A survey on managing users' preferences in ambient intelligence

Understanding the importance of preference management in ambient intelligent environments is key to providing systems that are better prepared to meet users' expectations. This survey provides an account of the various ways that preferences have been handled in Artificial Intelligence. Our analysis indicates that most of those techniques lack the ability to handle ambiguity and the evolution of preferences over time. Further exploration shows that argumentation can provide a feasible solution to complement existing work. We illustrate our claim by using an intelligent environment case study

Apical Hypertrophic Cardiomyopathy: The Variant Less Known

Hypertrophic cardiomyopathy (HCM) is an umbrella term for a heterogeneous heart muscle disease that was historically (and still is) defined by the detection of left ventricular (LV) hypertrophy (LVH) in the absence of abnormal cardiac loading conditions. Long after this morphological definition was established, the genetic basis of HCM was discovered, and we now know it is predominantly caused by autosomal dominant mutations in sarcomeric protein genes.1 Several patterns of LVH have been described in HCM: asymmetric septal (here referred to as “classic” HCM), concentric, reverse septal, neutral, and apical (ApHCM),2 as well as other, rarer LVH variants such as isolated lateral LVH and isolated inferoseptal LVH. Distinguishing between morphological HCM subtypes has conferred little in terms of personalized management strategies, with one distinctive exception: ApHCM. Compared with classic HCM, ApHCM is more sporadic, sarcomere mutations are detected less frequently, there is more atrial fibrillation (AF) and sudden cardiac death (SCD) risk factors differ. No authoritative ApHCM‐specific recommendations to guide diagnosis, family screening, and patient risk stratification currently exist. First described in Japan in 1976,2 ApHCM is exemplified by “giant” negative precordial T‐waves on electrocardiography and by “spadelike” configuration of its LV cavity in end diastole.3 This review summarizes the epidemiology, clinical expression, genetics, and prognosis of ApHCM, while also highlighting knowledge gap

Visualization of Data for Ambient Assisted Living Services

Ambient assisted living (AAL) services that provide support for people to remain in their homes are increasingly being used in healthcare systems around the world. Typically, these ambient assisted living services provide additional information though location-awareness, presence-awareness, and context-awareness capabilities, arising from the prolific use of telecommunications devices including sensors and actuators in the home of the person receiving care. In addition there is a need to provide abstract information, in context, to local and remote stakeholders. There are many different viewing options utilizing converged networks and the resulting explosion in data and information has resulted in a new problem, as these new ambient assisted living services struggle to convey meaningful information to different groups of end users. The article discusses visualization of data from the perspective of the needs of the differing end user groups, and discusses how algorithms are required to contextualize and convey information across location and time. In order to illustrate the issues, current work on nighttime AAL services for people with dementia is described

Familial cardiomyopathy caused by a novel heterozygous mutation in the gene LMNA (c.1434dupG): a cardiac MRI-augmented segregation study

In a five-generation family carrying a novel frameshift LMNA variant (c.1434dupG, p.Leu479AlafsX72), imaging-augmented segregation analysis supports its association with lamin heart disease. Affected members exhibit conduction abnormalities, supraventricular and ventricular arrythmias, dilated cardiomyopathy with non-infarct pattern midwall septal fibrosis, heart failure and thromboembolic complications

Abstract Argumentation / Persuasion / Dynamics

The act of persuasion, a key component in rhetoric argumentation, may be viewed as a dynamics modifier. We extend Dung's frameworks with acts of persuasion among agents, and consider interactions among attack, persuasion and defence that have been largely unheeded so far. We characterise basic notions of admissibilities in this framework, and show a way of enriching them through, effectively, CTL (computation tree logic) encoding, which also permits importation of the theoretical results known to the logic into our argumentation frameworks. Our aim is to complement the growing interest in coordination of static and dynamic argumentation.Comment: Arisaka R., Satoh K. (2018) Abstract Argumentation / Persuasion / Dynamics. In: Miller T., Oren N., Sakurai Y., Noda I., Savarimuthu B., Cao Son T. (eds) PRIMA 2018: Principles and Practice of Multi-Agent Systems. PRIMA 2018. Lecture Notes in Computer Science, vol 11224. Springer, Cha

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance

A Human-in-The-Loop context-aware system allowing the application of case-based reasoning for asthma management

Determining the asthma health status of a person is a relevant task in the application of context-awareness and case-based reasoning for asthma management. As there are no devices that can track the asthma health status of a person constantly, it is necessary to use a Human-in-The-Loop (HiTL) approach for creating a solution able to associate their health status with context-related data. This research work proposes a system that implements the Asthma Control Questionnaire (ACQ) for determining the asthma health status of a person. The system links this health status to context-related data the person is exposed and creates the cases to be used by the CBR component of the system. The system is then evaluated by users from a usability perspective through the Health IT Usability Evaluation Model (Health-ITUEM)