人体下肢关节坐标系的一种简单定义方法

在对人体运动进行运动学或者动力学分析的时候,通常需要对各关节建立局部坐标系,而目前大部分人体关节坐标系定义方法都主要针对临床应用,需要具备专业的解剖学知识且可操作性差。本文首先描述了下肢的主要解剖学特征点,并通过这些特征点构建了髋关节、膝关节及踝关节坐标系,提出了定义人体关节坐标系的基本原则。通过利用运动捕捉系统对自愿者步态过程中的下肢运动轨迹进行采集,分析构建坐标系的特征点在运动过程中空间相对位置的不变性,说明了文章提出的下肢关节坐标系定义方法在一定范围内是合理的。     

一种简单的上肢关节坐标系定义方法

人体运动的运动学或者动力学分析通常需要对各关节建立局部坐标系,目前大部分人体关节坐标系定义方法基于临床应用,要求专业的解剖学知识,可操作性差.本文定义了上肢的主要解剖学特征点,通过这些特征点构建了肩关节、肘关节及腕关节坐标系,并详细阐述了直接采用肩锁关节点（AC）构建肩关节坐标系的方法和必要性.利用运动捕捉系统对自愿者步态过程中的上肢运动轨迹进行采集,通过分析坐标系特征点在运动过程中空间相对位置的不变性,说明了文章提出的上肢局部坐标系定义方法在一定范围内是合理的.     

Evolutionary Development of Neural Systems in Vertebrates and Beyond

Abstract

The emerging field of “neuro-evo-devo” is beginning to reveal how the molecular and neural substrates that underlie brain function are based on variations in evolutionarily ancient and conserved neurochemical and neural circuit themes. Comparative work across bilaterians is reviewed to highlight how early neural patterning specifies modularity of the embryonic brain, which lays a foundation on which manipulation of neurogenesis creates adjustments in brain size. Small variation within these developmental mechanisms contributes to the evolution of brain diversity. Comparing the specification and spatial distribution of neural phenotypes across bilaterians has also suggested some major brain evolution trends, although much more work on profiling neural connections with neurochemical specificity across a wide diversity of organisms is needed. These comparative approaches investigating the evolution of brain form and function hold great promise for facilitating a mechanistic understanding of how variation in brain morphology, neural phenotypes, and neural networks influences brain function and behavioral diversity across organisms.     

功能电刺激腕关节运动的自适应控制技术研究

针对功能电刺激(FES)康复技术中肌肉的时变和高度非线性的特点,提出一种实时调整FES系统输出,实现康复患者自适应训练的方法。考虑到患者间和康复各阶段肌肉对电刺激响应能力的差异,利用神经网络良好的非线性逼近能力,采用神经网络辨识器辨识相关运动肌肉的FES模型,并在此基础上,利用神经网络控制器在线调节控制策略及刺激参数,提高FES系统的自适应能力。通过人体腕关节运动控制的FES实验,验证该方法具有较高的轨迹跟踪控制精度和较强的自适应能力。     

Filmless in 60 Days: The Impact of Picture Archiving and Communications Systems Within a Large Urban Hospital

Many large urban hospitals converting to filmless radiography use a phased approach for digital imaging implementation. In fact, this strategy often is recommended by picture archival communication systems (PACS) experts and vendors alike for large, busy hospitals installing PACS in existing physical facilities. The concern is that comprehensive conversion from film-based to digital imaging may be too overwhelming an adjustment in operations for a medical staff to effectively handle without serious disruption of workflow for patient treatment and care. Elmhurst Hospital Center is a 543-bed hospital located in the Borough of Queens in New York City. Owned by the New York City Health and Hospitals Corporation, this municipal teaching hospital provides services to a patient mix that is 38% indigent with no insurance, 50% covered by Medicaid or Medicare, and 12% affiliated with HMOs. Most inpatients are admitted through the emergency department. Forty-five percent of all radiology procedures conducted are for emergency patients. Historically, up to 25% of all diagnostic imaging examinations were never reported formally by radiologists. Report turnaround time for the remaining 75% was unacceptable, with only 3% of all imaging examinations reported within a 12-hour period in 1996. Both situations existed in great part because physicians and residents who felt they needed access to films simply took them. Many were never located or returned days after they were taken. In 1998, Elmhurst Hospital Center replaced its RIS and added voice recognition dictation capabilities in January 1999. A hospitalwide PACS was deployed 10 months later. With the exception of mammography, the hospital converted to filmless radiography within 60 days. The critical objectives to maintain control of films and radically improve the reporting process were achieved immediately. Over 99% of all examinations now are formally reviewed and reported. Only 7% of all reports take 1 or more days to generate. This report describes Elmhurst Hospital's efforts to make improvements in the delivery of radiology services and the reasons attributed to its rapid conversion to becoming a filmless (mammography excluded) medical center. The impact of the PACS on radiology department operations and service is discussed.     

基于BP神经网络的旋转血泵生理控制

提出一种基于BP神经网络的旋转血泵生理控制方法,实现血泵植入者生理状态变化下控制器的自适应调节。控制器以临床主动脉平均压100 mmHg作为控制目标,利用神经网络自动学习的特性,采用3层神经网络在循环系统生理状态发生变化时在线调优血泵PID控制器的参数。该控制方法在血液循环系统数学模型中进行数值模拟验证,分别在模拟左心室衰竭、体循环阻力发生生理变化以及左心室收缩能力动态变化等条件下,接入改进后的PID控制器控制血泵转速,使循环系统中主动脉压力达到设定的正常值。结果表明,在上述多种不同的生理状态下,基于BP神经网络改进后的PID控制器均可以克服扰动,在经过约150 s调整时间后达到主动脉平均压100 mmHg的控制目标,并且稳态误差为零。该控制方法可以适应循环系统多种生理状态的变化,为后续的体外和动物试验提供有效的旋转血泵控制方法。     

暂时神经联系的计算机模拟:一个反映DNA-RNA-Pr系统作用的模型

本文介绍了一个能反映ＤＮＡ－ＲＮＡ－Ｐｒ系统作用的暂时神经联系的模型以及为配合模拟而进行的两项记忆行为的观察。利用该模型进行了视听记忆功能和经典条件反射的模拟。结果表明：基于神经生物学的模型有益于表达和进一步探索记忆、条件反射等脑的高级功能的机制。利用该模型，提出了海马参与触发有关ＤＮＡ－ＲＮＡ－Ｐｒ系统来维持长期记忆的必要组构的假说。     

Evaluation of Heart State Variation and Neural Control Parameters with Animal Models

INTRODUCTION　　 The cardiac electrical physiology contains abundantphysiological and pathologi-cal information and enables noninvasive detection.Butitis notenough for diagnos-ing heart diseases in clinic in the past.Common approaches for diagnosing early…     

随机模糊神经网络在DNA微注射量信息融合控制中的应用

气压电控式DNA微注射量单因素控制方案中存在准确性较差的问题。本研究提出了一种基于随机模糊神经网络的微注射量多信息融合的控制方案，实现了注射压力、注射时间，以及微注射针尖端径等多种参数的信息融合控制。实验结果表明，较之单因素控制方案，本法的控制精度得到较大改善，而且对于参数测量中存在的噪声污染由较强的抗干扰能力。     

Design and Control Optimization of Microclimate Liquid Cooling Systems Underneath Protective Clothing

The use of protective clothing, whether in space suits, hazardous waste disposal, or sporting equipment, generally increases the risk of heat stress and hyperthermia by impairing the capacity for evaporative heat exchange from the body to the environment. To date the most efficient method of microclimate cooling underneath protective clothing has been via conductive heat exchange from circulating cooling fluid next to the skin. In order to make the use of liquid microclimate cooling systems (_LQMCSs) as portable and practical as possible, the physiological and biomedical engineering design goals should be towards maximizing the efficiency of cooling to maintain thermal comfort/neutrality with the least cooling possible to minimize coolant and power requirements. Meeting these conditions is an extremely complex task that requires designing for a plethora of different factors. The optimal fitting of the _LQMCSs, along with placement and design of tubing and control of cooling, appear to be key avenues towards maximizing efficiency of heat exchange. We review the history and major design constraints of _LQMCSs, the basic principles of human thermoregulation underneath protective clothing, and explore potential areas of research into tubing/fabric technology, coolant distribution, and control optimization that may enhance the efficiency of _LQMCSs.     

Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs. Part I: Theory and Simulations

This paper presents a new modeling approach for neural systems with point-process (spike) inputs and outputs that utilizes Boolean operators (i.e. modulo 2 multiplication and addition that correspond to the logical AND and OR operations respectively, as well as the AND_NOT logical operation representing inhibitory effects). The form of the employed mathematical models is akin to a “Boolean-Volterra” model that contains the product terms of all relevant input lags in a hierarchical order, where terms of order higher than first represent nonlinear interactions among the various lagged values of each input point-process or among lagged values of various inputs (if multiple inputs exist) as they reflect on the output. The coefficients of this Boolean-Volterra model are also binary variables that indicate the presence or absence of the respective term in each specific model/system. Simulations are used to explore the properties of such models and the feasibility of their accurate estimation from short data-records in the presence of noise (i.e. spurious spikes). The results demonstrate the feasibility of obtaining reliable estimates of such models, with excitatory and inhibitory terms, in the presence of considerable noise (spurious spikes) in the outputs and/or the inputs in a computationally efficient manner. A pilot application of this approach to an actual neural system is presented in the companion paper (Part II).