基于ARM的多生理参数嵌入式监护系统

采用ARM9为硬件平台的主控制模块,构建了嵌入式Linux主控系统,并编写了相应的硬件驱动程序,在主控系统上开发了嵌入式多生理参数监护软件。利用系统的硬件接口与底层生理参数监护模块的硬件进行数据通信,并实现对底层设备的实时监控,从而达到监护的目的。     

基于WSN 的医院病人实时监护系统

随着物联网技术的发展和广泛应用,智慧医疗已逐渐被人们接受和期待,基于WSN（无线传感网络）技术构建一个医院病人实时监护系统,完成了主要的硬件电路设计和软件构架,并给出了相关的算法,能实现医护人员实时掌握病人的生命特征数据,响应病人的突发事件。     

基于TGAM模块的穿戴式脑电实时采集监护系统

设计了一种基于TGAM模块的穿戴式无线脑电采集监护系统.文章先后详细阐述了本系统的工作流程、硬件设计和软件设计,系统利用干电极采集脑电原始数据,TGAM模块和微处理器进行数据处理与分析,安卓APP进行数据的显示和日常监护,同时,当脑电异常时,预警模块及时报警,实现了全方位动态实时的脑电采集与监护.经验证,本系统实时性较强,便于携带.     

基于ARM的远程实时心电监护仪软件设计实现

当前心电监护仪器主要仍然应用于传统床头静态监护,缺乏便携性和诊断全面性.提出了一种通讯基于CDMA无线网络的远程心电实时监护系统中监护仪前端的软件设计方案,整体设计立足于动态监护方式.监护仪在硬件上采用ARM7的主控芯片,通过模块化的嵌入式软件设计方案,特别在采样转换、数据存取和通讯协议方面得到细节性的实际研究,确保数据的完整性、连续性和准确性,便于监护服务器的分析诊断.监护仪还定义了人机交互接口,方便功能扩展.临床结果表明,该系统满足了动态心电监护要求.     

基于ZigBee技术的医疗输液监护系统设计

现有的临床输液监护形式中,大多采用人工监护;为了改善医疗输液环境,实现输液过程的智能监护,设计了一种利用TI公司CC2530芯片的基于ZigBee技术的医疗输液监护系统;该系统采用压力传感器采集输液状态信息,在传感器和监视设备间构建ZigBee无线通信网络,将传感器检测到的输液信息,通过无线网络发送到监视设备上;分析了系统的工作原理、硬件组成、软件设计;实验结果表明该系统具有误差低,实时性好和可靠度高等优点;提高了输液监护过程的安全性和医护人员的工作效率,为医护人员及病人带来了方便.     

一种用于临床监护的无线系统的设计

介绍了一种基于无线收发模块和单片机的监护系统的设计,阐述了系统的基本原理及硬件的实现。     

基于GPRS的远程心电实时监护终端

针对现代医疗的新要求,设计了一种基于GPRS的远程心电实时监护终端。该监护终端能采集人体心电信号并实时发送,从而实现真正意义上的无线实时监护。介绍了系统原理和总体方案,着重阐述了监护终端的硬件设计以及相应单片机的软件设计。     

多病床两级报警无线心电监护系统的设计

设计了一种多病床两级报警无线传输心电监护系统.说日月了系统的硬件电路设计和软件设计思想,重点介绍了心电监护终端的硬件设计和PC机集中监控中心的功能.系统的探测部分完成心电信号的数据采集、无线传输、心律失常实时分析、检测、一级报警功能,集中监护中心部分完成各病床病人心电信号的实时监测、数据存储、心电图显示、二级报警功能.     

可穿戴式生命体征监护设备的研制

专门针对高压氧舱内生命体征多参数监测及健康监护的技术实现问题,提出了一种基于IEEE802.15.4协议的无线传感检测技术系统解决方案,阐述了无线传感检测系统的体系结构以及主控制节点与生命体征参数采集传感器节点的硬件设计方法,给出了软件系统架构、软件设计流程及监护软件工作界面,对MAC层帧结构、物理层帧结构及系统时间同步策略进行了详细分析和设计.该系统样机已进入临床实验阶段,文中还给出了患者的临床检测数据,并与实用的进口监护设备的检测数据进行了对比,验证了临床应用的可行性.     

基于人脸视线追踪技术的嵌入式人机监护系统设计

为实时追踪用户的眼睛运动轨迹,设计一种基于人脸视线追踪技术的嵌入式人机监护系统。系统采用ARM7系列芯片作为核心硬件,利用人脸检测算法及视线追踪方法实现嵌入式人机监护系统的监护功能。实验结果表明,该系统追踪到的坐标与实际坐标一致,可以实现精准追踪。     

Integrated BIM,game engine and VR technologies for healthcare design: A case study in cancer hospital

The results of healthcare design should meet the requirements of design teams as well as healthcare stakeholders. However, misunderstandings that occur between the design teams and healthcare stakeholders when using 2D illustrations leads to the need for re-design and rework during the design phase. To overcome this problem, this study develops a Database-supported VR/BIM-based Communication and Simulation (DVBCS) system integrated with BIM, game engine and VR technologies for healthcare design special in the Semi-immersed VR environment. The DVBCS system is applied in a case study of a design project of a cancer center in Taiwan to verify the system and demonstrate its effectiveness in practice. The results demonstrate that a DVBCS system is an effective visual communication and simulation platform for healthcare design. The advantage of the DVBCS system lies not only in improving the communication efficiency between the design teams and healthcare stakeholders, but also in facilitating visual interactions and easing the decision-making process while communicating in the 3D VR/BIM environment. The effective use of the proposed DVBCS system will assist design teams and stakeholders significantly in systematically handling healthcare design work in future healthcare design.     

A hybrid power line and visible light communication system for indoor hospital applications

Modern hospitals are beginning to adopt E-HEALTH as efficient complements to the traditional healthcare services. To support the E-HEALTH services, a locatable, radiation-free and high-capacity communication system is urgently needed in hospitals. Power line communication (PLC) systems can use the ubiquitous power line network to power the light-emitting diode (LED) lamps while serving as the backbone network for the indoor visible light communication (VLC) systems naturally. In this article, a hybrid broadband power line and visible light communication system with orthogonal frequency division multiplexing modulation is proposed for the indoor hospital applications, which gives a brand-new solution to replace the conventional wireless communication systems in hospitals. A general-purpose system model is provided and some basic techniques to enhance system performance are also investigated. Moreover, a feasible demonstration which supports over 48 Mbps data rate within a bandwidth of 8 MHz is implemented in the laboratory.     

Relationship between solar radiation and surface distribution of vegetation in Fildes Peninsula and Ardley Island,Maritime Antarctica

The aim of this work is to produce a simplified vegetation map of ice-free areas of the Fildes Peninsula (FP) and Ardley Island (AI) thought object-oriented classification using a QuickBird satellite image and to evaluate the influence of the global solar radiation (GSR) over the vegetation distribution. The vegetation data were generated from multiresolution segmentation using the panchromatic and infrared layers, and for the classification we calculated the normalized vegetative difference index (NVDI) and the green NVDI. Two classes were created – Lichen and Moss Cushion SubFormation and Moss Subformation – with 48 vegetation samples collected on surveys during the austral summers of 2008 and 2009. We used a kappa index to evaluate the classification efficiency using 100 sampled points obtained in austral summer of 2013. The GSR was estimated, and in order to evaluate the effect of meteorological phenomena and cloudless, we measured the GSR using a net radiometer model CNR4 installed in FP between 2014 and 2016. The estimate of GSR was done for seasons of 2015, in order to estimate the light compensation point and the saturation point for the plant communities in FP and AI. The kappa index was 0.73 and the global accuracy was 0.78, showing consistency between the classification and ground truth. The area was covered by vegetation in FP was 16.7% and in AI is 59.1%. The vegetation cover is distributed differently at FP and AI, and our results suggest GSR plays an important role in vegetation distribution and these tendencies could be related to greater GSR demand by mosses when compared to lichens.     

Smart health: Big data enabled health paradigm within smart cities

In the era of “big data”, recent developments in the area of information and communication technologies (ICT) are facilitating organizations to innovate and grow. These technological developments and wide adaptation of ubiquitous computing enable numerous opportunities for government and companies to reconsider healthcare prospects. Therefore, big data and smart healthcare systems are independently attracting extensive attention from both academia and industry. The combination of both big data and smart systems can expedite the prospects of the healthcare industry. However, a thorough study of big data and smart systems together in the healthcare context is still absent from the existing literature. The key contributions of this article include an organized evaluation of various big data and smart system technologies and a critical analysis of the state-of-the-art advanced healthcare systems. We describe the three-dimensional structure of a paradigm shift. We also extract three broad technical branches (3T) contributing to the promotion of healthcare systems. More specifically, we propose a big data enabled smart healthcare system framework (BSHSF) that offers theoretical representations of an intra and inter organizational business model in the healthcare context. We also mention some examples reported in the literature, and then we contribute to pinpointing the potential opportunities and challenges of applying BSHSF to healthcare business environments. We also make five recommendations for effectively applying `BSHSF to the healthcare industry. To the best of our knowledge, this is the first in-depth study about state-of-the-art big data and smart healthcare systems in parallel. The managerial implication of this article is that organizations can use the findings of our critical analysis to reinforce their strategic arrangement of smart systems and big data in the healthcare context, and hence better leverage them for sustainable organizational invention.     

A new real time disk-scheduling method based on GSR algorithm

Disk scheduling has an important role in QOS guarantee of soft real-time environments such as video-on-demand and multimedia servers. Since now, some disk-scheduling algorithms have been proposed to schedule real-time disk requests. One of the most recent algorithms is global seek-optimizing real-time (GSR) that schedules the disk requests with different ready times by a global regrouping scheme. In the present paper, we propose a real-time disk-scheduling algorithm based on GSR that is called IGSR (improved GSR). IGSR creates the scan-groups of the requests and tries to find a good feasible schedule by optimized grouping with considering another chance for tasks that miss their deadlines at initial grouping. With regard to the admission policy of tasks, two different version of proposed method are presented: the first one has been designed for the case that all the disk requests available simultaneously and second one has been designed for the case that requests are admitted dynamically (GSR does not support the second one). It means that in the second case, the request queue may change when a task is running but in the first one it does not change. Simulation results showed IGSR outperformed GSR and some other related works in terms of maximum supportable streams, number of missed deadlines, and disk throughput.     

Analysis of the Desynchronization Attack Impact on the E2EA Scheme

The healthcare IoT system is considered to be a significant and modern medical system. There is broad consensus that these systems will play a vital role in the achievement of economic growth in numerous growth countries. Among the major challenges preventing the fast and widespread adoption of such systems is the failure to maintain the data privacy of patients and the integrity of remote clinical diagnostics. Recently, the author proposed an end-to-end authentication scheme for healthcare IoT systems (E2EA), to provide a mutual authentication with a high data rate between the communication nodes of the healthcare IoT systems. Although the E2EA authentication scheme supports numerous attractive security services to resist various types of attack, there is an ambiguous view of the impact of the desynchronization attack on the E2EA authentication scheme. In general, the performance of the authentication scheme is considered a critical issue when evaluating the applicability of such schemes, along with the security services that can be achieved. Therefore, this paper discusses how the E2EA authentication scheme can resist the desynchronization attack through all possible attack scenarios. Additionally, the effect of the desynchronization attack on the E2EA scheme performance is analyzed in terms of its computation and communication costs, based on a comparison with the recently related authentication schemes that can prevent such attack. Moreover, this research paper finds that the E2EA authentication scheme can not only prevent the desynchronization attack, but also offers a low cost in terms of computations and communications, and can maintain consistency and synchronization between the communication nodes of the healthcare IoT systems during the next authentication sessions.     

Insurance Classifications and Drivers' Galvanic Skin Response

Drivers' galvanic skin responses were recorded in town traffic and on country roads. Two groups of drivers were compared, those who would pay higher insurance premiums, by reason of their ago or occupation, and the rest. The high insurance group did not differ from the rest in the magnitude of the GSR. but when the ratio of the GSR in town traffic to that on a country road was considered there was a significant difference such that the high insurance group had a relatively greater GSR on the country road.

It is suggested that in town traffic most of the GSR arc generated by the actions of other drivers, whereas on the open road the GSRs are self generated by the subjects' driving. The GSR on the open road will therefore be more affected by the individual method of driving and by the risks the driver takes. The ratio of town GSR to country GSR can be used to eliminate the large unexplained differences between subjects and to expose the differences in driving behaviour     

Development of a statistical model to classify driving stress levels using galvanic skin responses

Many studies have demonstrated the strong relationships between physiological responses and driving stress, but they have done little to build a model that could be used to identify a driver's stress accurately in real time. The objective of this study is to develop a model that accurately classifies driving stress by monitoring physiological responses—specifically galvanic skin response (GSR). GSR data were collected from nine drivers with licenses obtained in the US in real road driving situations with two stress conditions—rest period (low stress) and highway or city driving (high stress). The validation drive was performed by one driver with licenses obtained in South Korea in real long‐term road driving situations with two stress conditions—rural area (low stress) and highway or highway under construction (high stress). Those two conditions were used to build a binary logistic regression model to classify low stress or high stress based on a driver's measured hand GSR. The overall classification accuracy of the developed model was found to be 85.3%, and the accuracy of cross validation, with a testing dataset, was found to be 83.2%. A simple logit model was developed to identify drivers' stress by incorporating their GSR data. The developed model can be embedded in a wearable device equipped with GSR sensors for drivers to detect their stress level in real time.     

Development of a wrist-worn calorie monitoring system using bluetooth

Methods and tools for monitoring real-time human body information in daily life are required for advanced healthcare. In this study, a method for estimating energy expenditure during health exercises was evaluated and a wrist-worn sensing system based on the method was developed. Pulse monitoring was used to calculate energy expenditure by estimating oxygen uptake from a correlation between heart rate and oxygen uptake. Bluetooth technology was utilized for sending data by wireless communication. By the newly developed system, energy expenditure during exercise can be estimated considering individual difference and distinguishing changes in grade or load. Our goal is to construct a miniaturized wearable system that monitors vital signs and has many applications for healthcare. The study suggests that a wearable pulse sensing system proposed could provide useful information for healthcare.