ObjectiveWith the wide use of transmission displays to improve operation performance, the display information highlights clutter because of the contradiction between the massive amount of information and limited display area. Our study aimed to develop a quantitative measurement for declutter design and appraisal. MethodsUsing the ergonomics research system of characters and symbols in a see-through cockpit display, we set the simulated flight task interface at four pixel scale levels by enlarging all the display elements in a certain ratio. Flight task videos of 12 clutter degrees were recorded using each flight interface matched with three flight scene complexity levels. A total of 60 pilots completed the visual search tasks in the flight task video while the eye tracker was used to record the view path in real time. Visual search performance was analyzed to study the effect of various clutter factors and levels on pilots' performance in visual search tasks, and acquire quantitative clutter measure parameters. ResultsGLM univariate test revealed that there were significant differences among the fixation time in areas of interest (AOI), total Fixation point number, total fixation time at four pixel scale levels, and three flight scene complexity levels (P < 0.05). Visual search performance declined after the cutoff point, while the clutter degree increased. According to the visual search performance data, the recommend feature congestion upper pixel number limit in a 600*800 display was 18,576, and the pixel ratio was 3.87%. ConclusionA quantitative measurement for declutter design and appraisal of cockpit displays was developed, which can be used to support see-through display design.

This work proposes a spherical-orthogonal-symmetric Haar wavelet to decompose and reconstruct spherical iris signals to obtain stronger geometric features of iris surface. It compares its feature extraction abilities of spherical harmonics, semi-orthogonal and nearly orthogonal spherical Haar wavelet. The developed spherical-orthogonal-symmetric Haar wavelet with a convolutional neural network is also proposed for drivers’ iris recognition. It can effectively capture the local fine features of iris spherical surface, and has stronger ability of iris recognition than semi-orthogonal or nearly orthogonal spherical Haar wavelet bases.

聚焦超声(FUS)作为一种新兴的平台性无创治疗技术,是祛邪不伤正的、顺应健康医学模式理念的典型代表医学技术,为外科手术、放射治疗、药物输送和癌症免疫治疗等医疗手段提供了一种颠覆性的、改变"游戏规则"的替代或补充,可以通过改变治疗一系列适应证的作用方法,提高患者的生活质量和寿命,并降低医疗护理成本.截止2021年底,已有159种采用FUS治疗的临床适应证或疾患处于不同的研发阶段,包括基础研究、动物试验、临床前试验、临床试验和临床应用.简述在以系统论思想为基础的健康医学模式指导下的FUS治疗技术的作用机理、发展历程、最新动态和市场前景,旨在推进这项具有改善千百万罹患各种严重疾病患者生活质量巨大潜力的革命性治疗技术早日造福人类.

This study aims to investigates the impact of outside scenery on the color coding of aircraft perspective visual displays and suggests a recommended palette of colors and coding techniques. Method A total of 62 male pilot complete visual search task based on different color-coding schemes of real flight images of see-through display. The performance was recorded by eye tracker. Results The ANOVA showed that the main effects of the four indicators of different number colors groups were significant for the other three indicators except for the number of intra-AOI look backs, (FRetrospectives Number in AOI (4,1989) = 20.89, FNumber of fixation points (4,1989) = 22.16, FTotal fixation time(4,1989) = 22.55, P < 0.01). There were no statistical differences among three four-color-coding groups (P > 0.05). Conclusion No more than four colors should be used when using multiple colors for information encoding; aside from green, blue has the worst smearing when several colors appear in the same screen.

This work designs an adversarial Bayesian deep network to solve the cognitive detection of pilot fatigue. Batch normalization and data enhancement are adopted in the posterior inference of the proposed model parameters to effectively improve the generalization of neural networks. The generator is used to enhance the brain power map generated from three cognitive indicators and improve the accuracy of fatigue state recognition. This work also adds adversarial noise in the vicinity of each brain electrode to form an adversarial image, which further reveals the correlation between the cognitive state of brain and the location of brain regions. Compared with other deep models and parameter optimization methods, our model achieves better detection accuracy.

目的 基于可视化血压测量中动态柯氏音趋势(DKT)图数据分析心血管功能状态与寻常型银屑病(PV)的相关性.方法 选取2021年7月14日-8月31日于空军特色医学中心皮肤科门诊就诊和病房住院的52例PV患者(设为PV组),另选取2021年8月2日-8月31日于空军特色医学中心健康体检中心体检的51名健康者作为健康对照组,进行血常规检测及可视化血压测量.收集并比较两组一般资料、血压相关指标以及系统性炎症指标中性粒细胞/淋巴细胞比值(NLR)和血小板/淋巴细胞比值(PLR);采用Pearson检验分析PV患者各血压指标与临床因素之间的关系,单因素和多因素logistic回归分析PV发病的影响因素,受试者工作特征(ROC)曲线分析各因素对PV发病的预测价值及临界值.结果 对干扰因素进行校正后,与健康对照组比较,PV患者的外周血PLR、NLR以及心脏射血能力(收缩压、K-D)、外周小动脉阻力(舒张压、平均压)、血管硬化程度(K-A)明显升高(P<0.05),主动脉和大动脉血管弹性(脉压差)以及自主神经对血压稳定性的控制能力(DKT图形态)明显下降(P<0.05).多因素logistic回归分析显示,体重指数、PLR、收缩压、DKT图形态为PV发病的独立危险因素(OR=1.270、1.014、1.078、6.084,P<0.05).ROC曲线分析显示,收缩压(AUC=0.798,P<0.001)、平均压(AUC=0.748,P<0.001)、脉压差(AUC=0.719,P=0.001)、舒张压(AUC=0.696,P=0.002)、NLR(AUC=0.718,P=0.001)、PLR(AUC=0.716,P=0.001)、K-D(AUC=0.637,P=0.030)、DKT图形态(AUC=0.638,P=0.029)为PV发病的预测指标,其临界值分别为109 mmHg、86 mmHg、35 mmHg、86 mmHg、1.3、97、68、形态2.结论 基于DKT图数据,PV患者心血管功能存在异常,且与PV的发生及严重程度相关.心血管功能异常以及系统性炎症指标NLR和PLR对PV的发生具有预测意义.

This article presents a new aviation brain-computer interface, which includes the construction of a color brain power map and a cognitive detection network. The developed network, Bpmnet, can effectively detect the cognitive state of the brain. To improve the effectiveness of model parameter optimization algorithms, momentum and batch normalization are proposed during Bayesian posterior parameter inference. Bpmnet reduces the risk of model overfitting and increases the uncertainty of outlier prediction. Experimental results demonstrate that our approach significantly outperforms state-of-the-art techniques.

为实现睡眠分期,为穿戴式生理参数监测技术在慢病监测领域的应用提供技术支撑,发展基于心率变异性和支持向量机模型的睡眠分期算法.从心率时间间期序列中提取时域、频域和非线性等86个特征,将多导睡眠图仪的三分类结果(醒、快速眼动期、非快速眼动期)作为“金标准”,采用支持向量机作为多分类器模型;为保证训练集数据质量,使用开放睡眠数据库SHHS中由专家确认挑选的67例PSG样本作为训练集,实现特征筛选和模型参数训练.为验证模型的泛化性能,从SHHS数据库中进一步随机提取939例PSG样本,对模型性能进行测试.睡眠分期模型在训练集上的五折交叉验证的准确率为84.00％±1.33％,卡帕系数为0.70±0.03;在939例测试集上的准确率为76.10％±10.80％,卡帕系数为0.57±0.15.剔除RR间期异常(110例)和明显睡眠结构异常(29例)的样本后,测试集(800例)的准确率为82.00％±5.60％,卡帕系数为0.67±0.14.所提出的基于心率变异性分析的睡眠分期算法具有较高的准确性,大样本人群测试结果表明,该模型具有较好的普适性.

面对日益蔓延的生活方式疾病,我国政府启动了主动健康科技专项,探索制定遏制慢性疾病不断恶化的中国方案.研究通过梳理现代医学模式发展脉络,面向即将到来的新科技革命,总结其学科特点,尝试给出主动健康的定义.主动健康是依照复杂性科学理论,人体可在远离平衡态形成自组织行为,通过主动对人体施加可控的刺激增加人体复杂性,从而达到健康干预的目的.研究认为,主动健康作为未来医学发展的重要方向,将会形成与现代疾病医学相互协同发展的新模式.同时,尽管运动科学是主动健康的重要组成部分,然而,面对主动健康医学的要求和未来科技发展的趋势,运动科学需要基于复杂系统、大数据和AI技术进行基础理论创新.

To achieve continuously physiological monitoring on hospital inpatients, a ubiquitous and wearable physiological monitoring system SensEcho was developed. The whole system consists of three parts: a wearable physiological monitoring unit, a wireless network and communication unit and a central monitoring system. The wearable physiological monitoring unit is an elastic shirt with respiratory inductive plethysmography sensor and textile electrocardiogram (ECG) electrodes embedded in, to collect physiological signals of ECG, respiration and posture/activity continuously and ubiquitously. The wireless network and communication unit is based on WiFi networking technology to transmit data from each physiological monitoring unit to the central monitoring system. A protocol of multiple data re-transmission and data integrity verification was implemented to reduce packet dropouts during the wireless communication. The central monitoring system displays data collected by the wearable system from each inpatient and monitors the status of each patient. An architecture of data server and algorithm server was established, supporting further data mining and analysis for big medical data. The performance of the whole system was validated. Three kinds of tests were conducted: validation of physiological monitoring algorithms, reliability of the monitoring system on volunteers, and reliability of data transmission. The results show that the whole system can achieve good performance in both physiological monitoring and wireless data transmission. The application of this system in clinical settings has the potential to establish a new model for individualized hospital inpatients monitoring, and provide more precision medicine to the patients with information derived from the continuously collected physiological parameters.

Pulmonary rehabilitation has been demonstrated as a highly effective and safe treatment for improving health-related quality of life and reducing hospital admissions mortality in chronic obstructive pulmonary disease (COPD) patients. Despite significant progress within the physiological monitoring device industry, the widespread integration of wearable systems into medical practice remains limited. In this paper, we present a medical-grade wearable multi-sensor system to acquire COPD patients' vital signs and assist in pulmonary respiratory rehabilitation. Currently, 4 areas in this field were explored: breathing pattern analysis, respiratory exercises training, six minute walk test and inpatient 24-hours physiological monitoring. Totally 130 subjects enrolled in this study. The results show that this system can acquire cardiopulmonary physiological signals unobtrusively and accurately, and provide useful information for pulmonary respiratory rehabilitation. The next step for this work is to collect more physiological data from COPD patients during respiratory training exercises and generate individualized guideline and therapy for pulmonary respiratory rehabilitation.

It is important to identify OSA events accurately for estimating the severity of OSA. Polysomnography examination was complex and not friendly for sleep. This paper proposed a novel method to identify OSA events. Three-channel mandible sEMG and breathing waveform were recorded simultaneously, and Fast ICA algorithm was applied for decomposing the sEMG signals into three independent components, then to determinate the independent component which has maximum Pearson correlation coefficient with breathing waveform as genioglossus muscle EMG. When the genioglossus muscle EMG value drops to 10% of the maximum value of the individual's maximum respiratory effort for more than 10 s, it is considered that an OSA event occurs once. Twenty-one OSA patients participated a controlled experiment, which demonstrates that there is no significant difference between the proposed method and Polysomnography examination (P = 0.1726). The proposed method to identify OSA events via mandible sEMG and breathing waveform was proved to be effective non-invasive, and more patient-friendly.

人的一生大约有1/3的时间处于睡眠当中.睡眠不是一个简单的静息过程,而是生命活动所必需的重要环节,决定着另外2/3生命的质量和精彩,因此对睡眠进行监测也是一个广受关注的领域.提起睡眠监测,很多人都会联想到各种精密的仪器和复杂的连线,但空军航空医学研究所的研究团队通过不干扰自然睡眠的压力敏感床垫式睡眠监测技术告诉我们,利用床垫也可以进行高精度、无干扰的自然睡眠监测.

目的:对多参数监护中保存的病人数据进行挖掘分析,获得病人的睡眠呼吸事件信息.方法:利用多参数监护中保存的心电、血氧、呼吸等生理信号,结合多信息融合分析技术和专家知识获取病人的睡眠分期和呼吸事件信息.结果:成功从监护数据中提取出关键生理信号,分析出睡眠分期和呼吸事件,并初步应用于临床.结论:利用多参数监护数据,可以提取出睡眠相关信息,该功能对全面了解和掌握病人健康状况具有重要意义,可以成为多参数监护的一项重要的扩展功能.

目的:设计一种实用的算法,能够自动识别长时间记录心电图中的伪差波形,达到用户快速剔除干扰的目的.方法:通过分析伪差发生的原因和实际呈现形态,总结出各类伪差波形有别于正常波形的特征,设计合适的算法.结果:从大量实测心电图中,总结了伪差波形的形态,对于饱和、微小、剧烈波动、趋势漂移等伪差形态,设计了具有针对性的识别算法,并用实测信号验证了算法的有效性.结论:该伪差识别算法在24小时心电HOLTER信号分析软件中得到应用,能够比较准确地自动筛查出信号中的大量伪差,为用户快速分析心电图提供了新的有效方法.

This study aimed to employ the recently developed fuzzy measure entropy (FuzzyMEn) method to compare the difference in heart rate variability (HRV) between rest and exercise states in hypoxic environment. Four healthy male volunteers were enrolled in this study. For each subject, electrocardiography (ECG) and finger pulse were recorded in ten days to obtain the heart rate (HR) time series. For each day, the measurement lasted 150 min and was divided into six consecutive experimental sections: 3 repeat rest sections (each 30 min) and 3 repeat exercise sections (each 20 min). The repeat rest and repeat exercise sections were in turn. In each rest or exercise section, the segment of HR time series from the second 5 min episode (from the 6th min to the 10th min) was selected for the FuzzyMEn calculation. The effects of subject, day, repeat measurement and state (rest or exercise) on the FuzzyMEn were investigated. The mean FuzzyMEn differences among ten days and between rest and exercise states were also analyzed. Results showed that day and state factors have significant effects on FuzzyMEn (both P

We designed two types of pre-adaption plans for this study. One was a pre-adaption training with progressive intermittent hypoxia, with a constant lower pressure oxygen tank used in the plain before arriving at the plateau (PG). The other was by progressively increasing the time of exposure to hypoxia with oxygen supplied in stages after radical plateau (RG). By testing the blood oxygen saturation (SpO2), heart rate (HR), and quality of sleep after arriving at the 3800 m high plateau, results showed that the pre-acclimatization and radical groups performed better than the control group (CG). Both strategies were equivalent in terms of effects and principles in providing more flexible choices for acclimatization.

Multi-scale entropy was introduced to analyze the blood oxygen sequence under hypoxic environment. Compared with mean analytical method, blood oxygen sequence analysis based on multi-scale entropy can reflect the dynamic adjustment mechanism of body hypoxia better. Multi-scale entropy, which is different from sample entropy that just estimates the difference between sequence lengthm andm+1 on the smallest scale and ignores other scales, calculates sample entropy of time series on multiple scales and relfects the irregular degree of time series on scales. The result shows that blood oxygen sequence analysis based on multi-scale entropy can identify human hypoxia endurance. This method is a reliable analytical method for studying the mechanism of hypoxic regulation of human body. The result also shows that repeated hypoxic stimulation will produce acclimatization effects on the human body which shows memory of hypoxia environment.

“做一名当代的好医生”是当前医疗战线上的一个重要课题，对于医疗改革和解决医患矛盾，尤其针对年轻医生有着重要的指导意义［1］。故将近年来我们学习钱学森先生的“系统论”，并在临床工作中实践“健康医学模式”调治心身性皮肤病的体会总结成文，供有识之士参考和研讨。