Mobile Healthcare Computing in the Cloud

To overcome drawbacks of traditional hospital management systems, this paper presents a new datamanagement system based on sensor networks and cloud computing. Cloud-computing features are included in the system's definition, framework and basic capabilities. The system is designed to tightly link various medical departments and coordinate among various medical institutions. Using sensor networks with mobile devices yields added flexibility and functionality for several medical-sensor devices and shows great practical potential. Employing healthcare information technology should lead to more efficient, safer, and higher-quality care. We believe a new scheme for cooperation between data, devices, and systems is mandated. This scenario requires that a variety of information from different sources be integrated. The data comes from several separate sources, ranging from patient monitors to sensors located nearby that provide environmental data, electronic medical records stored by the hospital, hospital administrative information, and financial and healthcare resource management. Indeed, technology currently implemented by the network wireless microcontroller supports this kind of healthcare data management. In this light, we present a network layer and a middleware layer for sensor networks to support such networking and data management here.

… Conference of the IEEE, 2010

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International Journal of Computer Science Issues, 2012

ABSTRACT Wireless Body Area Sensor Networks (WBASN) is an emerging technology which uses wireless sensors to implement real-time wearable health monitoring of patients to enhance independent living. In this paper we propose a prototype of cloud mobile health monitoring system. The system uses WBASN and Smartphone application that uses cloud computing, location data and a neural network to determine the state of patients.

Vietnam Journal of Computer Science, 2016

Mobile cloud computing (MCC) is a new technology for mobile web services. Accordingly, we assume that MCC is likely to be of the heart of healthcare transformation. MCC offers new kinds of services and facilities for patients and caregivers. In this regard, we have tried to propose a new mobile medical web service system. To this end, we implement a medical cloud multi-agent system (MCMAS) solution for polyclinic ESSALEMA Sfax-TUNISIA, using Google's Android operating system. The developed system has been assessing using the CloudSim Simulator. This paper presents initial results of the system in practice. In fact the proposed solution shows that the MCMAS has a commanding capability to cope with the problem of traditional application. The performance of the MCMAS is compared with the traditional system in polyclinic ESSALEMA which showed that this prototype yields better recital than using usual application. Keywords Mobile cloud computing • Healthcare • Mobile web services • Cloud computing • CloudSim • Medical cloud multi-agent system B Jemal Hanen

2010 Second International Conference on eHealth, Telemedicine, and Social Medicine, 2010

Existing processes for patients' vital data collection require a great deal of labor work to collect, input and analyze the information. These processes are usually slow and error-prone, introducing a latency that prevents real-time data accessibility. This scenario restrains the clinical diagnostics and monitoring capabilities. We propose a solution to automate this process by using ¿sensors¿ attached to existing medical equipments that are interconnected to exchange service. The proposal is based on the concepts of utility computing and wireless sensor networks. The information becomes available in the ¿cloud¿ from where it can be processed by expert systems and/or distributed to medical staff. The proof-of-concept design applies commodity computing integrated to legacy medical devices, ensuring cost-effectiveness and simple integration.

Ubiquitous healthcare services are becoming more and more popular, especially under the urgent demand of the global aging issue. Cloud computing owns the pervasive and on-demand service-oriented natures, which can fit the characteristics of healthcare services very well. However, the abilities in dealing with multimodal, heterogeneous, and nonstationary physiological signals to provide persistent personalized services, meanwhile keeping high concurrent online analysis for public, are challenges to the general cloud. In this paper, we proposed a private cloud platform architecture which includes six layers according to the specific requirements. This platform utilizes message queue as a cloud engine, and each layer thereby achieves relative independence by this loosely coupled means of communications with publish/subscribe mechanism. Furthermore, a plug-in algorithm framework is also presented, and massive semistructure or unstructured medical data are accessed adaptively by this cloud architecture. As the testing results showing, this proposed cloud platform, with robust, stable, and efficient features, can satisfy high concurrent requests from ubiquitous healthcare services.

2012 The First IEEE Workshop on Enabling Technologies for Smartphone and Internet of Things (ETSIoT), 2012

A new context-aware data-and patient-centric paradigm for ubiquitous healthcare is central to deliver personalized healthcare solutions to the elderly and the physically challenged. However, this new paradigm requires real-time inthe-field processing of wirelessly collected vital signs using inherently complex physiological models and analysis of the processed information (derived physiological parameters) under context (e.g., location, ambient conditions, current physical activity) to extract knowledge about the health condition of patients. As the computational capabilities of biomedical sensor nodes are insufficient to run these models, an innovative resource provisioning framework that harnesses the computing capabilities of under-utilized electronic devices in the vicinity (e.g., smart phones, laptops, tablets, DVRs, medical terminals) to form a mobile computing grid is presented. The framework is imparted with self-optimization and self-healing capabilities for efficiency and robustness under uncertainty, respectively. The proposed mobile grid management framework serves as a key enabling technology for Internet-of-Things-(IoT-) based next-generation ubiquitous healthcare solutions.

Classification and Clustering in Biomedical Signal Processing

This chapter introduces the combination of wireless body area network and mobile cloud computing in healthcare. The increased growth of low-power integrated circuits, physiological sensors and wireless communication has introduced a new generation of wireless sensor networks. Cloud computing is on high demand, whereas in case of mobile cloud computing the device is much more user friendly to manage the information. The combination of wireless body area network (WBAN) and mobile cloud computing (MCC) promises a better performance to the users immediately. It is more feasible to wire a sensor which performs the required medical tests and provides the information through devices like mobile phones and tablets. In this chapter, a theoretical study on the combination of WBAN and mobile cloud computing has been done.

Existing processes for patients' vital data collection require a great deal of labor work to collect, input and analyze the information. These processes are usually slow and error prone, introducing a latency that prevents real-time data accessibility. This scenario restrains the clinical diagnostics and monitoring capabilities. We propose a solution to automate this process by using " sensors " attached to existing medical equipments that are interconnected to exchange service. The proposal is based on the concepts of utility computing and wireless sensor networks. The information becomes available in the " cloud " from where it can be processed by expert systems and/or distributed to medical staff. The proof-of-concept design applies commodity computing integrated to legacy medical devices, ensuring cost effectiveness and simple integration.

Bulletin of Electrical Engineering and Informatics, 2019

Mobile applications in emergency health care help maintain patient confidentiality and manage patient records, data storage. Compiles and analyzes care of better quality care. new implementations come with new goals and technologies like using mobile application with cloud computing system and reducing the responding time to safe the patient life and give the patient best health care professional service transition to using of mobile application in emergency healthcare, this paper will present (MCCEH) mobile cloud computing in emergency health care model, mainly reducing the wasting time in emergency health care, The process starting once the accident occurred and the patient run the application, mobile application will detect the patient location and allow him to book nearest medical center or specialist in some emergency cases once the patient did the booking will send help request to medical center this process will include an online pre-register patient in the medical center to ...