Brain–computer interface connected to telemedicine and telecommunication in virtual reality applications

A novel brain–computer interface work is proposed for the applications of virtual reality in telemedicine and telecommunication in this study, in which the aim is to enhance the interactions between the humans and computers with virtual reality technologies. The system mainly contains automatic artifacts removal, feature extraction, significant feature selection and classification. A similarity measure approach is proposed to automatically remove the artifacts, which effectively reduce the influence of artifacts and simultaneously achieve higher accuracy. The artificial bee colony algorithm is used to select significant sub-features from feature combinations, which further greatly enhance the classification accuracy. Experimental results indicate that the proposed system performs better than several state-of-the-art approaches. It is also recommended that it is suitable for the applications of virtual reality in telemedicine and telecommunication.     

面向个人和家庭的远程医疗通信技术

近年来国际上开展了大量的面向个人和家庭的远程医疗中使用的通信技术的研究,其中国际产业联盟———康体佳健康联盟在这方面成果显著。本文通过介绍康体佳健康联盟的生态系统、市场关注和端到端参考构架,展现出远程医疗的应用模式、总体方案以及实现互联互通的关键技术。     

基于B/S模式的远程医疗系统开发与研究

设计了一种新型远程医疗系统，系统的总体结构采用B／S(测览器／服务器)模式结构体系。给出了系统网络结构模型以及远程监护、远程会诊的结构图。结合海军医院的应用需求开发了六个子功能系统，可提供远程监护、远程会诊、电子病历、疾病诊断专家分析、在线咨询等服务。     

医学图像标准研究及面向对象实现

对美国放射学会、美国电器制造商协会的DICOM（Digital Imaging and COmmunication in Medicine)标准和远程放射学标准等做了研究，提出了按应用范围和应用层次分析和采用医学图像标准的方法。在此基础上提出了医学影像系统按医学图像标准的分类，设计和实现了具有适当属性和方法的图像标准类，以图像类的属性和方法体现医学图像标准，并在远程医学会诊系统中得到应用。     

It's more than just use: An exploration of telemedicine use quality

“Simply saying that more use will yield more benefits without considering the nature of this use (and context) is clearly insufficient” [W.H. DeLone, E.R. McLean, The DeLone and McLean model of information system success: a ten-year update, Journal of Management Information Systems 19 (4) (2003) 9–30, p. 16]. Our research specifies the use quality construct in the context of a mission critical system deployment—namely, the use of medical video conferencing for patient exams. The product of this field study is a socio-technical framework for use quality in telemedicine service encounters. We also propose generalized categories (which may extend across domains) for identified attributes, provide a comparative overview of patient and provider perspectives, and discuss the effects of and remedies for selected attribute deficiencies.     

REPro.JPEG: a new image compression approach based on reduction/expansion image and JPEG compression for dermatological medical images

Medical images are known for their huge volume which becomes a real problem for their archiving or transmission notably for telemedicine applications. In this context, we present a new method for medical image compression which combines image definition resizing and JPEG compression. We baptise this new protocol REPro.JPEG (reduction/expansion protocol combined with JPEG compression). At first, the image is reduced then compressed before its archiving or transmission. At last, the user or the receiver decompresses the image then enlarges it before its display. The obtain results prove that, at the same number of bits per pixel lower than 0.42, that REPRo.JPEG guarantees a better preservation of image quality compared to the JPEG compression for dermatological medical images. Besides, applying the REPRo.JPEG on these colour medical images is more efficient while using the HSV colour space compared to the use of RGB or YCbCr colour spaces.     

The reality of medical work: The case for a new perspective on telemedicine

This paper considers the nature of medical work and how new telemedicine technologies can be developed to support that work. Telemedicine developers attempt to increase communication and collaboration between medical practitioners and between patients and medics, with the goal being to make medical care and information more easily accessible. However, the focus of telemedicine systems appears to have so far been technology centred, and the work they are trying to support is often ignored. We argue that to develop appropriate telemedicine technologies, it is important to understand the nature of medical work, and to examine the manner in which medical practiceactually occurs. Only then will we be in a position to design appropriate telemedicine technologies to support these activities. Unless designers have an insight into the work itself, new technologies will continue to fail to support what telemedicine effectively aims to promote — collaboration and access to distributed knowledge.     

岛礁远程医学异构网融合需求研究

本文简要介绍了岛礁远程医学异构网融合的研究背景,重点分析了解决岛礁远程医学传输问题可采用的卫星通信、4G/5G通信、自组网、COFDM等多种通信方式,分析了异构网融合的难点,提供了基于TCP/IP的粗略解决方案,对分析岛礁远程医学平台建设需求具有一定的指导作用。     

A novel solution approach and protocol design for bio-telemetry applications

In this contribution a novel model-based solution approach is introduced for medical networks and biotelemetric applications. Medical networks are communication networks that serve for the purpose of monitoring and protecting human health. These networks are designed to use biotelemetric ways to transmit the vital data to health observers such as doctors, nurses, first-aid teams, hospitals, and health agencies. These networks are also used in collective damages that may occur in situations such as flood, earthquake, war and terror and for treatments and follow-up of patients and to organize health teams more effective and efficiently. Implementations using this model presented here provides a reference design. In addition MCP (Medical Communication Protocol) and MMP (Medical Management Protocol) are designed to reveal how communications between modules designed. In this way, communication rules explained clearly on developed solution based on the model.     

Clustering-based compression connected to cloud databases in telemedicine and long-term care applications

A novel clustering-based compression work connected to cloud databases is proposed for the applications of telemedicine and long-term care in this study, where the goal is to enhance information transfer rate and storage capacity to further improve communication between medical staffs and patients in long-term care and telemedicine. The proposed system mainly involves three-dimensional histogram competitive Hopfield neural network (CHNN) clustering, regionalization, and modified block truncation coding (BTC). Three-dimensional histogram CHNN clustering and regionalization are proposed to achieve better clustering accuracy within three-dimensional spaces and simultaneously overcome the problems of fluctuating initial values of clustering. Modified BTC is also proposed to analyze clustering regions with different compression rates according to their importance in order to greatly preserve important image feature information under the condition of smaller image sizes. The experimental results indicate that the proposed system is adaptive and performs better than several previous methods. It is also suggested being suitable for the applications of telemedicine and long-term care connected to cloud databases.