Fuzzy rule-based system applied to risk estimation of cardiovascular patients

Cardiovascular decision support is one area of increasing research interest. On-going collaborations between clinicians and computer scientists are looking at the application of knowledge discovery in databases to the area of patient diagnosis, based on clinical records. A fuzzy rule-based system for risk estimation of cardiovascular patients is proposed. It uses a group of fuzzy rules as a knowledge representation about data pertaining to cardiovascular patients. Several algorithms for the discovery of an easily readable and understandable group of fuzzy rules are formalized and analysed. The accuracy of risk estimation and the interpretability of fuzzy rules are discussed. Our study shows, in comparison to other algorithms used in knowledge discovery, that classifcation with a group of fuzzy rules is a useful technique for risk estimation of cardiovascular patients. © 2013 Old City Publishing, Inc

Fuzzy-description logic for supporting the rehabilitation of the elderly

[EN] According to the latest statistics, the proportion of the elderly (+65) is increasing and is expected to double within the European Union in a period of 50 years. This ageing is due to the improvement of quality of life and advances in medicine in the last decades. Gerontechnology is receiving a great deal of attention as a way of providing the elderly with sustainable products, environments, and services combining gerontology and technology. One of the most important aspects to consider by gerontechnology is the mobility/rehabilitation technologies, because there is an important relationship between mobility and the elderly's quality of life. Telerehabilitation systems have emerged to allow the elderly to perform their rehabilitation exercises remotely. However, in many cases, the proposed systems assist neither the patients nor the experts about the progress of the rehabilitation. To address this problem, we propose in this paper, a fuzzy-semantic system for evaluating patient's physical state during the rehabilitation process based on well-known standard for patients' evaluation. Moreover, a tool called FINE has been developed that facilitates the evaluation be accomplished in a semi-automatic way first asking patients to carry out a set of standard tests and then inferencing their state by means of a fuzzy-semantic approach using the data captured during the rehabilitation tasks.This research was funded by the Spanish Ministry of Economy and Competitiveness and by EU FEDER funds under project grants TIN2016-79100-R and TIN2015-72931-EXP. It has also been funded by the Junta de Comunidades de Castilla¿La Mancha scholarship 2018-UCLM1-9131Moya, A.; Navarro, E.; Jaén Martínez, FJ.; González, P. (2020). Fuzzy-description logic for supporting the rehabilitation of the elderly. 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Assessment of Hand Gestures Using Wearable Sensors and Fuzzy Logic

Hand dexterity and motor control are critical in our everyday lives because a significant portion of the daily motions we perform are with our hands and require some degree of repetition and skill. Therefore, development of technologies for hand and extremity rehabilitation is a significant area of research that will directly help patients recovering from hand debilities sustained from causes ranging from stroke and Parkinson’s disease to trauma and common injuries. Cyclic activity recognition and assessment is appropriate for hand and extremity rehabilitation because a majority of our essential motions are cyclic in their nature. For a patient on the road to regaining functional independence with daily skills, the improvement in cyclic motions constitutes an important and quantifiable rehabilitation goal. However, challenges exist with hand rehabilitation sensor technologies preventing acquisition of long-term, continuous, accurate and actionable motion data. These challenges include complicated and uncomfortable system assemblies, and a lack of integration with consumer electronics for easy readout. In our research, we have developed a glove based system where the inertial measurement unit (IMU) sensors are used synergistically with the flexible sensors to minimize the number of IMU sensors. The classification capability of our system is improved by utilizing a fuzzy logic data analysis algorithm. We tested a total of 25 different subjects using a glove-based apparatus to gather data on two-dimensional motions with one accelerometer and three-dimensional motions with one accelerometer and two flexible sensors. Our research provides an approach that has the potential to utilize both activity recognition and activity assessment using simple sensor systems to help patients recover and improve their overall quality of life

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Mathematics in health care with applications

The Author aims to show how mathematics can be useful in supporting key activities in a hospital, including: noninvasive measurement of a patient’s status (see chapter 1), evaluation of quality of services (see chapter 2), business and clinical administration (see chapter 3), and diagnosis and prognosis (see chapter 4). Such applications suggest the development of innovative projects to improve health care processes, services and systems. In this way, mathematics can be a very important tool for technological and societal development

Seeing the wood for the trees. Carer related research and knowledge: A scoping review

This NIHR-SSCR funded scoping review provides a comprehensive mapping of what is known about carers and caring, and aims to help inform policy, practice and research in relation to carers. The review was undertaken by searching 10 electronic bibliographic databases, supplemented by additional web searches to identify academic research, grey literature and wider knowledge. The analysis adopts a selective thematic approach covering: carer variables - the characteristics of different types of carer and different caring situations; types of care - the nature of needs of the cared for person and the features of the care situation; the impact of caring – resilience and coping, employment and health; and carer support and needs assessment. The final section highlights key messages identified from the review. It found that caring involves all sections and age groups of the population, with people are likely to experience one or more periods of caregiving over their lifetime. The uniqueness of each caring relationship is also highlighted. In relation to types of carers, knowledge about ‘hard to reach’ groups, such as BAME and LGBT carers, remains sparse. Older carers are also relatively invisible in policy and research terms. It found that much of the knowledge about carers identified in the review relates to their characteristics, their lived experience and the nature of their caregiving, with relatively less being known about the effectiveness of interventions to support them. The report concludes by offering suggestions for policy and practice. An appendix provides a bibliography of the 3,434 items identified in review, classified into 17 types of reference

Decision support system for in-flight emergency events

Medical problems during flight have become an important issue as the number of passengers and miles flown continues to increase. The case of an incident in the plane falls within the scope of the healthcare management in the context of scarce resources associated with isolation of medical actors working in very complex conditions, both in terms of human and material resources. Telemedicine uses information and communication technologies to provide remote and flexible medical services, especially for geographically isolated people. Therefore, telemedicine can generate interesting solutions to the medical problems during flight. Our aim is to build a knowledge-based system able to help health professionals or staff members addressing an urgent situation by given them relevant information, some knowledge, and some judicious advice. In this context, knowledge representation and reasoning can be correctly realized using an ontology that is a representation of concepts, their attributes, and the relationships between them in a particular domain. Particularly, a medical ontology is a formal representation of a vocabulary related to a specific health domain. We propose a new approach to explain the arrangement of different ontological models (task ontology, inference ontology, and domain ontology), which are useful for monitoring remote medical activities and generating required information. These layers of ontologies facilitate the semantic modeling and structuring of health information. The incorporation of existing ontologies [for instance, Systematic Nomenclature Medical Clinical Terms (SNOMED CT)] guarantees improved health concept coverage with experienced knowledge. The proposal comprises conceptual means to generate substantial reasoning and relevant knowledge supporting telemedicine activities during the management of a medical incident and its characterization in the context of air travel. The considered modeling framework is sufficiently generic to cover complex medical situations for isolated and vulnerable populations needing some care and support services

Implementation of e-mental health interventions for informal caregivers of adults with chronic diseases:a protocol for a mixed-methods systematic review with a qualitative comparative analysis

Introduction Informal caregivers provide the majority of care to individuals with chronic health conditions, benefiting the care recipient and reducing use of formal care services. However, providing informal care negatively impacts the mental health of many caregivers. E-mental health interventions have emerged as a way to provide accessible mental healthcare to caregivers. Much attention has been given to reviewing the effectiveness and efficacy of such interventions, however, factors related to implementation have received less consideration. Therefore, this mixed-methods systematic review will aim to examine factors associated with the effectiveness and implementation of e-mental health interventions for caregivers.Methods and analysis Eligible studies published since 1 January 2007 will be searched for in several electronic databases (CINAHL Plus with Full Text, the Cochrane Library, EMBASE, PsycINFO, PubMed and Web of Science), clinical trial registries and OpenGrey, with all screening steps conducted by two independent reviewers. Studies will be included if they focus on the implementation or effectiveness of e-mental health interventions designed for informal adult caregivers of adults with cancer, heart disease, stroke, diabetes, dementia or chronic obstructive pulmonary disease. Pragmatic randomised controlled trials quantitatively reporting on caregiver anxiety, depression, psychological distress or stress will be used for a qualitative comparative analysis to identify combinations of conditions that result in effective interventions. Qualitative and quantitative data on implementation of e-mental health interventions for caregivers will be integrated in a thematic synthesis to identify barriers and facilitators to implementation. These results will inform future development and implementation planning of e-mental health interventions for caregivers.Ethics and dissemination Ethical approval is not required for this study as no primary data will be collected. Results will be disseminated in the form of a scientific publication and presentations at academic conferences and plain language summaries for various stakeholders.PROSPERO registration number CRD42020155727.</p

The Development of an Empirical Model for Estimation of the Sensitivity to Heat Stress in the Outdoor Workers at Risk

Background: Workers who work in hot environments may be at risk for heat stress. Exposure to heat can result in occupational illnesses, including heat stroke, heat cramps, and heat exhaustion. The risk of exposure to heat depends on individual, environmental, and occupational risk factors. Individual risk factors may decrease the individual’s tolerance to heat stress. Sensitivity as an intrinsic factor may predispose a person to heat stress. Aim: This study was aimed to determine the criteria for sensitivity parameter, specify their weights using the fuzzy Delphi-analytical hierarchy, and finally providing a model to estimate sensitivity. The significant of the study is presenting a model to estimate the sensitivity to heat stress. Materials and Methods: The expert’s opinions were used to extract the criteria in Delphi method. After determining the weight of each criterion, Fuzzy analytic hierarchy Process (FAHP), by mathematical principles matrix and triangular fuzzy numbers, was applied for the prioritization of criteria. Results: According to experts’ viewpoints and considering some exclusion, 10 of 36 criteria were selected. Among 10 selected criteria, age had the highest percentage of responses (90% (27/30)) and its relative weight was 0.063. After age, the highest percentages of response were assigned to the factors of preexisting disease (66.6% (20/30)), body mass index (56.6% (17/30)), work experience (53.3% (16/30)), and clothing (40% (16/30)), respectively. Other effective criteria on sensitivity were metabolic rate, daily water consumption, smoking habits, drugs that interfere with the thermoregulatory processes, and exposure to other harmful agents. Conclusions: Eventually, based on the criteria, a model for estimation of the workers’ sensitivity to heat stress was presented for the first time, by which the sensitivity is estimated in percent.Keywords: Heat stress, Sensitivity, Personal factors, Fuzzy AH