos
Atividades Cotidianas , Processamento de Sinais Assistido por Computador , Algoritmos , Artefatos , Frequência Cardíaca , Humanos , Fotopletismografia
9.
J Neural Eng ; 18(4)2021 08 02.
Artigo em Inglês | MEDLINE | ID: mdl-34342270

RESUMO

Objective. Electroencephalography (EEG) cleaning has been a longstanding issue in the research community. In recent times, huge leaps have been made in the field, resulting in very promising techniques to address the issue. The most widespread ones rely on a family of mathematical methods known as blind source separation (BSS), ideally capable of separating artefactual signals from the brain originated ones. However, corruption of EEG data still remains a problem, especially in real life scenario where a mixture of artefact components affects the signal and thus correctly choosing the correct cleaning procedure can be non trivial. Our aim is here to evaluate and score the plethora of available BSS-based cleaning methods, providing an overview of their advantages and downsides and of their best field of application.Approach. To address this, we here first characterized and modeled different types of artefact, i.e. arising from muscular or blinking activity as well as from transcranial alternate current stimulation. We then tested and scored several BSS-based cleaning procedures on semi-synthetic datasets corrupted by the previously modeled noise sources. Finally, we built a lifelike dataset affected by many artefactual components. We tested an iterative multistep approach combining different BSS steps, aimed at sequentially removing each specific artefactual component.Main results. We did not find an overall best method, as different scenarios require different approaches. We therefore provided an overview of the performance in terms of both reconstruction accuracy and computational burden of each method in different use cases.Significance. Our work provides insightful guidelines for signal cleaning procedures in the EEG related field.


Assuntos
Algoritmos , Artefatos , Encéfalo , Mapeamento Encefálico , Eletroencefalografia , Processamento de Sinais Assistido por Computador
10.
J Neural Eng ; 18(4)2021 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-34388744

RESUMO

Objective. Technical advances in deep brain stimulation (DBS) are crucial to improve therapeutic efficacy and battery life. We report the potentialities and pitfalls of one of the first commercially available devices capable of recording brain local field potentials (LFPs) from the implanted DBS leads, chronically and during stimulation. The aim was to provide clinicians with well-grounded tips on how to maximize the capabilities of this novel device, both in everyday practice and for research purposes.Approach. We collected clinical and neurophysiological data of the first 20 patients (14 with Parkinson's disease (PD), five with dystonia, one with chronic pain) that received the Percept™ PC in our centres. We also performed tests in a saline bath to validate the recordings quality.Main results. The Percept PC reliably recorded the LFP of the implanted site, wirelessly and in real time. We recorded the most promising clinically useful biomarkers for PD and dystonia (beta and theta oscillations) with and without stimulation. Furthermore, we provide an open-source code to facilitate export and analysis of data. Critical aspects of the system are presently related to contact selection, artefact detection, data loss, and synchronization with other devices.Significance. New technologies will soon allow closed-loop neuromodulation therapies, capable of adapting stimulation based on real-time symptom-specific and task-dependent input signals. However, technical aspects need to be considered to ensure reliable recordings. The critical use by a growing number of DBS experts will alert new users about the currently observed shortcomings and inform on how to overcome them.


Assuntos
Estimulação Encefálica Profunda , Doença de Parkinson , Artefatos , Encéfalo , Humanos , Doença de Parkinson/diagnóstico , Doença de Parkinson/terapia
11.
Nat Neurosci ; 24(9): 1324-1337, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34341584

RESUMO

Inference of action potentials ('spikes') from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals ('ground truth'). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation.


Assuntos
Artefatos , Encéfalo/fisiologia , Aprendizado Profundo , Neuroimagem/métodos , Neurônios/fisiologia , Potenciais de Ação/fisiologia , Animais , Cálcio/metabolismo , Bases de Dados Factuais , Camundongos , Modelos Neurológicos , Peixe-Zebra
12.
BMC Bioinformatics ; 22(1): 398, 2021 Aug 24.
Artigo em Inglês | MEDLINE | ID: mdl-34433408

RESUMO

BACKGROUND: The analyses of amplification and melting curves have been shown to provide valuable information on the quality of the individual reactions in quantitative PCR (qPCR) experiments and to result in more reliable and reproducible quantitative results. IMPLEMENTATION: The main steps in the amplification curve analysis are (1) a unique baseline subtraction, not using the ground phase cycles, (2) PCR efficiency determination from the exponential phase of the individual reactions, (3) setting a common quantification threshold and (4) calculation of the efficiency-corrected target quantity with the common threshold, efficiency per assay and Cq per reaction. The melting curve analysis encompasses smoothing of the observed fluorescence data, normalization to remove product-independent fluorescence loss, peak calling and assessment of the correct peak by comparing its melting temperature with the known melting temperature of the intended amplification product. RESULTS: The LinRegPCR web application provides visualization and analysis of a single qPCR run. The user interface displays the analysis results on the amplification curve analysis and melting curve analysis in tables and graphs in which deviant reactions are highlighted. The annotated results in the tables can be exported for calculation of gene-expression ratios, fold-change between experimental conditions and further statistical analysis. Web-based LinRegPCR addresses two types of users, wet-lab scientists analyzing the amplification and melting curves of their own qPCR experiments and bioinformaticians creating pipelines for analysis of series of qPCR experiments by splitting its functionality into a stand-alone back-end RDML (Real-time PCR Data Markup Language) Python library and several companion applications for data visualization, analysis and interactive access. The use of the RDML data standard enables machine independent storage and exchange of qPCR data and the RDML-Tools assist with the import of qPCR data from the files exported by the qPCR instrument. CONCLUSIONS: The combined implementation of these analyses in the newly developed web-based LinRegPCR ( https://www.gear-genomics.com/rdml-tools/ ) is platform independent and much faster than the original Windows-based versions of the LinRegPCR program. Moreover, web-based LinRegPCR includes a novel statistical outlier detection and the combination of amplification and melting curve analyses allows direct validation of the amplification product and reporting of reactions that amplify artefacts.


Assuntos
Artefatos , Internet , Reação em Cadeia da Polimerase em Tempo Real
13.
Nat Commun ; 12(1): 4880, 2021 08 12.
Artigo em Inglês | MEDLINE | ID: mdl-34385444

RESUMO

Accurate and imperceptible monitoring of electrophysiological signals is of primary importance for wearable healthcare. Stiff and bulky pregelled electrodes are now commonly used in clinical diagnosis, causing severe discomfort to users for long-time using as well as artifact signals in motion. Here, we report a ~100 nm ultra-thin dry epidermal electrode that is able to conformably adhere to skin and accurately measure electrophysiological signals. It showed low sheet resistance (~24 Ω/sq, 4142 S/cm), high transparency, and mechano-electrical stability. The enhanced optoelectronic performance was due to the synergistic effect between graphene and poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), which induced a high degree of molecular ordering on PEDOT and charge transfer on graphene by strong π-π interaction. Together with ultra-thin nature, this dry epidermal electrode is able to accurately monitor electrophysiological signals such as facial skin and brain activity with low-motion artifact, enabling human-machine interfacing and long-time mental/physical health monitoring.


Assuntos
Eletrodos , Eletrofisiologia/métodos , Epiderme/fisiologia , Desenho de Equipamento/métodos , Monitorização Fisiológica/métodos , Dispositivos Eletrônicos Vestíveis , Artefatos , Compostos Bicíclicos Heterocíclicos com Pontes/química , Condutividade Elétrica , Eletrofisiologia/instrumentação , Eletrofisiologia/normas , Desenho de Equipamento/normas , Grafite/química , Humanos , Estrutura Molecular , Monitorização Fisiológica/instrumentação , Monitorização Fisiológica/normas , Movimento (Física) , Polímeros/química , Poliestirenos/química , Pele
14.
Sensors (Basel) ; 21(16)2021 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-34450799

RESUMO

Wearable cardiac sensors pave the way for advanced cardiac monitoring applications based on heart rate variability (HRV). In real-life settings, heart rate (HR) measurements are subject to motion artifacts that may lead to frequent data loss (missing samples in the HR signal), especially for commercial devices based on photoplethysmography (PPG). The current study had two main goals: (i) to provide a white-box quality index that estimates the amount of missing samples in any piece of HR signal; and (ii) to quantify the impact of data loss on feature extraction in a PPG-based HR signal. This was done by comparing real-life recordings from commercial sensors featuring both PPG (Empatica E4) and ECG (Zephyr BioHarness 3). After an outlier rejection process, our quality index was used to isolate portions of ECG-based HR signals that could be used as benchmark, to validate the output of Empatica E4 at the signal level and at the feature level. Our results showed high accuracy in estimating the mean HR (median error: 3.2%), poor accuracy for short-term HRV features (e.g., median error: 64% for high-frequency power), and mild accuracy for longer-term HRV features (e.g., median error: 25% for low-frequency power). These levels of errors could be reduced by using our quality index to identify time windows with few or no data loss (median errors: 0.0%, 27%, and 6.4% respectively, when no sample was missing). This quality index should be useful in future work to extract reliable cardiac features in real-life measurements, or to conduct a field validation study on wearable cardiac sensors.


Assuntos
Eletrocardiografia , Fotopletismografia , Artefatos , Frequência Cardíaca , Monitorização Fisiológica , Processamento de Sinais Assistido por Computador
15.
Sensors (Basel) ; 21(16)2021 Aug 18.
Artigo em Inglês | MEDLINE | ID: mdl-34450990

RESUMO

BACKGROUND: The presence of noise is problematic in the analysis and interpretation of the ECG, especially in ambulatory monitoring. Restricting the analysis to high-quality signal segments only comes with the risk of excluding significant arrhythmia episodes. Therefore, the development of novel electrode technology, robust to noise, continues to be warranted. METHODS: The signal quality of a novel wet ECG electrode (Piotrode) is assessed and compared to a commercially available, commonly used electrode (Ambu). The assessment involves indices of QRS detection and atrial fibrillation detection performance, as well as signal quality indices (ensemble standard deviation and time-frequency repeatability), computed from ECGs recorded simultaneously from 20 healthy subjects performing everyday activities. RESULTS: The QRS detection performance using the Piotrode was considerably better than when using the Ambu, especially for running but also for lighter activities. The two signal quality indices demonstrated similar trends: the gap in quality became increasingly larger as the subjects became increasingly more active. CONCLUSIONS: The novel wet ECG electrode produces signals with less motion artifacts, thereby offering the potential to reduce the review burden, and accordingly the cost, associated with ambulatory monitoring.


Assuntos
Artefatos , Processamento de Sinais Assistido por Computador , Algoritmos , Eletrocardiografia , Eletrodos , Humanos
16.
Comput Methods Programs Biomed ; 209: 106327, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34428680

RESUMO

BACKGROUND AND OBJECTIVE: A large-scale training data and accurate annotations are fundamental for current segmentation networks. However, the characteristic artifacts of ultrasound images always make the annotation task complicated, such as attenuation, speckle, shadows and signal dropout. Further complications arise as the contrast between the region of interest and background is often low. Without double-check from professionals, it is hard to guarantee that there is no noisy annotation in segmentation datasets. However, among the deep learning methods applied to ultrasound segmentation so far, no one can solve this problem. METHOD: Given a dataset with poorly labeled masks, including a certain amount of noises, we propose an end-to-end noisy annotation tolerance network (NAT-Net). NAT-Net can detect noise by the proposed noise index (NI) and dynamically correct noisy annotations in the training stage. Simultaneously, noise index is used to correct the noise along with the output of the learning model. This method does not need any auxiliary clean datasets or prior knowledge of noise distributions, so it is more general, robust and easier to apply than the existing methods. RESULTS: NAT-Net outperforms previous state-of-the-art methods on synthesized data with different noise ratio. For real-world dataset with more complex noise types, the IoU of NAT-Net is higher than that of state-of-art approaches by nearly 6%. Experimental results show that our method can also achieve good results compared with the existing methods for clean dataset. CONCLUSION: The NAT-Net reduces manual interaction of data annotation, reduces dependence on medical personnel. After tumor segmentation, disease diagnosis efficiency is improved, which provides an auxiliary strategies for subsequent medical diagnosis systems based on ultrasound.


Assuntos
Processamento de Imagem Assistida por Computador , Ultrassonografia Mamária , Artefatos , Feminino , Humanos , Ultrassonografia
17.
Sensors (Basel) ; 21(13)2021 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-34283086

RESUMO

An increasing proportion of occupational mishaps in dynamic, high-risk operational environments have been attributed to human error, yet there are currently no devices to routinely provide accurate physiological data for insights into underlying contributing factors. This is most commonly due to limitations of commercial and clinical devices for collecting physiological data in environments of high motion. Herein, a novel Photoplethysmography (PPG) sensor device was tested, called SPYDR (Standalone Performance Yielding Deliberate Risk), reading from a behind-the-ear location, specifically designed for high-fidelity data collection in highly dynamic high-motion, high-pressure, low-oxygen, and high-G-force environments. For this study, SPYDR was installed as a functional ear-cup replacement in flight helmets worn by rated US Navy aircrew. Subjects were exposed to reduced atmospheric pressure using a hypobaric chamber to simulated altitudes of 25,000 feet and high G-forces in a human-rated centrifuge up to 9 G acceleration. Data were compared to control devices, finger and forehead PPG sensors, and a chest-mounted 12-lead ECG. SPYDR produced high-fidelity data compared to controls with little motion-artifact controls in the no-motion environment of the hypobaric chamber. However, in the high-motion, high-force environment of the centrifuge, SPYDR recorded consistent, accurate data, whereas PPG controls and ECG data were unusable due to a high-degree-motion artifacts. The data demonstrate that SPYDR provides an accurate and reliable system for continuous physiological monitoring in high-motion, high-risk environments, yielding a novel method for collecting low-artifact cardiovascular assessment data important for investigating currently inaccessible parameters of human physiology.


Assuntos
Algoritmos , Fotopletismografia , Artefatos , Eletrocardiografia , Frequência Cardíaca , Humanos , Monitorização Fisiológica , Processamento de Sinais Assistido por Computador
18.
Eur J Radiol ; 142: 109865, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34298389

RESUMO

PURPOSE: MRI is a powerful tool for optic nerve assessment, but image quality can be degraded by artifacts related to ocular motion. The purpose of this investigation was to evaluate the effect of undergoing MRI with eyes open versus closed on the degree of motion degradation affecting the optic nerves. METHOD: Patients undergoing 3 Tesla orbital MRI were randomized to undergo the coronal STIR sequence with eyes open and focused on a standardized fixation point, blinking as needed, or with eyes closed. The sequence was then performed again with the other instruction set. Two neuroradiologists rated the intraorbital optic nerves for motion artifact on a 5-point scale (higher numbers reflecting greater motion artifact) in 2 locations of each nerve. Differences were evaluated by the clustered Wilcoxon signed rank test. RESULTS: Seventy-seven orbits were included. Interrater reliability was high (weighted kappa = 0.78). The anterior intraorbital optic nerves were rated with less motion artifact when eyes were open and focused during acquisition than when closed (p = 0.006), but this was not the case for the posterior intraorbital optic nerve (p = 0.69). For example, at the anterior intraorbital optic nerve, motion artifact of mean grade better than 2 was seen in 60% of eyes-open vs. 32% of eyes-closed acquisitions, while mean grade 4 or worse was seen in 4% of eyes-open vs. 12% of eyes-closed acquisitions. CONCLUSION: Undergoing orbital MRI with eyes open and focused rather than closed reduces motion artifact at the anterior intraorbital segment of the optic nerve.


Assuntos
Imageamento por Ressonância Magnética , Nervo Óptico , Artefatos , Humanos , Movimento (Física) , Nervo Óptico/diagnóstico por imagem , Reprodutibilidade dos Testes
19.
Sensors (Basel) ; 21(13)2021 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-34201834

RESUMO

Multi-channel measurements from the maternal abdomen acquired by means of dry electrodes can be employed to promote long-term monitoring of fetal heart rate (fHR). The signals acquired with this type of electrode have a lower signal-to-noise ratio and different artifacts compared to signals acquired with conventional wet electrodes. Therefore, starting from the benchmark algorithm with the best performance for fHR estimation proposed by Varanini et al., we propose a new method specifically designed to remove artifacts typical of dry-electrode recordings. To test the algorithm, experimental textile electrodes were employed that produce artifacts typical of dry and capacitive electrodes. The proposed solution is based on a hybrid (hardware and software) pre-processing step designed specifically to remove the disturbing component typical of signals acquired with these electrodes (triboelectricity artifacts and amplitude modulations). The following main processing steps consist of the removal of the maternal ECG by blind source separation, the enhancement of the fetal ECG and identification of the fetal QRS complexes. Main processing is designed to be robust to the high-amplitude motion artifacts that corrupt the acquisition. The obtained denoising system was compared with the benchmark algorithm both on semi-simulated and on real data. The performance, quantified by means of sensitivity, F1-score and root-mean-square error metrics, outperforms the performance obtained with the original method available in the literature. This result proves that the design of a dedicated processing system based on the signal characteristics is necessary for reliable and accurate estimation of the fHR using dry, textile electrodes.


Assuntos
Frequência Cardíaca Fetal , Processamento de Sinais Assistido por Computador , Algoritmos , Artefatos , Eletrocardiografia , Eletrodos , Feminino , Humanos , Gravidez
20.
Sensors (Basel) ; 21(14)2021 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-34300544

RESUMO

Gamification is known to enhance users' participation in education and research projects that follow the citizen science paradigm. The Cosmic Ray Extremely Distributed Observatory (CREDO) experiment is designed for the large-scale study of various radiation forms that continuously reach the Earth from space, collectively known as cosmic rays. The CREDO Detector app relies on a network of involved users and is now working worldwide across phones and other CMOS sensor-equipped devices. To broaden the user base and activate current users, CREDO extensively uses the gamification solutions like the periodical Particle Hunters Competition. However, the adverse effect of gamification is that the number of artefacts, i.e., signals unrelated to cosmic ray detection or openly related to cheating, substantially increases. To tag the artefacts appearing in the CREDO database we propose the method based on machine learning. The approach involves training the Convolutional Neural Network (CNN) to recognise the morphological difference between signals and artefacts. As a result we obtain the CNN-based trigger which is able to mimic the signal vs. artefact assignments of human annotators as closely as possible. To enhance the method, the input image signal is adaptively thresholded and then transformed using Daubechies wavelets. In this exploratory study, we use wavelet transforms to amplify distinctive image features. As a result, we obtain a very good recognition ratio of almost 99% for both signal and artefacts. The proposed solution allows eliminating the manual supervision of the competition process.


Assuntos
Processamento de Imagem Assistida por Computador , Redes Neurais de Computação , Artefatos , Humanos , Aprendizado de Máquina , Análise de Ondaletas
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