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The paper presents fuzzy based approach to select best suited network for remote healthcare services. A direct mapping between clinical parameters and corresponding QoS network parameters is done. The paper proposes an application independent integrated system where stage of the disease is identified based on the fuzzified clinical parametric values which are critical for that disease. Based on critical nature of the disease i.e. stage of disease, the requirements of network QoS are defined in linguistic terms. This eliminates strict sense condition on any specific network and selects most suited network out of all available networks. The objective is to avoid denial of service in case of unavailability of a network with high QoS values and also to conserve resources in case the patient is in normal condition medically. A simulation study has been presented to verify the selection of the network based on stage of disease.

Cardiac Disease has become very common perhaps because of increasingly busy lifestyles. The rapid advancement of mobile communication technologies offers innumerable opportunities for the development of software and hardware applications for remote monitoring of chronic disease. This paper describes a remote health-monitoring service that provides an end-to-end solution. We present an efficient data mining-based solution that recognizes different CVDs (such as ventricular flutter/fibrillation, atrial fibrillation, atrial premature beat, premature ventricular contraction) from the compressed ECG, it was proposed to perform real-time classification of Cardiac Vascular Disease (CVD) based on data mining techniques. The subset of the features selection from the compressed ECG was performed using the Genetic algorithm and the clustering was performed using Expectation Maximization.

Chronic diseases, especially cardiovascular diseases, have become one of the leading health problems in China. For preventing cardiovascular diseases and improving treatment, it is necessary to regularly monitor vascular status related physiological signals at home. We designed a home used wireless system for daily monitoring cardiovascular condition. Vital physiological signs are obtained by a chair-based measurement apparatus and then transmitted by bluetooth. Finally, these data are delivered to a remote healthcare server through internet. General practitioners can analyze the related indices and make an electronic report to users, who can check health status and understand cardiovascular risks.

For 18 years, the American Telemedicine Association (ATA) Annual International Meeting & Exposition has been the premier forum for professionals in the telemedicine, telehealth and mHealth space -- one of the fastest growing meetings in the country. ATA 2013 is on course to be the largest ATA meeting ever, with over 6,000 projected attendees. The program will include 500 educational sessions and posters, highlighting the latest innovations, applications and research in telemedicine. The 2013 exhibit hall will feature nearly 300 of the leading vendors in remote healthcare technologies. With over 6000 projected attendees, from all around the world, there's no better place to meet and network with your peers and thought leaders in the field. Detailed program information--including courses, sessions and CME information--will be available January 2013 at:http://www.americantelemed.org.

In this paper first we present an overview of the state-of-the-art remote patient monitoring systems in the back- drop of real clinical needs. The paper establishes a clear guideline in terms of clinical expectations from such a system from the viewpoint of practicing clinicians. It provides in-depth analysis of the shortcomings of the existing architectures and paves a way towards developing a practical “patient-centric” architecture that could be useful in the day-to-day clinical practice for providing “continuum of care”. Subsequently, the restrictions imposed by the resource constrained nature of such a system on development of appropriate hardware for supporting information processing on the data acquired by body-worn sensors are analyzed.

Improvement of life quality in the developed nations has systematically generated an increase in the life expectancy. A statistic studies curried out by the French national institute of statistic and economic studies (INSEE) shows a new distribution of age classes in France. In fact, almost one in three people will be over 60 years in 2050, against one in five in 2005, and France will have over 10 million of people over 75 years and over 4 million of people over 85 years. Nevertheless, the increasing number of elderly person implies more resources for aftercare, paramedical care and natural assistance in their habitats. The current healthcare infrastructure in those countries is widely considered to be inadequate to meet the needs of this increasingly older population. In this case a permanent assistance is necessary wherever they are, healthcare monitoring is a solution to deal with this problem and ensure the elderly to live safely and independently in their own home for as long as possible.

Due to the global trend of aging societies with increasing demand for low cost and high quality healthcare services, there has been extensive research and development directed toward wireless and remote healthcare technology that considers age-associated ailments. In this paper, we introduce Mobility Assessment and Remote Healthcare System (MARHS) that utilizes a force sensor in order to provide quantitative assessment of the mobility level of patients with movement disorder ailment, which is one common age-associated ailment. The proposed system also enables the remote healthcare services that allow patients to receive diagnoses from clinical experts without his/her presence. MARHS also contains a data analysis unit in order to provide information that summarizes the characteristics of symptoms of a group of patients (e.g., patients with a certain type of ailment) using a combination of feature ranking, feature selection, and classification algorithms. The results of the analyses on the data from a clinical trial show that the examination results of the proposed system can accurately recognize various groups of patients, such as, patients with (i) chronic obstructive pulmonary disease, (ii) hypertension, and (iii) cerebral vascular accident with an average accuracy of 90.05%, 82.60%, and 93.54%, respectively.

One of the major functions of telemedicine is the prompt delivery of modern healthcare to the remotest areas with reduced cost and efficient use of communication resources. The establishment of a well organized telemedicine system is therefore exigent for the developing countries like Bangladesh where there are extreme paucities of efficient healthcare professionals and equipments, specifically in the rural areas. In this paper a novel, hierarchical and semi-centralized telemedicine network architecture has been proposed holistically focusing on the rural underdeveloped areas of Bangladesh. The model utilizes the existing fiber optic backbone and wireless telecommunication infrastructures to connect the remote healthcare centers with the urban specialized hospitals. The proposed network is of low cost, flexible and faster as well as more concrete than the existing healthcare organogram of Bangladesh. Finally, some features and services associated with the model have also been proposed which are pragmatic and easily implementable.

With the growth of aging population and the patients with spinal cord injury, the demand of intelligent vehicle that is also called smart carrier increases. The development of a smart carrier to help the subject to stand and move becomes very important issue for home health care problem. However, the safety of user is crucial for our proposed smart carrier. The purpose of this study is to design a system based on our developed smart carrier to monitor the user’s physiological conditions, including ECG, respiratory rate, and blood pressure. Using the wireless techniques, Bluetooth, into, a real-time remote healthcare and early warning system can be built. This system can be divided into two parts. The first part is composed of portable sensors that acquired physiological signals and pre-processed by micro-controller and transmitted to the monitoring system via Bluetooth. The second part includes signal display, storage and data analysis. Furthermore, while unusual physiological signal is detected, the system could send a warning signal to remind, or inform the caregivers through the personal handy-phone system (PHS) immediately and made carrier doing relative actions like emergency stop. The purposed system has the potential to be a useful monitoring and warning tool for the patients using smart carrier.

In this paper, we describe the architecture of Sqwelch, and show how it can be applied in the delivery of healthcare to patients in the community and to support their caregiver networks. We show, through a detailed scenario, how personalized web applications can be composed by non technical users on our website: www.sqwelch.com (on which we have a demonstration video). Sqwelch uses lightweight semantics to effect mediation between heterogeneous components.

For the lack of effective methods of service aggregation in convergent network and diversification of user needs, we proposed a user preferences-driven dynamic service aggregation model (UPDDSAM) and the corresponding aggregation algorithm. This model implements run-time aggregation of service processes and service resources by adopting dynamic rules and late-binding technology. At the same time we also presents an ontology model of user preferences based on service scenario and user status, making the service aggregation more user-centric. Finally, through the case study of a practical application “Remote Healthcare”, we verify the validity of the model.

There are several important trends in healthcare that call for the deployment of remote healthcare applications. It is expected that people will live longer and that chronic diseases, such as hypertension and diabetes, will become more prevalent among older adults.

In the context of healthcare and the assistance of dependent people, this paper describes an original proactive solution for home monitoring. Our approach does not use any additional sensors and is only based on the observation of existing home automation events. An analysis of user habits is proposed to offer automatic scenarios which adapt to user capabilities. The simulation results, issued from previous experiments, show that our approach helps improve user autonomy while facilitating their use of daily services.

In this study, we propose a novel design of the wearable digital sensor, embedded within a monitoring suit for posture monitoring. Our studies are going to solve wearable monitoring systems' drawbacks, include non-washable, uncomfortable, and high power -consumption due to complex signal processing. There are two digital sensor designs, dome shape type and clip shape type, knitted on clothes. The characteristics of these two digital sensor designs are easy implementation, small size, low power-consumption, and comfort. Our proposed system can catch up and monitor postures of the real-time information from the wearing person. Therefore, the monitoring system embedded with the capability of detecting real-time postures and transmission makes it highly suitable for applications of remote healthcare and wellness.

Major benefits may be achieved in the efficient administration of healthcare provision if a secure and adaptable communications system could be established to allow patient and medical data to be communicated to remote locations. However, significant barriers exist preventing the uptake of this technology. This paper addresses a number of these concerns via the integration of technology allowing for the efficient generation of encryption keys directly from the characteristics of electronic devices (ICmetrics) and the utilisation of flexible communication pathways within enclosed environments offered by the incorporation of intelligent physical panels constructed from frequency selective surfaces (FSS) within building designs. (4 pages)

Ambient Intelligence has acquired great importance in recent years and requires the development of new innovative solutions. This paper presents a tele-monitoring system aimed at enhancing remote healthcare of dependent people at their homes. The system integrates distributed and heterogeneous Wireless Sensor Networks for optimizing the construction of ubiquitous scenarios. This approach provides the system with more flexibility to change its functionalities and components after the initial deployment than other analyzed proposals.

The improvement in processor performance through continuous breakthroughs in transistor technology has resulted in the proliferation of lightweight embedded systems. Advances in wireless technology and embedded systems have enabled remote healthcare and telemedicine. Continuous and real-time monitoring can discretely analyze how a patient's lifestyle affects his/her physiological conditions and if additional symptoms occur under various stimuli. Diabetes is one of most difficult challenges facing the healthcare industry today. One of the primary afflictions of diabetic patients is peripheral neuropathy (loss of sensation in the foot). As a direct result of this condition, the likelihood of ulcer increases which in many cases leads to to amputation. We have developed a wireless electronic orthotics composed of lightweight embedded systems and non-invasive sensors which can be used by diabetic patients suffering from peripheral neuropathy. Our proposed system monitors feet motion and pressure distribution beneath the feet in real-time and classifies the state of the patient. The proposed system detects the conditions that could potentially cause a foot ulcer. This system enables a continuous feedback mechanism for instance in case of an undesired behavior or condition a preemptive message wirelessly to the patient and the patient's caregiver.

The improvement in processor performance through continuous breakthroughs in transistor technology has resulted in the proliferation of lightweight embedded systems. Advances in wireless technology and embedded systems have enabled remote healthcare and telemedicine. Continuous and real-time monitoring can discretely analyze how a patient's lifestyle affects his/her physiological conditions and if additional symptoms occur under various stimuli.Diabetes is one of most difficult challenges facing the health-care industry today. One of the primary afflictions of diabetic patients is peripheral neuropathy (loss of sensation in the foot). As a direct result of this condition, the likelihood of ulcer increases which in many cases leads to to amputation. We have developed a wireless electronic orthotics composed of lightweight embedded systems and non-invasive sensors which can be used by diabetic patients suffering from peripheral neuropathy. Our proposed system monitors feet motion and pressure distribution beneath the feet in real-time and classifies the state of the patient. The proposed system detects the conditions that could potentially cause a foot ulcer. This system enables a continuous feedback mechanism for instance in case of an undesired behavior or condition a preemptive message wirelessly to the patient's cell phone/PDA/PC and over the WEB to the patient's care-giver. This system can potentially reduce the amputation rates resulting from neuropathy by a huge factor.

A system with wearable sensors for detecting and sensing vital and physical motion signals such as the ECG, respiration, temperature, sweatiness, three-axis accelerations, and the motions of both knee ankles and elbows is presented. The system is also equipped with a bluetooth transceiver such that the obtained sensor signals can be transmitted to mobile phones or remote computers for either monitoring or post signal processing to extract knowledge or information. The presented system is embedded with signal processing algorithms such as the heart rate, the respiratory period, the body temperature, the degree of sweatiness, and the posture of wearing person are demonstrated. The heart rate and heart rate variation from the measured ECG data are estimated using an adaptive ESPRIT algorithm. This system is highly suitable for applications of remote healthcare and wellness.

Governments the world over are worried about the increasing costs of providing healthcare to elderly and infirm persons whose numbers are growing rapidly. This paper describes ReMoteCare, a prototype we have developed for remote healthcare monitoring using a Wireless Sensor Network (WSN) Pulse Oximeters, environmental sensors and streaming video to monitor patients. To illustrate the functionality of the prototype we describe three typical remote health monitoring scenarios set in an aged care facility. Finally a series of experimental scenarios were developed and implemented in a laboratory setting to evaluate the reactivity of the monitoring system to a series of physiological conditions that cause the streaming video to alert the observer to potential problems.

� Abstract—Clinicians and patients need mobile tools to detect ototoxic change early and prevent hearing loss. We report on the development of an upgrade of our existing desktop-based clinical-audiological instrumentation into a mobile instrument platform which efficiently supports personalized ototoxicity monitoring on the hospital wards as well as clinic by a trained clinician. Our new wireless-enabled system also serves as the instrumentation platform for the next phase of our work which is remote healthcare delivery with patient-guided at-home ototoxicity monitoring using an evidence-based individualized SRO protocol. I. INTRODUCTION

The Australian Commonwealth Department of Health and Ageing provided funds for the Australian medical schools to establish Rural Clinical Schools. This workforce initiative has enabled medical students to learn in a diverse range of rural and remote healthcare settings. A common questionnaire was developed and agreed on by all the directors of the Rural Clinical Schools. Use of this common questionnaire will facilitate reports on student attitudes and program outcomes, both within individual Rural Clinical Schools and at a national program level. The data analysis will inform the community and the Australian Government about the effectiveness of the national Rural Clinical School program in (1) meeting the primary aims of providing high quality rural medical education; and (2) addressing the medical workforce shortage in rural and remote areas.

Telemonitoring systems have been shown to greatly reduce medical costs while improving the quality of medical care. Today, the main factors restricting the development and popularization of Telemonitoring systems include scalability and compatibility. The challenge for the remote healthcare lies in the variety of heterogeneous medical sensors which need to be dynamically removed or added to the environment according to the health care needs. This paper presents the design for an ontology-based context model and related middleware that provides a reusable and extensible application platform for Remote Healthcare. We designed the ontology context model to describe physiological parameters, medical tasks and the patient’s personal profile. Developers may extend the ontology model by considering new requirements as needed.

Smart homes are intelligent environments that interact with their occupants in ways that improve their lives. This paper presents the ubiquitous pervasive technologies that will need to be integrated to realise the future vision of smart homes that have the intelligence to anticipate, predict and take decisions in a virtually autonomous manner. It also presents some of the major application areas that will benefit from the realisation of smart homes. It then discusses some of the challenges that need to be overcome in order for smart homes to become a reality and find acceptance from people across all sectors of the society.

International audience; The aim of the paper is to carry out a cost-minimisation analysis in order to measure the cost saving performances of teleconsultation in Guiana. A prospective analysis lasting 6 months of all admissions for three pathologies (cardiology, parasitology, dermatology) at four care stations in Guiana (Saint Georges, Trois Sauts, Maripasoula and Anticum pata). A cost-minimisation analysis is carried out to compare teleconsultation with air medical evacuations. Fixed and variable costs are estimated in order to identify the break-even point of teleconsultation. Estimations are done at two levels: aggregate level where the four stations are considered jointly, and disaggregate level where these stations are assumed to be separable. It also takes into account organisational and quality effects. If the four stations are considered jointly, the break-even point is 12.67 (Investments are assumed to last 6 years). This means that teleconsultation permits savings on air medical evacuation costs if thirteen evacuations are avoided each year inseparably at the four stations. We deduce a reference threshold for each station whose value is 3.17. If stations are analysed separately, the most efficient station is Trois Sauts with the lowest break-even point, 2.98. Saint Georges is the worst, 4.31, and suffers from organisational problems caused by personnel turnover which inflate costs of teleconsultation by about 35.96%. Our main question is whether teleconsultation is cost saving and our response is based on the comparison of break-event points with the number of air medical evacuations actually avoided during the period. At the aggregate level of the four stations, teleconsultation is not cost saving as only three evacuations were actually prevented. However, these evacuations were avoided in Trois Sauts. Regarding its break-even point, 2.98, we note that teleconsultation is already a promising option and permits savings.

Many studies have shown that mobile phones are in great demand; smart phones in particular have an ever-growing market. It is evident that with greater number of mobile users, people can be facilitated with mobile accessible applications. Of many beneficial applications one such application is providing remote healthcare on mobile devices. Much work has been done in this area of research; however using Bluetooth enabled smart phones with Wireless Application Protocol (WAP) technology implementing an intelligent remote healthcare system has been proposed. A rule based expert system can identify diagnosis for remotely located patients to off location expert physicians and subsequent analysis can be delivered to the patient relieving her from frequent visits to healthcare service provider thus reducing the load of patients on existing infrastructure. This paper presents design and implementation of Mobile Intelligent Remote Healthcare Monitoring System (MIRHMS) and discusses issues.

This research is in the field of remote healthcare monitoring systems which propose software solutions to monitor elderly people in their own homes. Our objective is to take advantage of the technological diversity of several Decision Support Systems used to detect distress situations. We propose a multi-agent approach in which each agent encapsulates a decision support system. This encapsulation enables the real-time combination of decisions. In this paper, we present the architecture of our multi-agent system and the real-time scheduling of the collective decision process.

Physiological or biological stress is an organism’s response to a stressor such as an environmental condition or a stimulus. The identification of physiological stress while performing the activities of daily living is an important field of health research in preventive medicine. Activities initiate a dynamic physiological response that can be used as an indicator of the overall health status. This is especially relevant to high risk groups; the assessment of the physical state of patients with cardiovascular diseases in daily activities is still very difficult. This paper presents a context-aware telemonitoring platform, IPM-mHealth, that receives vital parameters from multiple sensors for online, real-time analysis. IPM-mHealth provides the technical basis for effectively evaluating patients’ physiological conditions, whether inpatient or at home, through the relevance between physical function and daily activities. The two core modules in the platform include: 1) online activity recognition algorithms based on 3-axis acceleration sensors and 2) a knowledge-based, conditional-reasoning decision module which uses context information to improve the accuracy of determining the occurrence of a potentially dangerous abnormal heart rate. Finally, we present relevant experiments to collect cardiac information and upper-body acceleration data from the human subjects. The test results show that this platform has enormous potential for use in long-term health observation, and can help us define an optimal patient activity profile through the automatic activity analysis.