Linking recorded data with emotive and adaptive computing in an eHealth environment

Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development

Systems identification and application systems development for monitoring the physiological and health status of crewmen in space

The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems

Communication system for a tooth-mounted RF sensor used for continuous monitoring of nutrient intake

In this Thesis, the communication system of a wearable device that monitors the user’s diet is studied. Based in a novel RF metamaterial-based mouth sensor, different decisions have to be made concerning the system’s technologies, such as the power source options for the device, the wireless technology used for communications and the method to obtain data from the sensor. These issues, along with other safety rules and regulations, are reviewed, as the first stage of development of the Food-Intake Monitoring projectOutgoin

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 341)

This bibliography lists 133 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 349)

This bibliography lists 149 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1991. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Predicting Blood Glucose with an LSTM and Bi-LSTM Based Deep Neural Network

A deep learning network was used to predict future blood glucose levels, as this can permit diabetes patients to take action before imminent hyperglycaemia and hypoglycaemia. A sequential model with one long-short-term memory (LSTM) layer, one bidirectional LSTM layer and several fully connected layers was used to predict blood glucose levels for different prediction horizons. The method was trained and tested on 26 datasets from 20 real patients. The proposed network outperforms the baseline methods in terms of all evaluation criteria.Comment: 5 pages, submitted to 2018 14th Symposium on Neural Networks and Applications (NEUREL

Real-time sweat pH monitoring based on a wearable chemical barcode micro-fluidic platform incorporating ionic liquids

This work presents the fabrication, characterisation and the performance of a wearable, robust, flexible and disposable chemical barcode device based on a micro-fluidic platform that incorporates ionic liquid polymer gels (ionogels). The device has been applied to the monitoring of the pH of sweat in real time during an exercise period. The device is an ideal wearable sensor for measuring the pH of sweat since it does not contents any electronic part for fluidic handle or pH detection and because it can be directly incorporated into clothing, head- or wristbands, which are in continuous contact with the skin. In addition, due to the micro-fluidic structure, fresh sweat is continuously passing through the sensing area providing the capability to perform continuous real time analysis. The approach presented here ensures immediate feedback regarding sweat composition. Sweat analysis is attractive for monitoring purposes as it can provide physiological information directly relevant to the health and performance of the wearer without the need for an invasive sampling approac

Innovation, Entrepreneurship and Governance for Sustainable Development of Africa’s Agri-food System

Africa has the human capital to transform its agricultural sector Growth in urban markets provides new opportunities for enterprise development Investments in science, technology, engineering and math must be increased Bold leadership, as well as policies that promote R&D collaboration and provide incentives for partnering with the private sector, should be implemented

Technologies for climate change adaptation: agricultural sector

This Guidebook presents a selection of technologies for climate change adaptation in the agricultural sector. A set of twenty two adaptation technologies are showcased that are primarily based on the principals of agroecology, but also include scientific technologies of climate and biological sciences complemented with important sociological and institutional capacity building processes that are required to make adaptation function. The technologies cover monitoring and forecasting the climate, sustainable water use and management, soil management, sustainable crop management, seed conservation, sustainable forest management and sustainable livestock management. Technologies that tend to homogenize the natural environment and agricultural production have low possibilities of success in conditions of environmental stress that are likely to result from climate change. On the other hand, technologies that allow for, and indeed promote, diversity are more likely to provide a strategy which strengthens agricultural production in the face of uncertain future climate change scenarios. In this sense, the twenty two technologies showcased in this Guidebook have been selected because they facilitate the conservation and restoration of diversity while at the same time providing opportunities for increasing agricultural productivity. Many of these technologies are not new to agricultural production practices, but they are implemented based on assessment of current and possible future impacts of climate change in a particular location. Agro-ecology is an approach that encompasses concepts of sustainable production and biodiversity promotion and therefore provides a useful framework for identifying and selecting appropriate adaptation technologies for the agricultural sector. The Guidebook provides a systematic analysis of the most relevant information available on climate change adaptation technologies in the agriculture sector. It has been compiled based on a literature review of key publications, journal articles, and e-platforms, and by drawing on documented experiences sourced from a range of organizations working on projects and programmes concerned with climate change adaptation technologies in the agricultural sector. Its geographic scope is focused on developing countries where high levels of poverty, agricultural production, climate variability and biological diversity currently intersect. Key concepts around climate change adaptation are not universally agreed. It is therefore important to understand local contexts – especially social and cultural norms - when working with national and sub-national stakeholders to make informed decisions about appropriate technology options. Thus, decision-making processes should be participative, facilitated, and consensus-building oriented and should be based on the following key guiding principles: increasing awareness and knowledge, strengthening institutions, protecting natural resources, providing financial assistance and developing context-specific strategies. For decision-making the Community–Based Adaptation framework is proposed for creating inclusive governance that engages a range of stakeholders directly with local or district government and national coordinating bodies, and facilitates participatory planning, monitoring and implementation of adaptation activities. Seven criteria are suggested for the prioritization of adaptation technologies: (i) The extent to which the technology maintains or strengthens biological diversity and is environmentally sustainable; (ii) The extent to which the technology facilitates access to information systems and awareness of climate change information; (iii) Whether the technology support water, carbon and nutrient cycles and enables stable and/or increased productivity; (iv) Income-generating potential, cost-benefit analysis and contribution to improved equity; (v) Respect for cultural diversity and facilitation of inter-cultural exchange; (vi) Potential for integration into regional and national policies and can be scaled-up; (vii) The extent to which the technology builds formal and information institutions and social networks. Finally, recommendations are set out for practitioners and policy makers: • There is an urgent need for improved climate modelling and forecasting which can provide a basis for informed decision-making and the implementation of adaptation strategies. This should include traditional knowledge. • Information is also required to better understand the behaviour of plants, animals, pests and diseases as they react to climate change. • Potential changes in economic and social systems in the future under different climate scenarios should also be investigated so that the implications of adaptation strategy and planning choices are better understood. • It is important to secure effective flows of information through appropriate dissemination channels. This is vital for building adaptive capacity and decision-making processes. • Improved analysis of adaptation technologies is required to show how they can contribute to building adaptive capacity and resilience in the agricultural sector. This information needs to be compiled and disseminated for a range of stakeholders from local to national level. • Relationships between policy makers, researchers and communities should be built so that technologies and planning processes are developed in partnership, responding to producers’ needs and integrating their knowledge