As one of the standard electrophysiological signals in the human body, the photoplethysmography contains detailed information about the blood microcirculation and has been commonly used in various medical scenarios, where the accurate detection of the pulse waveform and quantification of its morphological characteristics are essential steps. In this paper, a modular pulse wave preprocessing and analysis system is developed based on the principles of design patterns. The system designs each part of the preprocessing and analysis process as independent functional modules to be compatible and reusable. In addition, the detection process of the pulse waveform is improved, and a new waveform detection algorithm composed of screening-checking-deciding is proposed. It is verified that the algorithm has a practical design for each module, high accuracy of waveform recognition and high anti-interference capability. The modular pulse wave preprocessing and analysis software system developed in this paper can meet the individual preprocessing requirements for various pulse wave application studies under different platforms. The proposed novel algorithm with high accuracy also provides a new idea for the pulse wave analysis process.
In order to solve imperfection of heart rate extraction by method of traditional ballistocardiogram (BCG), this paper proposes an improved method for detecting heart rate by BCG. First, weak cardiac activity signals are acquired in real time by embedded sensors. Local BCG beats are obtained by signal filtering and signal conversion. Second, the heart rate is estimated directly from the BCG beat without the use of a heartbeat template. Compared with other methods, the proposed method has strong advantages in heart rate data accuracy and anti-interference, and it also realizes non-contact online detection. Finally, by analyzing the data of more than 20,000 heart rates of 13 subjects, the average beat error was 0.86% and the coverage was 96.71%. It provides a new way to estimate heart rate for hospital clinical and home care.
Objective To explore the methods of early diagnosis of arteriosclerosis obliterans of lower extremity (ASOLE). Methods The related literatures on ASOLE detection means adopted clinically were reviewed, and their advantages and disadvantages were compared.Results Asymptomatic ASOLE could be discovered by determination of ankle brachial index (ABI) and toe brachial index (TBI), which was a good index for arterial function assessment of lower extremity. Pulse wave velocity (PWV) was more vulnerable and less sensitive than ABI, and therefore more suitable for screening of a large sample. ASI was an index to assess arterial structure and function, and it had a good correlation with PWV. Flow-mediated dilation (FMD) was a measurement evaluating the function of endothelial cell; Pulse wave measurement was simple, sensitive, and its result was reliable. Color Doppler ultrasonography could localizate the lesion and determine the degree of stenosis at the same time. Multiple-slice CT angiography (MSCTA) was more accurate than color Doppler ultrasonography, but its inherent shortcomings, such as nephrotoxicity of contrast agent, was still need to be resolved. 3D-contrast enhancement magnetic resonance angiography (CEMRA) had little nephrotoxicity, but a combination of other imaging methods was necessary. Microcirculation detections required high consistency of the measurement environment, but they were simple, sensitive and noninvasive, and therefore could be used for screening of ASO. Conclusion Publicity and education of highrisk groups, and reasonable selection of all kinds of detection means, are helpful to improve the early diagnosis of ASOLE.
Fatigue driving is one of the leading causes of traffic accidents, posing a significant threat to drivers and road safety. Most existing methods focus on studying whole-brain multi-channel electroencephalogram (EEG) signals, which involve a large number of channels, complex data processing, and cumbersome wearable devices. To address this issue, this paper proposes a fatigue detection method based on frontal EEG signals and constructs a fatigue driving detection model using an asymptotic hierarchical fusion network. The model employed a hierarchical fusion strategy, integrating an attention mechanism module into the multi-level convolutional module. By utilizing both cross-attention and self-attention mechanisms, it effectively fused the hierarchical semantic features of power spectral density (PSD) and differential entropy (DE), enhancing the learning of feature dependencies and interactions. Experimental validation was conducted on the public SEED-VIG dataset. The proposed model achieved an accuracy of 89.80% using only four frontal EEG channels. Comparative experiments with existing methods demonstrate that the proposed model achieves high accuracy and superior practicality, providing valuable technical support for fatigue driving monitoring and prevention.
Amanitin-containing mushroom poisoning is one of the most harmful and lethal types of mushroom poisoning events. Its basic medical and clinical medical knowledge has not been fully understood and mastered, so the basic and clinical diagnosis and treatment of amanitin-containing mushroom poisoning has always been a hot research field of acute mushroom poisoning. This article focuses on the new progress in the epidemiology, toxicological properties, poisoning mechanism, clinical diagnosis and treatment of amanitin-containing mushroom poisoning, in order to provide the basis for further study, diagnosis and treatment of amanitin-containing mushroom poisoning for basic researchers and clinical medical staff.
The method for detecting the negative terms in Chinese electronic medical record (EMR) is useful in providing evidence for constructing concept index. In this respect, we adopted an improved method which combined maximum matching with mutual information in order to extract terms in EMRs. This method can overcome the influence of overlay ambiguity. In addition, for the determination of negative semantic, we also adopted an improved method which combined rule-based method with word co-occurrence. This new method can reduce the probability of appearance of false positive terms caused by punctuation input errors. The result showed that the negative predictive value is 7.85% higher than the rule-based method.
Objective To explore the application of two methods of direct fecal detection ofClostridium difficilein patients with recurrent inflammatory bowel disease (IBD), including nucleic acid amplification test (NAAT) and enzyme immunoassay (EIA), in order to provide support for hospitals to prevent and control clostridium difficile infection (CDI). Methods Fresh feces of 48 patients with recurrent IBD treated between November 2014 and April 2015 were collected within 48 hours after admission. Anaerobic culture and identification, NAAT and EIA were used to test the same samples. Statistical analysis was performed using Kappa test. Results Among the 48 fecal samples,Clostridium difficilewas negative in 37 and positive in 11 including 2 (4.2%) with toxigenicClostridium difficile characterized as toxin type A+B+. Compared with anaerobic culture and identification, NAAT had a perfect correlation (Kappa=1.00,P<0.05), and EIA had an almost perfect correlation (Kappa=0.89,P<0.05). But EIA toxin test had missed detection of toxigenic samples. Conclusions For patients with recurrent IBD combined with CDI, both NAAT and EIA test may be applied to detctClostridium difficile in feces directly, while NAAT may show a better performance. Samples from highly suspected patients with negative toxin result tested by EIA should be confirmed by other methods such as NAAT.
Based on the capacitance coupling principle, we studied a capacitive way of non-contact electrocardiogram (ECG) monitoring, making it possible to obtain ECG on the condition that a patient is habilimented. Conductive fabric with a good electrical conductivity was used as electrodes. The electrodes fixed on a bed sheet is presented in this paper. A capacitance comes into being as long as the body gets close to the surface of electrode, sandwiching the cotton cushion, which acts as dielectric. The surface potential generated by heart is coupled to electrodes through the capacitance. After being processed, the signal is suitable for monitoring. The test results show that 93.5% of R wave could be detected for 9 volunteers and ECG with good signal quality could be acquired for 2 burnt patients. Non-contact ECG is harmless to skin, and it has advantages for those patients to whom stickup electrodes are not suitable. On the other hand, it is convenient to use and good for permanent monitoring.
The detection of electrocardiogram (ECG) characteristic wave is the basis of cardiovascular disease analysis and heart rate variability analysis. In order to solve the problems of low detection accuracy and poor real-time performance of ECG signal in the state of motion, this paper proposes a detection algorithm based on segmentation energy and stationary wavelet transform (SWT). Firstly, the energy of ECG signal is calculated by segmenting, and the energy candidate peak is obtained after moving average to detect QRS complex. Secondly, the QRS amplitude is set to zero and the fifth component of SWT is used to locate P wave and T wave. The experimental results show that compared with other algorithms, the algorithm in this paper has high accuracy in detecting QRS complex in different motion states. It only takes 0.22 s to detect QSR complex of a 30-minute ECG record, and the real-time performance is improved obviously. On the basis of QRS complex detection, the accuracy of P wave and T wave detection is higher than 95%. The results show that this method can improve the efficiency of ECG signal detection, and provide a new method for real-time ECG signal classification and cardiovascular disease diagnosis.
ObjectiveTo suggest the importance of taking notice of oral chemotherapy drugs in cancer patients, and the importance of drug-use evaluation in patients with insufficient kidney functions, by reporting one death case caused by multiple organ failure because of myelosuppression after oral tegafur, gimeracil and oteracil potassium (S-1) capsules for 10 days in a patient with insufficient kidney functions. MethodsThrough the analysis of one patient who died of multiple organ failure due to degree-Ⅳ myelosuppression and the related literature review, we discussed the necessity of individualized administration of clinical chemotherapy. ResultsThe patient had grade-Ⅱ renal insufficiency before chemotherapy and did not undergo dihydropyrimidine dehydrogenase (DPYD) gene test. Myelosuppression occurred 10 days after oral chemotherapy drugs. The white blood cells, neutrophils and platelets decreased progressively, and then developed into degree-Ⅳ suppression. Finally the patient died of multiple organ failure. Conclusions Genetic variation and renal insufficiency may cause differences in drug metabolism. The reduced urinary excretion of guimet pyrimidine (CDHP), the inhibitors of dihydropyrimidine dehydrogenase which is the 5-fluorouracil (5-FU) metabolic enzyme, may lead to elevated plasma concentration of 5-FU, thereby increasing myelosuppression and other adverse reactions. If DPYD gene detection results show low enzyme activity, it can cause lethal toxicity through deceleration of 5-FU metabolism and high concentration of blood. DPYD gene dzetection should be performed if allowed, and individualized treatment plan should be formulated after comprehensive evaluation. The overall situation of the patients should be considered before treatment, and then individualized drugs should be administered.