Corona virus disease 2019 (COVID-19) is an acute respiratory infectious disease with strong contagiousness, strong variability, and long incubation period. The probability of misdiagnosis and missed diagnosis can be significantly decreased with the use of automatic segmentation of COVID-19 lesions based on computed tomography images, which helps doctors in rapid diagnosis and precise treatment. This paper introduced the level set generalized Dice loss function (LGDL) in conjunction with the level set segmentation method based on COVID-19 lesion segmentation network and proposed a dual-path COVID-19 lesion segmentation network (Dual-SAUNet++) to address the pain points such as the complex symptoms of COVID-19 and the blurred boundaries that are challenging to segment. LGDL is an adaptive weight joint loss obtained by combining the generalized Dice loss of the mask path and the mean square error of the level set path. On the test set, the model achieved Dice similarity coefficient of (87.81 ± 10.86)%, intersection over union of (79.20 ± 14.58)%, sensitivity of (94.18 ± 13.56)%, specificity of (99.83 ± 0.43)% and Hausdorff distance of 18.29 ± 31.48 mm. Studies indicated that Dual-SAUNet++ has a great anti-noise capability and it can segment multi-scale lesions while simultaneously focusing on their area and border information. The method proposed in this paper assists doctors in judging the severity of COVID-19 infection by accurately segmenting the lesion, and provides a reliable basis for subsequent clinical treatment.
Humans ; COVID-19/diagnostic imaging* ; Respiratory Rate ; Tomography, X-Ray Computed

To comprehensively evaluate the human body's respiratory, circular metabolism and other functions, and to diagnose lung disease, an accurate and reliable pulmonary function test (PFT) is developed. The system is divided into two parts:hardware and software. It realizes the collection of respiratory, pulse oxygen, carbon dioxide, oxygen and other signals, and draws flow-volume curve (FV curve), volume-time curve (VT curve), respiratory waveform, pulse wave, carbon dioxide and oxygen waveform in real time on the upper computer of the PFT system, and conducts signal processing and parameter calculation for each signal. The experimental results prove that the system is safe and reliable, it can accurately measure the basic functions of human body, and provide reliable parameters, and has good application prospects.
Humans ; Carbon Dioxide ; Respiratory Function Tests ; Oxygen ; Heart Rate

Breathing is of great significance in the monitoring of patients with obstructive sleep apnea hypopnea syndrome, perioperative monitoring and intensive care. In this study, a respiratory monitoring and verification system based on optical capacitance product pulse wave (PPG) is designed, which can synchronously collect human PPG signals. Through algorithm processing, the characteristic parameters of PPG signal are calculated, and the respiratory signal and respiratory frequency can be extracted in real time. In order to verify the accuracy of extracting respiratory signal and respiratory rate by the algorithm, the system adds the nasal airflow respiratory signal acquisition module to synchronously collect the nasal airflow respiratory signal as the standard signal for comparison and verification. Finally, the root mean square error between the respiratory rate extracted by the algorithm from the pulse wave and the standard respiratory rate is only 1.05 times/min.
Algorithms ; Electrocardiography ; Heart Rate ; Humans ; Photoplethysmography ; Respiration ; Respiratory Rate ; Signal Processing, Computer-Assisted ; Sleep Apnea, Obstructive

Peak expiratory flow (PEF) is a portable, reliable, and inexpensive method for lung function assessment. PEF can reflect expiratory airflow limitation and its variability can document reversibility, which provides an objective basis for the diagnosis of asthma in children. Short-term PEF monitoring can be an important aid in the management of acute asthma exacerbations, identification of possible triggers, and assessment of response to treatment. Long-term PEF monitoring can assist in the assessment of asthma control and warning of acute exacerbations, and this is useful for children with severe asthma. This article reviews the measurements, influencing factors, interpretation, and application of PEF, and its role in the diagnosis and management of asthma in children, to provide references for the clinical application of PEF in children.
Asthma/therapy* ; Child ; Humans ; Peak Expiratory Flow Rate ; Respiratory Function Tests

Oxygen saturation and respiratory signals are important physiological signals of human body, respiratory monitoring plays an important role in clinical and daily life. A system was established to extract respiratory signals from photoplethysmography in this study. Including the collection of pulse wave signal, the extraction of respiratory signal, and the calculation of respiratory rate and pulse rate transmitted from the slave computer to the host computer in real time.
Heart Rate ; Humans ; Monitoring, Physiologic ; Photoplethysmography ; Respiratory Rate ; Signal Processing, Computer-Assisted

Life monitoring technology as the basis of health evaluation, in recent years, its related technology research also has new development, in which cardiopulmonary parameters are the core physiological indicators to measure the basic state of vital signs, the analysis of its monitoring technology is particularly important. In this study, the main means of life monitoring are analyzed, and the monitoring technology of cardiopulmonary parameters is the main focus. What is more, the research status and development of contact and non-contact cardiopulmonary monitoring technology at home and abroad were also considered. Lastly, this study will be combined with the radar wave vital signs monitoring technology, which has been achieved good results in the field of cardiopulmonary monitoring, in order to provide a reference for the long-term development of life monitoring field and the technology integration of intelligent pension, intelligent automobile and other related industries.
Algorithms ; Heart Rate ; Monitoring, Physiologic ; Radar ; Respiratory Rate ; Technology ; Vital Signs

Traditional methods of non-contact human respiratory rate measurement usually require complex devices or algorithms. Aiming at this problem, a non-contact respiratory rate measurement method based on only the RGB video information was proposed in this paper. The method consisted of four steps. Firstly, spatial filtering was applied to each frame of the input video. Secondly, a gray compensation algorithm was used to compensate for the gray level change caused by the environmental light. Thirdly, the gray levels of each pixel over time were filtered separately by a low-pass filter. Finally, the region of interest was determined based on the filtering results, and the respiration rate of the human is measured. The physical measurement experiments were designed, and the measurement accuracy was compared with that of the biological radar. The error of the proposed method was between - 5.5% and 3% in different detection directions. The results show that the non-contact respiration rate measurement method can effectively measure the human respiration rate.
Algorithms ; Humans ; Radar ; Respiration ; Respiratory Rate

This paper designs a bluetooth-based low-power multi-parameter monitoring system. The system is mainly composed of ECG signal acquisition, respiratory signal acquisition, body temperature acquisition, bluetooth 4.0 transmission module and Android mobile phone APP display. The system collects the corresponding physiological signals through various collection parts, and can realize the monitoring of three physiological signals of electrocardiogram, respiration and body temperature. The Android mobile APP can display ECG, respiratory waveform and temperature data in real time. The system is small in size and low in power consumption, and has a good application prospect in portable and wearable medical applications.
Body Temperature ; Cell Phone ; Electrocardiography ; Humans ; Mobile Applications ; Monitoring, Physiologic/instrumentation* ; Respiratory Rate

OBJECTIVES: To develop a new Chinese medicine (CM)-based drug and to evaluate its safety and effect for suppressing acute respiratory distress syndrome (ARDS) in COVID-19 patients. METHODS: A putative ARDS-suppressing drug Keguan-1 was first developed and then evaluated by a randomized, controlled two-arm trial. The two arms of the trial consist of a control therapy (alpha interferon inhalation, 50 µg twice daily; and lopinavir/ritonavir, 400 and 100 mg twice daily, respectively) and a testing therapy (control therapy plus Keguan-1 19.4 g twice daily) by random number table at 1:1 ratio with 24 cases each group. After 2-week treatment, adverse events, time to fever resolution, ARDS development, and lung injury on newly diagnosed COVID-19 patients were assessed. RESULTS: An analysis of the data from the first 30 participants showed that the control arm and the testing arm did not exhibit any significant differences in terms of adverse events. Based on this result, the study was expanded to include a total of 48 participants (24 cases each arm). The results show that compared with the control arm, the testing arm exhibited a significant improvement in time to fever resolution (P=0.035), and a significant reduction in the development of ARDS (P=0.048). CONCLUSIONS Keguan-1-based integrative therapy was safe and superior to the standard therapy in suppressing the development of ARDS in COVID-19 patients. (Trial registration No. NCT04251871 at www.clinicaltrials.gov ).
Administration, Inhalation ; Adult ; China ; Coronavirus Infections ; diagnosis ; drug therapy ; mortality ; Dose-Response Relationship, Drug ; Drug Administration Schedule ; Drugs, Chinese Herbal ; administration & dosage ; Female ; Follow-Up Studies ; Humans ; Integrative Medicine ; Interferon-alpha ; administration & dosage ; Lopinavir ; administration & dosage ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnosis ; drug therapy ; mortality ; Risk Assessment ; Severe Acute Respiratory Syndrome ; diagnosis ; drug therapy ; mortality ; Severity of Illness Index ; Survival Rate

PURPOSE: This study was conducted to evaluate the effect of breast milk olfactory stimulation on physiological responses, oral feeding progression, and body weight in preterm infants. METHODS: A repeated measures design with nonequivalent control group was used. The participants were healthy, preterm infants born at a gestational age of 28~32 weeks; 12 in the experimental group and 16 in the control group. Data were collected prospectively in the experimental group, and retrospectively in the control group, by the same methods. Breast milk olfactory stimulation was provided 12 times over 15 days. The data were analyzed using the chi-square test, Mann-Whitney U test, Wilcoxon signed rank test and linear mixed models using SPSS 19. RESULTS: The gastric residual volume (GRV) of the experimental group was significantly less than that of the control group. The heart rate, oxygen saturation, respiration rate, transition time to oral feeding, and body weight were not significantly different between the two groups. CONCLUSION: These findings indicate that breast milk olfactory stimulation reduces GRV and improves digestive function in preterm infants without inducing distress.
Body Weight ; Breast ; Gastric Emptying ; Gestational Age ; Heart Rate ; Humans ; Infant, Newborn ; Infant, Premature ; Milk, Human ; Oxygen ; Prospective Studies ; Residual Volume ; Respiratory Rate ; Retrospective Studies ; Smell ; Vital Signs