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1.
Vestn Otorinolaringol ; 86(3): 52-55, 2021.
Artigo em Russo | MEDLINE | ID: mdl-34269024

RESUMO

Purpose is to study the long-term results of patients with cicatricial stenosis of the larynx treated with use lyophilized xenodermoimplants for postoperative wound plasty. MATERIAL AND METHODS: The results of treatment of 34 patients (age from 32 to 56 years) with cicatricial stenosis of the larynx were analyzed. A fundamentally new method of surgical treatment of such patients has been developed and introduced into practice, in which lyophilized xenodermoimplants were used for plasty of the wound surface. RESULTS: The proposed technique made it possible in the immediate postoperative period to obtain a good result in 28 (82.4%) patients, satisfactory - in 6 (17.6%). The length of hospital stay was reduced by 8-10 days. In the long-term period (after 6-11 years), 27 patients were examined. Of these, 21 (77.8%) obtained a good result, and 6 (22.2%) - satisfactory. CONCLUSION: The proposed method of surgical rehabilitation of the respiratory function of the larynx with its cicatricial stenosis using lyophilized xenodermoimplants is quite effective and can be proposed for use in clinical practice.


Assuntos
Laringoestenose , Laringe , Adulto , Constrição Patológica , Humanos , Laringoestenose/diagnóstico , Laringoestenose/etiologia , Laringoestenose/cirurgia , Laringe/cirurgia , Pessoa de Meia-Idade , Período Pós-Operatório , Respiração
2.
Nan Fang Yi Ke Da Xue Xue Bao ; 41(6): 916-922, 2021 Jun 20.
Artigo em Chinês | MEDLINE | ID: mdl-34238745

RESUMO

OBJECTIVE: To analyze the respiratory motion of the scanned object during acquisition of digital chest tomosynthesis (CTS) using a linear model. OBJECTIVE: Respiratory signals were generated by extracting the motion of the diaphragm from the projection radiographs. The diaphragm trajectory obtained by dynamic programming (DP) was modeled and fitted, and according to the fitting of the data, the base motion curve and respiratory signal curve of the diaphragm were separated. Multipurpose chest phantom data, simulated digital Xcat phantom data and the datasets of 3 clinical patients were used to validate the performance of the proposed method. OBJECTIVE: The motion trajectory of the diaphragm extracted from multipurpose chest phantom simulation data was linear. The respiratory signals could be effectively extracted from the 3 datasets of clinical patients in different respiratory states. The correlation coefficient between the respiratory signal extracted in Xcat simulation experiment and the original design was 0.9797. OBJECTIVE: The linear model can effectively obtain the respiratory motion information of patients in real time, thus enabling the physicians to make clinical decisions on a rescan.


Assuntos
Respiração , Simulação por Computador , Humanos , Movimento (Física) , Imagens de Fantasmas
3.
PLoS One ; 16(7): e0254666, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34255812

RESUMO

INTRODUCTION: Motor imagery (MI) is the mental rehearsal of a motor task. Between real and imagined movements, a functional equivalence has been described regarding timing and brain activation. The primary study aim was to investigate the feasibility of MI training focusing on the autonomic function in healthy young people. Further aims were to evaluate participants' MI abilities and compare preliminary effects of activating and relaxing MI on autonomic function and against controls. METHODS: A single-blinded randomised controlled pilot trial was performed. Participants were randomised to the activating MI (1), relaxing MI (2), or control (3) group. Following a MI familiarisation, they practiced home-based kinaesthetic MI for 17 minutes, 5 times/week for 2 weeks. Participants were called once for support. The primary outcome was the feasibility of a full-scale randomised controlled trial using predefined criteria. Secondary outcomes were participants' MI ability using the Movement Imagery Questionnaire-Revised, mental chronometry tests, hand laterality judgement and semi-structured interviews, autonomic function. RESULTS: A total of 35 participants completed the study. The feasibility of a larger study was confirmed, despite 35% attrition related to the COVID-19 pandemic. Excellent MI capabilities were seen in participants, and significant correlations between MI ability measures. Interview results showed that participants accepted or liked both interventions. Seven major themes and insider recommendations for MI interventions emerged. No significant differences and negligible to medium effects were observed in MI ability or autonomic function between baseline and post-intervention measures or between groups. CONCLUSIONS: Results showed that neither activating nor relaxing MI seems to change autonomic function in healthy individuals. Further adequately powered studies are required to answer open questions remaining from this study. Future studies should investigate effects of different MI types over a longer period, to rule out habituation and assess autonomic function at several time points and simultaneously with MI.


Assuntos
Sistema Nervoso Autônomo/fisiologia , Imagens, Psicoterapia/métodos , Destreza Motora , Metabolismo Basal , Feminino , Habituação Psicofisiológica , Voluntários Saudáveis , Frequência Cardíaca , Humanos , Masculino , Respiração , Adulto Jovem
4.
Nat Commun ; 12(1): 4229, 2021 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-34244477

RESUMO

Cell response to force regulates essential processes in health and disease. However, the fundamental mechanical variables that cells sense and respond to remain unclear. Here we show that the rate of force application (loading rate) drives mechanosensing, as predicted by a molecular clutch model. By applying dynamic force regimes to cells through substrate stretching, optical tweezers, and atomic force microscopy, we find that increasing loading rates trigger talin-dependent mechanosensing, leading to adhesion growth and reinforcement, and YAP nuclear localization. However, above a given threshold the actin cytoskeleton softens, decreasing loading rates and preventing reinforcement. By stretching rat lungs in vivo, we show that a similar phenomenon may occur. Our results show that cell sensing of external forces and of passive mechanical parameters (like tissue stiffness) can be understood through the same mechanisms, driven by the properties under force of the mechanosensing molecules involved.


Assuntos
Citoesqueleto de Actina/metabolismo , Adesão Celular/fisiologia , Mecanotransdução Celular/fisiologia , Citoesqueleto de Actina/ultraestrutura , Animais , Núcleo Celular/metabolismo , Células Cultivadas , Citoplasma/metabolismo , Fibroblastos , Técnicas de Silenciamento de Genes , Peptídeos e Proteínas de Sinalização Intracelular/metabolismo , Pulmão/fisiologia , Masculino , Camundongos , Camundongos Knockout , Microscopia de Força Atômica , Pinças Ópticas , Paxilina/metabolismo , Cultura Primária de Células , Ratos , Ratos Sprague-Dawley , Respiração , Organismos Livres de Patógenos Específicos , Talina/genética , Talina/metabolismo
5.
PLoS One ; 16(7): e0254134, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34197556

RESUMO

A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a robust computerized respiratory sound analysis algorithm for breath phase detection and adventitious sound detection at the recording level has not yet been validated in practical applications. In this study, we developed a lung sound database (HF_Lung_V1) comprising 9,765 audio files of lung sounds (duration of 15 s each), 34,095 inhalation labels, 18,349 exhalation labels, 13,883 continuous adventitious sound (CAS) labels (comprising 8,457 wheeze labels, 686 stridor labels, and 4,740 rhonchus labels), and 15,606 discontinuous adventitious sound labels (all crackles). We conducted benchmark tests using long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (BiLSTM), bidirectional GRU (BiGRU), convolutional neural network (CNN)-LSTM, CNN-GRU, CNN-BiLSTM, and CNN-BiGRU models for breath phase detection and adventitious sound detection. We also conducted a performance comparison between the LSTM-based and GRU-based models, between unidirectional and bidirectional models, and between models with and without a CNN. The results revealed that these models exhibited adequate performance in lung sound analysis. The GRU-based models outperformed, in terms of F1 scores and areas under the receiver operating characteristic curves, the LSTM-based models in most of the defined tasks. Furthermore, all bidirectional models outperformed their unidirectional counterparts. Finally, the addition of a CNN improved the accuracy of lung sound analysis, especially in the CAS detection tasks.


Assuntos
COVID-19/fisiopatologia , Pulmão/fisiopatologia , Sons Respiratórios/fisiopatologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Benchmarking , COVID-19/diagnóstico , Bases de Dados Factuais , Progressão da Doença , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Redes Neurais de Computação , Respiração
6.
Sensors (Basel) ; 21(13)2021 Jun 27.
Artigo em Inglês | MEDLINE | ID: mdl-34199084

RESUMO

Respiration is a key vital sign used to monitor human health status. Monitoring respiratory rate (RR) under non-contact is particularly important for providing appropriate pre-hospital care in emergencies. We propose an RR estimation system using thermal imaging cameras, which are increasingly being used in the medical field, such as recently during the COVID-19 pandemic. By measuring temperature changes during exhalation and inhalation, we aim to track the respiration of the subject in a supine or seated position in real-time without any physical contact. The proposed method automatically selects the respiration-related regions from the detected facial regions and estimates the respiration rate. Most existing methods rely on signals from nostrils and require close-up or high-resolution images, while our method only requires the facial region to be captured. Facial region is detected using YOLO v3, an object detection model based on deep learning. The detected facial region is divided into subregions. By calculating the respiratory likelihood of each segmented region using the newly proposed index, called the Respiratory Quality Index, the respiratory region is automatically selected and the RR is estimated. An evaluation of the proposed RR estimation method was conducted on seven subjects in their early twenties, with four 15 s measurements being taken. The results showed a mean absolute error of 0.66 bpm. The proposed method can be useful as an RR estimation method.


Assuntos
COVID-19 , Taxa Respiratória , Algoritmos , Humanos , Monitorização Fisiológica , Pandemias , Respiração , SARS-CoV-2 , Termografia
7.
J Bras Pneumol ; 47(4): e20210076, 2021.
Artigo em Inglês, Português | MEDLINE | ID: mdl-34287504

RESUMO

OBJECTIVE: High prevalences of muscle weakness and impaired physical performance in hospitalized patients recovering from COVID-19-associated pneumonia have been reported. Our objective was to determine whether the level of exercise capacity after discharge would affect long-term functional outcomes in these patients. METHODS: From three to five weeks after discharge from acute care hospitals (T0), patients underwent a six-minute walk test (6MWT) and were divided into two groups according to the distance walked in percentage of predicted values: <75% group and ≥75% group. At T0 and three months later (T1), patients completed the Short Physical Performance Battery and the Euro Quality of Life Visual Analogue Scale, and pulmonary function and respiratory muscle function were assessed. In addition, a repeat 6MWT was also performed at T1. RESULTS: At T0, 6MWD values and Short Physical Performance Battery scores were lower in the <75% group than in the ≥75% group. No differences were found in the Euro Quality of Life Visual Analogue Scale scores, pulmonary function variables, respiratory muscle function variables, length of hospital stay, or previous treatment. At T1, both groups improved their exercise capacity, but only the subjects in the <75% group showed significant improvements in dyspnea and lower extremity function. Exercise capacity and functional status values returned to predicted values in all of the patients in both groups. CONCLUSIONS: Four weeks after discharge, COVID-19 survivors with exercise limitation showed no significant differences in physiological or clinical characteristics or in perceived health status when compared with patients without exercise limitation. Three months later, those patients recovered their exercise capacity.


Assuntos
COVID-19 , Tolerância ao Exercício , Teste de Esforço , Humanos , Qualidade de Vida , Respiração , SARS-CoV-2
8.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue ; 33(6): 680-685, 2021 Jun.
Artigo em Chinês | MEDLINE | ID: mdl-34296686

RESUMO

OBJECTIVE: To investigate the relationship between double-triggering and abnormal movement of air in the lungs (pendelluft phenomenon) under pressure support ventilation (PSV). METHODS: A prospective observational study was conducted, postoperative patients admitted to department of critical care medicine of Beijing Tiantan Hospital, Capital Medical University from April 1, 2019 to August 31, 2020 and received invasive mechanical ventilation with PSV mode were enrolled. Electrical impedance tomography (EIT) monitoring was performed. Airway pressure-time, flow-time, global and regional impedance-time curves were synchronously collected and analyzed offline. The volume of abnormal movement of air in the lungs at the beginning of inspiration was measured and defined as pendelluft volume. Double-triggered breaths were identified by trained researchers. Pendelluft volume during double-triggering was measured including the first triggered breath, the double-triggered breath, and the breath immediately following the double-triggered breath. Pendelluft volume was also measured for normal breath during the study. According to the frequency of double-triggering, patients were divided into severe (≥ 1 time/min) and non-severe double-triggering group. Pendelluft volume, parameters of respiratory mechanics, and clinical outcomes between the two groups were compared. RESULTS: In 40 enrolled patients, a total of 9 711 breaths [(243±63) breaths/patient] were collected and analyzed, among which 222 breaths (2.3%) were identified as double-triggering. The Kappa of interobserver reliability to detect double-triggering was 0.964 [95% confidence interval (95%CI) was 0.946-0.982]. In 222 double-triggered breaths, pendelluft volume could not be measured in 7 breaths (3.2%), but the pendelluft phenomenon did exist as shown by opposite regional impedance change at the beginning of double-triggered inspiration. Finally, pendelluft volume was measured in 215 double-triggered breaths. Meanwhile, 400 normal breaths (10 normal breaths randomly selected for each patient) were identified as control. Compared with normal breath, pendelluft volume significantly increased in the first breath, the double-triggered breath, and the following normal breath [mL: 3.0 (1.4, 6.4), 8.3 (3.6, 13.2), 4.3 (1.9, 9.1) vs. 1.4 (0.7, 2.8), all P < 0.05]. Patients in severe double-triggering, pendelluft volume of normal breath and double-triggered breath were significantly higher than those in non-severe double-triggering group [mL: 1.8 (0.9, 3.2) vs. 1.1 (0.5, 2.1), P < 0.001; 8.5 (3.9, 13.4) vs. 2.0 (0.6, 9.1), P = 0.008]. Patients in severe double-triggering group had significantly higher respiratory rate than that in the non-severe double-triggering group (breaths/min: 20.9±3.5 vs. 15.2±3.7, P < 0.001). There were no significant differences in other respiratory mechanics parameters and main clinical outcomes between the two groups. CONCLUSIONS: During PSV, the abnormal movement of air in the lungs (pendelluft phenomenon) was more likely to occur in double-triggering especially in double-triggered breath. The more frequent the double-triggering occurred, the more serious the pendelluft phenomenon was. A higher pendelluft volume of normal breath and a higher respiratory rate were related to severity of double-triggering.


Assuntos
Respiração com Pressão Positiva , Respiração Artificial , Humanos , Estudos Prospectivos , Reprodutibilidade dos Testes , Respiração
9.
Sensors (Basel) ; 21(14)2021 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-34300552

RESUMO

Utilising cooling stimulation as a thermal excitation means has demonstrated profound capabilities of detecting sub-surface metal loss using thermography. Previously, a prototype mechanism was introduced which accommodates a thermal camera and cooling source and operates in a reciprocating motion scanning the test piece while cold stimulation is in operation. Immediately after that, the camera registers the thermal evolution. However, thermal reflections, non-uniform stimulation and lateral heat diffusions will remain as undesirable phenomena preventing the effective observation of sub-surface defects. This becomes more challenging when there is no prior knowledge of the non-defective area in order to effectively distinguish between defective and non-defective areas. In this work, the previously automated acquisition and processing pipeline is re-designed and optimised for two purposes: 1-Through the previous work, the mentioned pipeline was used to analyse a specific area of the test piece surface in order to reconstruct the reference area and identify defects. In order to expand the application of this device over the entire test area, regardless of its extension, the pipeline is improved in which the final surface image is reconstructed by taking into account multiple segments of the test surface. The previously introduced pre-processing method of Dynamic Reference Reconstruction (DRR) is enhanced by using a more rigorous thresholding procedure. Principal Component Analysis (PCA) is then used in order for feature (DRR images) reduction. 2-The results of PCA on multiple segment images of the test surface revealed different ranges of intensities across each segment image. This potentially could cause mistaken interpretation of the defective and non-defective areas. An automated segmentation method based on Gaussian Mixture Model (GMM) is used to assist the expert user in more effective detection of the defective areas when the non-defective areas are uniformly characterised as background. The final results of GMM have shown not only the capability of accurately detecting subsurface metal loss as low as 37.5% but also the successful detection of defects that were either unidentifiable or invisible in either the original thermal images or their PCA transformed results.


Assuntos
Respiração , Termografia , Movimento (Física) , Análise de Componente Principal
10.
Sensors (Basel) ; 21(14)2021 Jul 19.
Artigo em Inglês | MEDLINE | ID: mdl-34300635

RESUMO

This paper reports on a mask-type sensor for simultaneous pulse wave and respiration measurements and eye blink detection that uses only one sensing element. In the proposed sensor, a flexible air bag-shaped chamber whose inner pressure change can be measured by a microelectromechanical system-based piezoresistive cantilever was used as the sensing element. The air bag-shaped chamber is fabricated by wrapping a sponge pad with plastic film and polyimide tape. The polyimide tape has a hole to which the substrate with the piezoresistive cantilever adheres. By attaching the sensor device to a mask where it contacts the nose of the subject, the sensor can detect the pulses and eye blinks of the subject by detecting the vibration and displacement of the nose skin caused by these physiological parameters. Moreover, the respiration of the subject causes pressure changes in the space between the mask and the face of the subject as well as slight vibrations of the mask. Therefore, information about the respiration of the subject can be extracted from the sensor signal using either the low-frequency component (<1 Hz) or the high-frequency component (>100 Hz). This paper describes the sensor fabrication and provides demonstrations of the pulse wave and respiration measurements as well as eye blink detection using the fabricated sensor.


Assuntos
Sistemas Microeletromecânicos , Piscadela , Frequência Cardíaca , Pressão , Respiração
11.
Sensors (Basel) ; 21(11)2021 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-34199681

RESUMO

Non-contact detection of the breathing patterns in a remote and unobtrusive manner has significant value to healthcare applications and disease diagnosis, such as in COVID-19 infection prediction. During the epidemic prevention and control period of COVID-19, non-contact approaches have great significance because they minimize the physical burden on the patient and have the least requirement of active cooperation of the infected individual. During the pandemic, these non-contact approaches also reduce environmental constraints and remove the need for extra preparations. According to the latest medical research, the breathing pattern of a person infected with COVID-19 is unlike the breathing associated with flu and the common cold. One noteworthy symptom that occurs in COVID-19 is an abnormal breathing rate; individuals infected with COVID-19 have more rapid breathing. This requires continuous real-time detection of breathing patterns, which can be helpful in the prediction, diagnosis, and screening for people infected with COVID-19. In this research work, software-defined radio (SDR)-based radio frequency (RF) sensing techniques and machine learning (ML) algorithms are exploited to develop a platform for the detection and classification of different abnormal breathing patterns. ML algorithms are used for classification purposes, and their performance is evaluated on the basis of accuracy, prediction speed, and training time. The results show that this platform can detect and classify breathing patterns with a maximum accuracy of 99.4% through a complex tree algorithm. This research has a significant clinical impact because this platform can also be deployed for practical use in pandemic and non-pandemic situations.


Assuntos
COVID-19 , Algoritmos , Humanos , Pandemias , Respiração , SARS-CoV-2
12.
Sensors (Basel) ; 21(12)2021 Jun 09.
Artigo em Inglês | MEDLINE | ID: mdl-34207864

RESUMO

We present a novel method for estimating respiratory motion using inertial measurement units (IMUs) based on microelectromechanical systems (MEMS) technology. As an application of the method we consider the amplitude gating of positron emission tomography (PET) imaging, and compare the method against a clinically used respiration motion estimation technique. The presented method can be used to detect respiratory cycles and estimate their lengths with state-of-the-art accuracy when compared to other IMU-based methods, and is the first based on commercial MEMS devices, which can estimate quantitatively both the magnitude and the phase of respiratory motion from the abdomen and chest regions. For the considered test group consisting of eight subjects with acute myocardial infarction, our method achieved the absolute breathing rate error per minute of 0.44 ± 0.23 1/min, and the absolute amplitude error of 0.24 ± 0.09 cm, when compared to the clinically used respiratory motion estimation technique. The presented method could be used to simplify the logistics related to respiratory motion estimation in PET imaging studies, and also to enable multi-position motion measurements for advanced organ motion estimation.


Assuntos
Tomografia por Emissão de Pósitrons , Respiração , Abdome , Humanos , Processamento de Imagem Assistida por Computador , Movimento (Física) , Tórax
13.
Sensors (Basel) ; 21(12)2021 Jun 09.
Artigo em Inglês | MEDLINE | ID: mdl-34207899

RESUMO

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients' discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R2 = 0.98) vs. 0.98, 0.11 s (R2 = 0.88), Bland-Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.


Assuntos
Eletrocardiografia , Respiração , Coração , Humanos , Monitorização Fisiológica , Reprodutibilidade dos Testes , Processamento de Sinais Assistido por Computador
14.
Sensors (Basel) ; 21(12)2021 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-34207961

RESUMO

Respiratory rate (RR) is typically the first vital sign to change when a patient decompensates. Despite this, RR is often monitored infrequently and inaccurately. The Circadia Contactless Breathing Monitor™ (model C100) is a novel device that uses ultra-wideband radar to monitor RR continuously and un-obtrusively. Performance of the Circadia Monitor was assessed by direct comparison to manually scored reference data. Data were collected across a range of clinical and non-clinical settings, considering a broad range of user characteristics and use cases, in a total of 50 subjects. Bland-Altman analysis showed high agreement with the gold standard reference for all study data, and agreement fell within the predefined acceptance criteria of ±5 breaths per minute (BrPM). The 95% limits of agreement were -3.0 to 1.3 BrPM for a nonprobability sample of subjects while awake, -2.3 to 1.7 BrPM for a clinical sample of subjects while asleep, and -1.2 to 0.7 BrPM for a sample of healthy subjects while asleep. Accuracy rate, using an error margin of ±2 BrPM, was found to be 90% or higher. Results demonstrate that the Circadia Monitor can effectively and efficiently be used for accurate spot measurements and continuous bedside monitoring of RR in low acuity settings, such as the nursing home or hospital ward, or for remote patient monitoring.


Assuntos
Radar , Taxa Respiratória , Humanos , Monitorização Fisiológica , Respiração , Tecnologia
15.
Nutrients ; 13(6)2021 Jun 09.
Artigo em Inglês | MEDLINE | ID: mdl-34207775

RESUMO

Arterial hypercapnia reduces renal perfusion. Beetroot juice (BRJ) increases nitric oxide bioavailability and may improve renal blood flow. We tested the hypothesis that acute consumption of BRJ attenuates both decreases in blood velocity and increases in vascular resistance in the renal and segmental arteries during acute hypercapnia. In fourteen healthy young adults, blood velocity and vascular resistance were measured with Doppler ultrasound in the renal and segmental arteries during five minutes of breathing a carbon dioxide gas mixture (CO2) before and three hours after consuming 500 mL of BRJ. There was no difference between pre- and post-BRJ consumption in the increase in the partial pressure of end-tidal CO2 during CO2 breathing (pre: +4 ± 1 mmHg; post: +4 ± 2 mmHg, p = 0.4281). Segmental artery blood velocity decreased during CO2 breathing in both pre- (by -1.8 ± 1.9 cm/s, p = 0.0193) and post-BRJ (by -2.1 ± 1.9 cm/s, p = 0.0079), but there were no differences between pre- and post-consumption (p = 0.7633). Segmental artery vascular resistance increased from room air baseline during CO2 at pre-BRJ consumption (by 0.4 ± 0.4 mmHg/cm/s, p = 0.0153) but not post-BRJ (p = 0.1336), with no differences between pre- and post-consumption (p = 0.7407). These findings indicate that BRJ consumption does not attenuate reductions in renal perfusion during acute mild hypercapnia in healthy young adults.


Assuntos
Beta vulgaris , Sucos de Frutas e Vegetais , Hemodinâmica/efeitos dos fármacos , Hipercapnia/fisiopatologia , Rim/irrigação sanguínea , Raízes de Plantas , Adulto , Pressão Arterial , Velocidade do Fluxo Sanguíneo/efeitos dos fármacos , Dióxido de Carbono , Ingestão de Líquidos/fisiologia , Feminino , Voluntários Saudáveis , Humanos , Masculino , Artéria Renal/fisiopatologia , Respiração/efeitos dos fármacos , Volume de Ventilação Pulmonar/efeitos dos fármacos , Ultrassonografia Doppler , Resistência Vascular/efeitos dos fármacos
16.
Sensors (Basel) ; 21(10)2021 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-34069847

RESUMO

Respiration rate is an essential indicator of vital signs, which can demonstrate the physiological condition of the human body and provide clues to some diseases. Commercial Wi-Fi devices can provide a non-invasive, cost-effective and long-term respiration rate-monitoring scheme for home scenarios. However, previous studies show that the breathing depth and location may affect the detectability of respiratory signals. In this study, we leverage the variation of the Doppler spectral energy extracted from the channel state information (CSI) collected by Wi-Fi devices to track the chest displacement induced by respiration. First, the random phase is eliminated by phase-fitting method to obtain the complex CSI containing the Doppler shift. Then, the multipath decomposition of CSI is carried out to obtain the channel impulse response, which eliminates the interference phase of the time delay and retains the Doppler shift. The dynamic path units are also separate from the multipath, which overcomes the indoor multipath effect. Finally, we conduct a time-frequency analysis to dynamic units to accumulate Doppler spectral energy. Based on these ideas, we design a complete respiration rate-monitoring system to obtain the respiration rate by using the consistency between the Doppler energy change period and the respiratory cycle. We evaluate our system through extensive experiments in several typical home environments filled with multipath. Experimental results show that the errors of the three scenarios are approximate, the maximum error is less than 0.7 bpm, and the average errors are approximately 0.15 bpm. This result indicates that our scheme can achieve high precision respiration monitoring and has good anti-multipath ability compared with existing methods.


Assuntos
Taxa Respiratória , Sinais Vitais , Efeito Doppler , Humanos , Monitorização Fisiológica , Respiração
17.
Sensors (Basel) ; 21(9)2021 May 02.
Artigo em Inglês | MEDLINE | ID: mdl-34063222

RESUMO

In this paper, we propose an unobtrusive method and architecture for monitoring a person's presence and collecting his/her health-related parameters simultaneously in a home environment. The system is based on using a single ultra-wideband (UWB) impulse-radar as a sensing device. Using UWB radars, we aim to recognize a person and some preselected movements without camera-type monitoring. Via the experimental work, we have also demonstrated that, by using a UWB signal, it is possible to detect small chest movements remotely to recognize coughing, for example. In addition, based on statistical data analysis, a person's posture in a room can be recognized in a steady situation. In addition, we implemented a machine learning technique (k-nearest neighbour) to automatically classify a static posture using UWB radar data. Skewness, kurtosis and received power are used in posture classification during the postprocessing. The classification accuracy achieved is more than 99%. In this paper, we also present reliability and fault tolerance analyses for three kinds of UWB radar network architectures to point out the weakest item in the installation. This information is highly important in the system's implementation.


Assuntos
Radar , Processamento de Sinais Assistido por Computador , Idoso , Feminino , Humanos , Masculino , Monitorização Fisiológica , Postura , Reprodutibilidade dos Testes , Respiração
18.
Sensors (Basel) ; 21(10)2021 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-34063527

RESUMO

Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would reduce discomfort and help detect and prevent fatal diseases. Therefore, we propose a respiration measurement method using a learning-based region-of-interest detector and a clustering-based respiration pixel estimation technique. The proposed method consists of a model for classifying whether a pixel conveys respiration information based on its variance and a method for classifying pixels with clear breathing components using the symmetry of the respiration signals. The proposed method was evaluated with the data of 14 men and women acquired in an actual environment, and it was confirmed that the average error was within approximately 0.1 bpm. In addition, a Bland-Altman analysis confirmed that the measurement result had no error bias, and regression analysis confirmed that the correlation of the results with the reference is high. The proposed method, designed to be inexpensive, fast, and robust to noise, is potentially suitable for practical use in clinical scenarios.


Assuntos
Redes Neurais de Computação , Respiração , Análise por Conglomerados , Feminino , Humanos , Masculino
19.
Sensors (Basel) ; 21(9)2021 May 03.
Artigo em Inglês | MEDLINE | ID: mdl-34063576

RESUMO

During the pandemic of coronavirus disease-2019 (COVID-19), medical practitioners need non-contact devices to reduce the risk of spreading the virus. People with COVID-19 usually experience fever and have difficulty breathing. Unsupervised care to patients with respiratory problems will be the main reason for the rising death rate. Periodic linearly increasing frequency chirp, known as frequency-modulated continuous wave (FMCW), is one of the radar technologies with a low-power operation and high-resolution detection which can detect any tiny movement. In this study, we use FMCW to develop a non-contact medical device that monitors and classifies the breathing pattern in real time. Patients with a breathing disorder have an unusual breathing characteristic that cannot be represented using the breathing rate. Thus, we created an Xtreme Gradient Boosting (XGBoost) classification model and adopted Mel-frequency cepstral coefficient (MFCC) feature extraction to classify the breathing pattern behavior. XGBoost is an ensemble machine-learning technique with a fast execution time and good scalability for predictions. In this study, MFCC feature extraction assists machine learning in extracting the features of the breathing signal. Based on the results, the system obtained an acceptable accuracy. Thus, our proposed system could potentially be used to detect and monitor the presence of respiratory problems in patients with COVID-19, asthma, etc.


Assuntos
COVID-19 , Processamento de Sinais Assistido por Computador , Algoritmos , Humanos , Respiração , SARS-CoV-2
20.
Sensors (Basel) ; 21(10)2021 May 17.
Artigo em Inglês | MEDLINE | ID: mdl-34067611

RESUMO

There is abundant worldwide research conducted on the subject of the methods of human respiration process examination. However, many of these studies describe methods and present the results while often lacking insight into the hardware and software aspects of the devices used during the research. This paper's goal is to present new equipment for assessing the parameters of human respiration, which can be easily adopted for daily diagnosis. This work deals with the issue of developing the correct method of obtaining measurement data. The requirements of the acquisition parameters are clearly pointed out and examples of the medical applications of the described device are shown. Statistical analysis of acquired signals proving its usability is also presented. In the examples of selected diseases of the Upper Respiratory Tract (URT), the advantages of the developed apparatus for supporting the diagnosis of URT patency have been proven.


Assuntos
Síndromes da Apneia do Sono , Equipamentos para Diagnóstico , Humanos , Respiração , Software
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