Issue 19

Dynamic Nutrition Behavior Awareness System For The Olders

Tudor Cioară
Asistent Doctor Inginer

Recent studies have shown that in Europe more than 15% of the older population is affected by poor nutrition and malnutrition caused by ageing problems such as decrease in sensitivity, difficulty in chewing and swallowing, lack of transportation, physical difficulty, forgetfulness and other issues. The nutrition related problems contribute to / or exacerbate the older adults chronic and acute diseases, speed up the development of degenerative diseases, increase the time needed to recover from illness and may even cause death.

In this context the project DIET4Elders (Dynamic nutrItion bEhavior awareness sysTem FOR the ELDERS) aims at developing an innovative ICT-based system that will support and help elders during their daily life self-feeding activities and will early detect and prevent the instauration of malnutrition. Figure 1 shows the DIET4Elders overall system conceptual architecture.

Figure 1. DIET4Elders system conceptual architecture

The Monitoring Layer will collect data regarding the older adult"s self-feeding activities and the context in which these activities took place using the new state of the art sensors such as:

  • smart cards and RFID (Radio-frequency identification) tags and readers to detect the type of food eaten;
  • smart containers or smart plates to detect the quantity of food eaten;
  • inertial and magnetic position sensors to detect the intake motions;
  • strain gauge and acoustic sensors for detecting the chewing and swallowing problems;
  • heart rate and blood pressure sensors for detecting the diet-related psychology, etc.

The Analysis and Assessment Layer aims at: (i) identifying the daily life activity that the older adult is currently carrying out, (ii) constructing the older adult activity diagram representing his/her self-feeding behaviour and (iii) identifying the unhealthy self-feeding behaviours. On-line reasoning based techniques are used with the goals of identifying the older adult"s current daily life activity and eventually identifying critical situations (e.g. food chocking, lack of food in the house, too much drugs are taken all at once, etc.) in which urgent alarming and intervention of informal carers is required. The identified older adult"s self-feeding activities are chained in activities diagrams describing the overall older adult"s self-feeding behaviour. Prediction and knowledge engineering techniques are employed on the constructed self-feeding activities diagram and used to proactively detect and identify unhealthy behavioural patterns (as defined by nutritionists).

The Support Services Layer will provide services to: (i) assist older adults and their informal carers during daily self-feeding activities aiming at detecting and preventing the instauration of malnutrition, (ii) help the nutritionists to establish the degree in which the older adults follow their prescribed diet and to dynamically adjust it and (iii) enable the dynamic selection, based on the prescribed diet, of suitable food service provider and potentially enable automated shopping (Diet Aware Food Ordering Service). The Diet Aware Food Ordering Service will aggregate the food delivery services of different providers and will guide the older adults and their informal carers to order the right food that complies to the nutritionists recommended diet. The selection of food services which satisfy complex criteria like the older adult recommended diet or preferences for a certain type of food is not a trivial task and cannot be addressed using conventional techniques. There are a large number of food delivery services available on the market offering various types of food. In this context, we will model the food services selection and aggregation problem as a combinatorial optimization problem which aims to find the optimal combination of food services such that the considered criteria are met. Such an optimization problem requires specific search strategies capable of identifying the optimal or near optimal solutions. For these techniques to work effectively, the system will create a virtual electronic marketplace which will define food services in a diet and nutritionally rich context and where food providers can register their services. All the food services registered and available in the market will comply with a service description specification based on semantic annotation.

To address the DIET4Elders project ambitious goals the consortium brings together partners with specific expertise in the following domains: telehealthcare (Tunstall Healthcare , the world"s leading provider of telehealthcare solutions), information and computer technology (Kings College London and the Distributed Systems Research Laboratory from the Technical University of Cluj-Napoca), software development (ISOIN ) and food providing and delivery to elders (COESCO).

The project success will subsequently help reducing homecare, healthcare, and other associated costs, which in Europe are currently estimated around 170 billion euro per year .



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