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Multimedia telehomecare system using standard TV set

Nowadays, there are a very large number of patients that need specific health support at home. The deployment of broadband communication networks is making feasible the provision of home care services with a proper quality of service. This paper presents a telehomecare multimedia platform that runs over integrated services digital network and internet protocol using videoconferencing standards H.320 and H.323, and a standard TV set for patient interaction. This platform allows online remote monitoring: ECG, heart sound, blood pressure. Usability, affordability, and interoperability were considered for the design and development of its hardware and software components. A first evaluation of technical and usability aspects were carried forward with 52 patients of a private clinic and 10 students in the University. Results show a high rate (mean = 4.33, standard deviation-SD = 1.63 in a five-points Likert scale) in the global perception of users on the quality of images, voice, and feeling of virtual presence.

Realizing Effective Behavioral Management of Health: The Metamorphosis of Behavioral Science Methods

The past two centuries have shown radical improvements in health and longevity, with hygiene as the key contributor to this trend in the 19th century and antibiotics and vaccinations in the 20th century. With most infectious diseases largely at bay in the developed world, the greatest contributors to suboptimal health today are largely behavioral. For example, there are three behavioral risk factors-tobacco use, poor diet, and inactivity-that contribute to four chronic diseases: heart disease, type 2 diabetes, lung disease, and some cancers. Together, these behaviors account for more than 50% of preventable deaths (see the Web site 3four50.com). While medical advances will surely continue, it is likely that the next great advancements in health in the 21st century will occur via more effective behavior management.

User satisfaction with home telecare based on broadband communication

Home telecare services based on broadband communication were established in five locations in Europe. Two different types of telecare unit were developed: one based on a PC or set-top box containing a videoconferencing codec and another on off-the-shelf videoconferencing units. The participants in the project were 13 medical staff, 135 patients and 88 people informally caring for the patients. Questionnaires were used to evaluate user satisfaction with eight telecare services. Almost all participants rated the usability of the system as good or excellent. A total of 105 telecare sessions were scored by the medical staff. Overall, the quality of audio and video communication was judged satisfactory. For the patients and carers, the perceived quality of communication was also satisfactory and did not vary significantly between sites. The medical staff were reasonably satisfied with how the service supported them in their work. Except for the item about being able to support patients in a critical situation, medical staff agreed that an improved quality of health services was offered through telecare. All participants agreed that personal information was treated confidentially and that there was little risk in using the telecare services. The medical staff trusted the assessments they could make remotely while using the telecare system. Although the findings cannot be generalized due to the small number of telecare sessions and the relatively short duration of the experiment, the results encourage further research.

Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection.

Evaluation of a mobile health system for supporting postoperative patients following day surgery

A system based on mobile phones with built-in cameras has been developed for the postoperative management of patients sent home after day surgery. The system allows patients to send pictures and pulse oximetry measurements to a hospital server in a few seconds. Health professionals can then see what patients are describing and make a more objective estimate of the patients’ status. Over a five-month period, a total of 49 patients used the system. A total of 222 images were sent, the average image delivery time being 29 s (SD 11). In nine cases (18%), the availability of images modified the treatment, and a visit to an emergency unit was avoided in eight of them who had blood-stained dressings and normal haematomas. The patients who had their treatment modified sent more images (an average of 5.4/patient) than those for whom images confirmed the correct treatment (3.1/patient). Each telephone call lasted for a mean duration of 18 min (range 8–34). The patient satisfaction data showed that all the aspects studied were evaluated in a very positive way, with 96% of the patients completely satisfied with the attention received by the mobile health application.

Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems

The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the measure of this process is usually made in an obtrusive way, forcing nurses to get information and time data, affecting the proper process and generating inaccurate data due to human errors during the stressful journey of health staff in the operating theater. The use of indoor location systems can take time information about the process in an unobtrusive way, freeing nurses, allowing them to engage in purely welfare work. However, it is necessary to present these data in a understandable way for health professionals, who cannot deal with large amounts of historical localization log data. The use of process mining techniques can deal with this problem, offering an easily understandable view of the process. In this paper, we present a tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way. We have successfully tested this tool in a real surgical area with 3613 patients during February, March and April of 2015.

When the Social Meets the Semantic: Social Semantic Web or Web 2.5

The social trend is progressively becoming the key feature of current Web understanding (Web 2.0). This trend appears irrepressible as millions of users, directly or indirectly connected through social networks, are able to share and exchange any kind of content, information, feeling or experience. Social interactions radically changed the user approach. Furthermore, the socialization of content around social objects provides new unexplored commercial marketplaces and business opportunities. On the other hand, the progressive evolution of the web towards the Semantic Web (or Web 3.0) provides a formal representation of knowledge based on the meaning of data. When the social meets semantics, the social intelligence can be formed in the context of a semantic environment in which user and community profiles as well as any kind of interaction is semantically represented (Semantic Social Web). This paper first provides a conceptual analysis of the second and third version of the Web model. That discussion is aimed at the definition of a middle concept (Web 2.5) resulting in the convergence and integration of key features from the current and next generation Web. The Semantic Social Web (Web 2.5) has a clear theoretical meaning, understood as the bridge between the overused Web 2.0 and the not yet mature Semantic Web (Web 3.0).

Activity-based Process Mining for Clinical Pathways Computer aided design

Current trends in health management improvement demand the standardization of care protocols to achieve better quality and efficiency. The use of Clinical Pathways is an emerging solution for that problem. However, current Clinical Pathways are big manuals written in natural language and highly affected by human subjectivity. These problems make the deployment and dissemination of them extremely difficult in real practice environments. In this work, a complete computer based architecture to help the representation and execution of Clinical Pathways is suggested. Furthermore, the difficulties inherent to the design of formal Clinical Pathways in this way requires new specific design tools to help making the system useful. Process Mining techniques can help to automatically infer processes definition from execution samples. Yet, the classical Process Mining paradigm is not totally compatible with the Clinical Pathways paradigm. In this paper, a pattern recognition algorithm based in an evolution of the Process Mining classical paradigm is presented and evaluated as a solution to this situation. The proposed algorithm is able to infer Clinical Pathways from execution logs to support the design of Clinical Pathways.

Behaviour patterns detection for persuasive design in Nursing Homes to help dementia patients

Nursing homes usually host large accounts of persons with different levels of dementia. Detecting dementia process in early stages may allow the application of mechanisms to reduce or stop the cognitive impairment. Our ultimate objective is to demonstrate that the use of persuasive techniques may serve to motivate these subjects and induct re-learning mechanisms to stop mental impairment. Nevertheless, this requires the study of the behaviour of each patient individually in order to detect conduct disorders in their living ambient. This study presents a behavior pattern detection architecture based on the Ambient Assisted Living paradigm and Workflow Mining technology to enable re-learning mechanisms in dementia processes via providing tools to automate the conduct disorder detection. This architecture fosters the use of Workflows as representation languages to allow health professionals to represent persuasive motivation protocols in the AAL environment to react individually to dementia symptoms detected.

Performance assessment of a closed‑loop system for diabetes management

Telemedicine systems can play an important role in the management of diabetes, a chronic condition that is increasing worldwide. Evaluations on the consistency of information across these systems and on their performance in a real situation are still missing. This paper presents a remote monitoring system for diabetes management based on physiological sensors, mobile technologies and patient/doctor applications over a service-oriented architecture that has been evaluated in an international trial (83,905 operation records). The proposed system integrates three types of running environments and data engines in a single service-oriented architecture. This feature is used to assess key performance indicators comparing them with other type of architectures. Data sustainability across the applications has been evaluated showing better outcomes for full integrated sensors. At the same time, runtime performance of clients has been assessed spotting no differences regarding the operative environment.