Neonatal acute respiratory distress syndrome (ARDS) is a clinical condition characterized by acute respiratory failure with refractory hypoxemia triggered by local or systemic etiologies during the neonatal period. Diagnosis primarily relies on the Montreux criteria. Oxygen index is recommended for grading index and lung ultrasound scoring is recommended for auxiliary diagnosis and treatment index. Current therapeutic strategies include high-frequency oscillatory ventilation, high-dose pulmonary surfactant administration, inhaled nitric oxide, intratracheal instillation of budesonide combined with surfactant, prone positioning, extracorporeal membrane oxygenation. Despite these interventions, targeted therapies remain limited. In particular, neonates with moderate or severe neonatal ARDS generally carry a poor prognosis, with mortality escalating in severe cases or those with systemic etiologies.

Neonatal acute respiratory distress syndrome (ARDS) is a clinical condition characterized by acute respiratory failure with refractory hypoxemia triggered by local or systemic etiologies during the neonatal period. Diagnosis primarily relies on the Montreux criteria. Oxygen index is recommended for grading index and lung ultrasound scoring is recommended for auxiliary diagnosis and treatment index. Current therapeutic strategies include high-frequency oscillatory ventilation, high-dose pulmonary surfactant administration, inhaled nitric oxide, intratracheal instillation of budesonide combined with surfactant, prone positioning, extracorporeal membrane oxygenation. Despite these interventions, targeted therapies remain limited. In particular, neonates with moderate or severe neonatal ARDS generally carry a poor prognosis, with mortality escalating in severe cases or those with systemic etiologies.

This paper is to provide a basis for the establishment of an early diagnostic system for hypoxic-ischemic encephalopathy (HIE) by performing segmentation and feature extraction of lesions on the MR images of neonatal babies with HIE. The segmentation on MR images of HIE based on the genetic algorithm (GA) combined with a pulse-coupled neural network (PCNN) were carried out. There were better segmentation results by using PCNN segmentation based on GA than PCNN segmentation with fixed parameters. The data suggested that a PCNN based on GA could provide effective assistance for diagnosis and research.
Algorithms ; Female ; Humans ; Hypoxia-Ischemia, Brain ; diagnosis ; physiopathology ; Image Processing, Computer-Assisted ; Infant, Newborn ; Magnetic Resonance Imaging ; methods ; Male ; Neural Networks (Computer)

This paper is aimed to study a method and feasibility of early diagnostic system using hypoxic ischemic encephalopathy (HIE) in the newborns. Fifteen non-invasive indicators with high sensitivity and specificity were selected for the early diagnosis of HIE on the basis of related researches from the literature and the researches in our laboratory. The diagnostic test was done with 140 cases with the HIE, using the fussy BP neural network experiment system. The initial results showed that the accuracy rate was 100% for the training set and 95% for the testing set, and the error rate was 5%. The data suggested that the fuzzy back-propagation neural networks, with the clinical comprehensive indicators, exhibited a high accuracy for the early diagnosis of HIE. This method provides an objective and convenient new way for the early clinical diagnosis of the HIE.
Algorithms ; Diagnosis, Computer-Assisted ; methods ; Early Diagnosis ; Female ; Fuzzy Logic ; Humans ; Hypoxia-Ischemia, Brain ; diagnosis ; Infant, Newborn ; Male ; Neural Networks (Computer) ; Pattern Recognition, Automated ; methods ; Reproducibility of Results ; Sensitivity and Specificity

This paper explores the use of multi-channel event-related potentials (ERP) to identify mentality facticity or detect lie. Some identifiably meaning information, such as subjects' name and birthday, were selected as concealed information to be identified, 15 subjects were tested by concealed information test (CIT) paradigm and their electroencephalographs (EEG) were recorded from 30 electrodes. In virtue of analysis on the statistically significant difference between multi-channel ERPs evoked by probe information and that evoked by irrelevant information, the P300 amplitudes of 15 electrodes were selected as F-test samples. The significant difference of feature sample values between probe and irrelevant information was applied to identify mentality facticity. The results indicate that P300 amplitudes evoked in many electrodes are significantly different between probe and irrelevant information (P < 0.01). According to the significant difference of space sample values between probe and irrelevant information, the detection correctness to probe information reaches to 93.3% and is better than that of methods based single-channel ERP. The method proposed has the advantages of non-invasion and better accuracy, which could be used to identify mentality facticity effectively.
Adult ; Electroencephalography ; methods ; Event-Related Potentials, P300 ; physiology ; Female ; Humans ; Lie Detection ; psychology ; Male ; Neuropsychological Tests ; Young Adult

The aim of this experiment is to find a feasible impersonal index for analyzing the physiological mental fatigue level. Three characteristic parameters, relative power in different rhythm, barycenter frequency and power spectral entropy, are extracted from two channels' electroencephalogram (EEG) under two physiological mental fatigue states. Then relationships between such three parameters and physiological mental fatigue are analyzed to explore whether they can be of use for detecting (or monitoring) the mental fatigue level. The experiment results show that the relative power, barycenter frequency and power spectral entropy of EEG exhibit strong correlation with physiological mental fatigue level. While physiological mental fatigue level increases, the relative power in theta, alpha and beta rhythms, barycenter frequency and power spectral entropy of EEG decrease, but the relative power in delta rhythm of EEG increases. The relative power in four rhythms, barycenter frequency and power spectral entropy of EEG reflect the change of physiological mental fatigue level sensitively, and may hopefully be used as indexes for detecting physiological mental fatigue level.
Adult ; Electroencephalography ; Entropy ; Humans ; Male ; Mental Fatigue ; physiopathology ; Signal Processing, Computer-Assisted ; Young Adult

Water-fat separation is a particularly important problem for magnetic resonance imaging. Although many methods have been proposed, the reliability is still challenging. In this work, we have presented a method based on the combination of the branch-cut method and multigrid algorithm to get a more robust performance of water-fat separation. First, the branch-cut method is applied to identify residues, which violates the requirement that the interacting phase gradient around a closed path be zero. Residues and branches are marked to be zeros and filled to the weighting factor array. Then, the unwrapped phase array can be given by the multigrid algorithm. Finally, the Dixon method for water-fat separation is applied to the unwrapped phase array. Experiments for brain scanning on the 0.3T low field MRI system demonstrate the successful application of the proposed method.

This study was conducted to evaluate the applicability of 99mTc-2beta-[ N, N'-bis (2-mercaptoethyl) ethylenediamino]methyl,3beta(4-chlorophenyl)tropane(TRODAT-1) dopamine transporter(DAT) SPECT imaging in children with autism, and thus to provide an academic basis for the etiology, mechanism and clinical therapy of autism. Ten autistic children and ten healthy controls were examined with 99mTc-TRODAT-1 DAT SPECT imaging. Striatal specific uptake of 99mTc-TRODAT-1 was calculated with region of interest analysis according to the ratics between striatum and cerebellum [(STR-BKG)/BKG]. There was no statistically significant difference in semiquantitative dopamine transporter between the bilateral striata of autistic children (P=0.562), and between those of normal controls (p=0.573); Dopamine transporter in the brain of patients with autism increased significantly as compared with that in the brain of normal controls (P=0.017). Dopaminergic nervous system is dysfunctioning in the brain of children with autism, and DAT 99mTc-TRODAT-1 SPECT imaging on the brain will help the imaging diagnosis of childhcod autism.
Autistic Disorder ; diagnostic imaging ; metabolism ; Brain ; diagnostic imaging ; metabolism ; Child ; Child, Preschool ; Dopamine Plasma Membrane Transport Proteins ; metabolism ; Humans ; Male ; Organotechnetium Compounds ; Tomography, Emission-Computed, Single-Photon ; Tropanes

The event-related desynchronization/synchronization(ERD/ERS) time courses of lower and upper alpha band rhythms during hand motor imagery are investigated respectively by Fourier Sectral Entropy (FSE) in this paper. By analyzing one group of BCI competition data, it was found that FSE within upper alpha band displays a pronounced increase and decrease over contralateral and ipsilaterai brain areas respectively at the onset of hand motor imagery, which is corresponding to the antagonistic ERD/ERS patterns in previous studies. Different from the upper alpha activity pattern, FSE within lower alpha band displays a consistent increase over both two hemispheres hand representative areas. The preliminary results show that FSE could disclose the different behaviors of the upper and lower alpha band rhythms so that a new idea with the complexity measure is provided to characterize functional dissociation of lower and upper frequency alpha rhythms in relation to hand motor imagery.

Mental task classification is one of the most important problems in Brain-computer interface. This paper studies the classification of five-class mental tasks. The nonlinear parameter of mean period obtained from frequency domain information was used as features for classification implemented by using the method of SVM (support vector machines). The averaged classification accuracy of 85.6% over 7 subjects was achieved for 2-second EEG segments. And the results for EEG segments of 0.5s and 5.0s compared favorably to those of Garrett's. The results indicate that the parameter of mean period represents mental tasks well for classification. Furthermore, the method of mean period is less computationally demanding, which indicates its potential use for online BCI systems.