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.
ObjectiveTo use failure mode and effect analysis (FMEA) to check and improve the risk of severe acute respiratory syndrome coronavirus 2 nucleic acid detection, and explore the application effect of FMEA in the emergency inspection items.MethodsFMEA was used to sort out the whole process of severe acute respiratory syndrome coronavirus 2 nucleic acid detection from January 30 to February 21, 2020. By establishing the theme, setting up a team, analyzing the failure mode and potential influencing factors. Then calculate the risk priority number (RPN), formulate preventive measures and implement continuous improvement according to the analysis results.ResultsA total of 2 138 cases were included. After improvement, the number of potential failure modes has been reduced by 2 (17 vs.19); the value of total RPN decreased (3 527.49 vs. 1 858.28). There was significant difference in average RPN before and after improvement [(185.66±74.34) vs. (97.80±37.97); t=6.128, P<0.001].ConclusionsIn the early stage of emergency inspection items, using FMEA can systematically check the risk factors in the process, develop improvement measures. It also can effectively reduce the risk of severe acute respiratory syndrome coronavirus 2 nucleic acid detection in hospital.
目的 探讨贵州地区进行宫颈癌机会性筛查的价值。 方法 回顾性分析2010年11月－2011年10月贵州省人民医院妇科门诊及住院进行宫颈癌机会性筛查的1 842例患者资料，筛查方法包括液基细胞学技术、宫颈刮片、人乳头瘤病毒（HPV）分型检测、HPV第2代捕获杂交法检测、阴道镜检查，以病理确诊宫颈癌前病变及宫颈癌。 结果 贵州地区女性人群的HPV平均感染率为21.87%。共检出宫颈癌前病变39例（2.12%），宫颈癌2例（0.11%）。 结论 医院内就诊女性宫颈病变检出率高，应高度重视其机会性筛查，有助于早期干预治疗。
Neurosyphilis is a group of clinical syndromes in which Treponema pallidum invades the nervous system and causes damage to the meninges, blood vessels, brain parenchyma or spinal cord. At present, there is no highly specific and sensitive method for the diagnosis of neurosyphilis, and its diagnosis mainly depends on clinical manifestations, abnormal cerebrospinal fluid and the comprehensive judgment of clinicians. Current studies show that some cytokines and chemokines are promising for laboratory detection of neurosyphilis. This article reviews the research progress of neurosyphilis from the aspects of traditional laboratory testing, polymerase chain reaction testing, cytokine and chemokine testing, and existing diagnostic criteria for neurosyphilis, in order to provide a reference for clinical testing and follow-up research.
目的:观察脑出血急性期血凝动态变化规律,为治疗提供理论依据。方法:检测36例脑出血患者病后第1天、第3天、第5天、第10天、凝固启动时间(CST)、凝固达峰值时间(MCT)、最大凝固程度(MCE)、凝血酶原(FⅡ)、纤维蛋白原(Fg)和44例健康体检者的相同指标。结果:与对照组比较,脑出血组病后第1天、第3天、第5天,第10天的MCE、Fg、FⅡ增高(Plt;0.05)。结论:脑出血病后10天血凝显著增高,提示脑出血患者急性期应慎用止血剂和清除脑血肿。
The number of white blood cells in the leucorrhea microscopic image can indicate the severity of vaginal inflammation. At present, the detection of white blood cells in leucorrhea mainly relies on manual microscopy by medical experts, which is time-consuming, expensive and error-prone. In recent years, some studies have proposed to implement intelligent detection of leucorrhea white blood cells based on deep learning technology. However, such methods usually require manual labeling of a large number of samples as training sets, and the labeling cost is high. Therefore, this study proposes the use of deep active learning algorithms to achieve intelligent detection of white blood cells in leucorrhea microscopic images. In the active learning framework, a small number of labeled samples were firstly used as the basic training set, and a faster region convolutional neural network (Faster R-CNN) training detection model was performed. Then the most valuable samples were automatically selected for manual annotation, and the training set and the corresponding detection model were iteratively updated, which made the performance of the model continue to increase. The experimental results show that the deep active learning technology can obtain higher detection accuracy under less manual labeling samples, and the average precision of white blood cell detection could reach 90.6%, which meets the requirements of clinical routine examination.
Ambulatory electrocardiogram (ECG) monitoring can effectively reduce the risk and death rate of patients with cardiovascular diseases (CVDs). The Body Sensor Network (BSN) based ECG monitoring is a new and efficient method to protect the CVDs patients. To meet the challenges of miniaturization, low power and high signal quality of the node, we proposed a novel 50 mm×50 mm×10 mm, 30 g wireless ECG node, which includes the single-chip analog front-end AD8232, ultra-low power microprocessor MSP430F1611 and Bluetooth module HM-11. The ECG signal quality is guaranteed by the on-line digital filtering. The difference threshold algorithm results in accuracy of R-wave detection and heart rate. Experiments were carried out to test the node and the results showed that the proposed node reached the design target, and it has great potential in application of wireless ECG monitoring.
In order to solve the saturation distortion phenomenon of R component in fingertip video image, this paper proposes an iterative threshold segmentation algorithm, which adaptively generates the region to be detected for the R component, and extracts the human pulse signal by calculating the gray mean value of the region to be detected. The original pulse signal has baseline drift and high frequency noise. Combining with the characteristics of pulse signal, a zero phase digital filter is designed to filter out noise interference. Fingertip video images are collected on different smartphones, and the region to be detected is extracted by the algorithm proposed in this paper. Considering that the fingertip’s pressure will be different during each measurement, this paper makes a comparative analysis of pulse signals extracted under different pressures. In order to verify the accuracy of the algorithm proposed in this paper in heart rate detection, a comparative experiment of heart rate detection was conducted. The results show that the algorithm proposed in this paper can accurately extract human heart rate information and has certain portability, which provides certain theoretical help for further development of physiological monitoring application on smartphone platform.
Objective To explore the clinical value of metagenomic next-generation sequencing (mNGS) in the diagnosis and treatment of severe and complex infection of malignant hematological disorder. Methods The mNGS test results, traditional etiology test results and general clinical data of inpatients with malignant hematological disorder in the Department of Hematology, the Affiliated Hospital of Southwest Medical University between June 2020 and February 2022 were retrospectively analyzed. To explore the clinical application value of mNGS in the diagnosis and treatment of severe complicated infection of hematological disorder. Results A total of 21 patients were included. The samples included 18 peripheral blood samples, 2 pleural fluid samples and 1 alveolar lavage fluid sample. In the included patients, through mNGS, pathogenic bacteria were directly detected in 17 patients, including 8 fungi, 9 bacteria and 10 viruses, of which 9 were mixed infections. The positive rate (81.0% vs. 33.3%, P=0.002), sensitivity (85.7% vs. 30.0%), granulocytopenia (9 vs. 3 cases, P=0.031) and the types of pathogen (Z=−3.416, P=0.001) detected by mNGS were all higher than those by traditional method. The infection control of 17 patients improved in varying degrees after adjusting the treatment plan according to the test results. ConclusionsmNGS has significantly higher detection rate and sensitivity for bacteria, fungi, viruses and mixed infections. Compared with the traditional method, mNGS has more efficient characteristics. Its clinical application can further improve the diagnosis and treatment efficiency of severe complicated infection of malignant hematological disorder, and thus improve the survival rate of patients.
Due to lack of the practical technique to measure the biomechanical properties of the ocular cornea in vivo, clinical ophthalmologists have some difficulties in understanding the deformation mechanism of the cornea under the action of physiological intraocular pressures. Using Young's theory analysis of the corneal deformation during applanation tonometry, the relation between the elasticity moduli of the cornea and the applanated corneal area and the measured and true intraocular pressures can be obtained. A new applanation technique has been developed for measuring the biomechanical properties of the ocular cornea tissue in vivo, which can simultaneously acquire the data of the applanation area and displacement of the corneal deformation as well as the exerted applanation force on the cornea. Experimental results on a rabbit's eyeball demonstrated that the present technique could be used to measure the elasticity moduli and creep properties of the ocular cornea nondestructively in vivo.