IN LIFE– INdependent LIving support Functions for the Elderly
IN LIFE is a 36-month EU-funded project, bringing together leading experts of design and urban integration, transport operation and business, with local and regional authorities and end-users organizations, which represent the economic, demographic and territorial diversity of Europe.
The number of elderly living with cognitive impairment is growing rapidly due to increasing life expectancy. The percentage of those who live alone depends upon the condition (i.e. roughly 30% of those diagnosed with dementia) but the majority would like to live in their own home or with family, provided that it is safe, comfortable, and cost effective. IN LIFE aims to prolong and support independent living for elderly with cognitive impairments, through interoperable, open, personalised and seamless ICT services that support home activities, communication, health maintenance, travel, mobility and socialization, with novel, scalable and viable business models, based on feedback from large-scale, multi-country pilots. Building on existing knowledge and tested AAL technology/services IN LIFE will offer 19 different services, which will be further optimised and adapted to the particular needs and wants of various elderly groups, including mild cognitive impairment (MCI), early dementia and cognitive impairment with co morbid conditions, plus formal and informal caregivers. These interoperable services will be integrated into an open, cloud- based, reference architecture to be tested in 6 Europe-wide pilots in Greece, Netherlands, Slovenia, Spain, Sweden, and UK, with over 1200 elderly with cognitive impairments, 600 formal and informal caregivers, and 60 other stakeholders. Attention will be paid to issues concerning multilingual and multicultural environments. The project will establish and extensively test new business models for a new taxonomy of elderly with cognitive impairments, encompassing those that are clustered as “dependent”, “at risk”, “assisted” or “active” and formulating and accessing new business scenarios, such as the “user-centric”, “service provider-centric” and “data exploitation-centric” ones.
IN LIFE [EU]
IN LIFE [SLO]
Commodity12 – COntinuous Multi-parametric and Multi-layered analysis Of DIabetes TYpe 1 & 2
COMMODITY12 aims at improving the daily management of diabetes and the prevention/management of its cardiovascular co-morbidities. A multi-layer multi-parametric infrastructure is being developed which monitors the patient’s physiological signals and lifestyle, and analyzes patient’s data to produce indicators to doctors concerning diabetes and its cardiovascular co-morbidities.
We will contribute to the project by developing methods for monitoring the patient’s lifestyle: recognition of patient’s elementary activity (e.g. walking, sitting, lying), estimation of patient’s energy expenditure and recognition of his/her main daily activity groups (e.g. work, exercise, rest). The reasoning is based on data obtained from an accelerometer placed on the patient’s chest and/or from sensors integrated in a smart phone worn by the user.
CHIRON – Cyclic and person-centric Health management: Integrated appRoach for hOme, mobile and clinical eNvironments
The project aims to develop an integrated framework for personalized health-care at home, in a nomadic environment and in the hospital. A patient is equipped with wearable sensors, which continuously monitor his condition. The sensors are connected to a smart-phone, which issues warnings and advises the patient based on a personalized health assessment model. The data from the sensors, together with the data from the patient’s health record and novel medical imaging solutions, is accessible to medical professionals. Their work is supported by an advanced health assessment model, which is continuously modified by incoming data and experts’ input. For explanation of the key concepts, and overview of the system, its functions and use in practice see the video on the right.
e-Turist – Electronic Mobile Tourist Guide
Are you planning a trip in Slovenia, but are not sure what you should see? Then e-Turist is just what you need. The application first asks you where and when you want to go, and what kind of sights you are interested in. It then prepares the perfect itinerary for you, using artificial intelligence to learn your preferences from your ratings of the sights you have seen, as well as ratings of other users with similar tastes. Finally, it guides you on your trip, showing the sights on the map, and providing written and spoken descriptions. Currently included are sights from the Heart of Slovenia region and Slovenian Istria.
The application uses a hybrid recommender system based on expert knowledge, user ratings and user profile to filter relevant points of interest (POI). After that it solves two coupled NP-complete problems, namely knapsack problem and traveling salesman problem, to choose a subset of relevant POI and to find the optimal path between them.
The application is available on all major mobile platforms and the website www.e-turist.si.
Confidence: Ubiquitous Care System to Support Independent Living
The Confidence system aims at helping the elderly stay independent longer by detecting falls and unusual movement which may indicate a health problem. The system uses location sensors and wearable tags to determine the coordinates of the user’s body parts, and an accelerometer to detect fall impact and movement. Machine learning is combined with domain knowledge in the form of rules to recognize the user’s activity. The fall detection employs a similar combination of machine learning and domain knowledge. It was tested on five atypical falls and events that can be easily mistaken for a fall. We show that neither sensor type can correctly recognize all of these events on its own, but the combination of both sensor types yields highly accurate fall detection. In addition, the detection of unusual movement can observe both the user’s micro-movement and macro-movement. This makes it possible for the Confidence system to detect most types of threats to the user’s health and well-being manifesting in his/her movement.