Information and Communication Technologies for Ageing Well and e-Health

The omnipresence and familiarity of textiles in combination with the integration of invisible sensors, actuators, and information and communication technology under the term “interactive digital textiles” offer the potential of bridging the gap between age, the aging-population, and latest information and communication technology. Digital textiles are reaching maturity and first technology augmented cloths are becoming commercially available. However, little is known about the acceptance and projected use of digital textiles for/in home environments and whether acceptance is shaped by age, gender, expertise in interacting with technology, or other aspects of user diversity. In a survey with \(n=136\) participants, we identified and quantified factors that influence the adoption and rejection of a smart cushion as example for digital textiles. We found that attitude towards technology and attitude towards automation are decisive for the projected acceptance, while age plays a minor role. In addition, we provide a customer segmentation based on the projected use and provide detailed descriptions of adopters and rejecters as well as their model-based evaluations of the smart interactive cushion. The article concludes with open research questions and strategies for practitioners to leverage smart textile interfaces as basis for many innovative products in the future.

To face the challenges of increasing care needs due to demographic change, the development of smart home and Ambient Assisted Living (AAL) technologies present one approach, which is continuously forwarded. Besides aspects of technical development and implementation, user acceptance of diverse stakeholders plays a major role for a successful rollout and sustainable adoption of those technologies. So far, user acceptance research in this context has concentrated mostly on age-related issues. In contrast, disabilities and related care needs have hardly been researched yet. The current study focused on persons having different experiences with disabilities and care needs. In a qualitative interview pre-study (n = 9) and a follow-up quantitative online questionnaire study (n = 279) perceived benefits and barriers, use conditions, and acceptance of AAL technologies were contrasted. Four user groups were under study: disabled participants, relatives of disabled persons, professional caregivers, and, as a control group, persons without experience with disabilities. Results indicate that disabled and care-needy people show a higher acceptance and intention to use an AAL system than not-experienced people and especially professional caregivers. The motives for acceptance and rejection differ strongly regarding user diversity as well. The results contribute to a better understanding of user-specific acceptance of smart home and AAL technologies and show that the integration of diverse user groups into the technologies’ design and evaluation process is necessary.

Proactive support of patients with chronic diseases such as Congestive Heart Failure is vital since the recovery from a critical condition usually presents complications and it is not always possible. Although emergency situations may occur without prior warning, still in the majority of emergency cases, there are “signals” that precede their appearance. By capitalizing on technology developments that are changing the way how healthcare services are provided, we propose a multi-parameter and multi-level data analysis approach in order to detect possible alarms which can then trigger proper preventive medical interventions. The main contribution of the presented approach is a methodology that combines selected health parameters that can be measured in a home environment using ambient assisted living technologies, with clinical history, in order to design a risk detection system for a chronic disease based on a Bayesian reasoning network. The added value of the proposed approach is that the system not only collects, processes and transmits vital measurements to the healthcare experts but also detects risks within the collected data. The system developed is discussed in detail as well as the validation process performed both on a technical and a medical level.

As society ages, healthcare systems are preparing for an increasing prevalence of frail, co-morbid and older community-dwellers at risk of adverse outcomes including falls, malnutrition, hospitalisation, institutionalisation and death. Early intervention is desirable and pre-frailty, before onset of functional decline, may represent a suitable transition stage to target, albeit evidence for reversibility and appropriate interventions are limited. No consensus on the definition, diagnosis or management of pre-frailty exists. This work describes 25 healthcare related findings from the recently completed PERsonalised ICT Supported Service for Independent Living and Active Ageing (PERSSILAA) project, funded under the 2013–2016 European Union Framework Programme 7 (grant #610359). PERSSILAA developed a comprehensive Information and Communication Technologies (ICT)-supported platform to screen, assess, intervene and then monitor community-dwellers in two regions (Enschede in the Netherlands and Campania in Italy) in order to address pre-frailty and promote active and healthy ageing, targeting three important pre-frailty subdomains: nutrition, cognition and physical function. Proposed definitions of pre-frailty, ICT-based approaches to screen and monitor for the onset of frailty and targeted management strategies employing technology across these domains are described. The potential of these 25 healthcare recommendations in the development of future European guidelines on the screening and prevention of frailty is explored.

The healthcare system is one of the main pillars of any society. However, it carries with it an enormous economic weight. Portugal, alongside with many others, is a country in economic and social restructuration and consequently, the need to increase the efficiency of resource management and services is imperative. With the proven effectiveness of Business Intelligence (BI) in many organisations, the urge to implement such tools in Healthcare arises, specifically in the healthcare of Misericórdia. In addition to the results, it presents a critical analysis of the implementation and the process followed for the development and usage of KPIs. In this work, some concepts associated with the use of BI in Misericórdias were addressed, and the architecture of the developed solution was designed. It is also important to emphasise that the solution presented is pervasive, available anywhere at any time. Through this work, it was possible to gather all the data into a single structure (Data Mart), to identify a set of aspects that can be improved and to have a generalised view of the state of operation of the organisation, as far as health care is concerned. The developed includes ten KPIs in the area of Surgery Production and Waiting List Surgery. The dashboards can be analysed in several dimensions: date, specialities, physicians, service, diagnosis, location and time.

Continuing efforts to increase the relevance and effectiveness of nutritional recommendations are essential to promote long-term biological effects. Several studies refer that older adults often struggle with making the right decisions regarding meal preparation, healthy diets or groceries shopping. In this work research on user needs are presented, where different stakeholders were listened concerning their needs and perspectives within the domain of nutrition in older adults. Moreover, an improved version of SousChef, a meal recommender system is here presented, where new heuristics were added to the system and the users can now choose between 4 to 6 meals to be planned per day. Since another important factor besides nutrition and food preferences impact food choice concerns with the budget, new heuristics were considered in order to reduce waste and shortening the shopping list. Also new heuristics were added to the system to better reflect the Portuguese nutritional guidelines and information about food prices in order foster reducing waste and shortening one’s shopping list. The nutritional recommendations and the application was thought and designed for older adults, presenting friendly user interfaces and following the guidelines of a nutritionist.

As the age of the human population increases worldwide, depression in elderly patients has become a problem in medical care. In this study, we analyzed voice-emotion component data, attribute data, and Beck Depression Inventory (BDI) scores by multivariate analysis, particularly in the elderly, and proposed evaluation indicators for estimating the state of depression of elderly patients. We divided the data into two groups according to BDI scores: a state of depression and the absence of this state. The labels distinguishing the two groups were dependent variables, while the voice-emotion component and attribute information were set as independent variables, and we performed logistic regression analysis on the data. We obtained a prediction model with significantly sufficient fitness. In the receiver operating characteristic curve for the proposed depression evaluation indicator, a sorting performance with an area under the curve of approximately 0.93 was obtained.

The paper presents results from the SmartSleep project which aims at developing a smartphone app that gives users individual advice on how to change their behaviour to improve their sleep. The advice is generated by identifying correlations between behaviour during the day and sleep architecture. To this end, the project addressed two sub-tasks: detecting a user’s daytime behaviour and recognising sleep stages in an everyday setting. In the case of daytime activity detection the best results were achieved using an accelerometer at the wrist and another one at the ankle (87%). A subsequent smoothing step increased the accuracy to over 90%. For recognising sleep architecture we experimented with various consumer wearables that we used in addition to the usual PSG sensors in a sleep lab. Several sleep stage classifiers were learned from the resulting sensor data streams segmented into labelled sleep stages of 30 s each. Apart from handcrafted features we experimented with unsupervised feature learning based on the deep learning paradigm. Our best results for correctly classified sleep stages are between 86 and 90% for Wake, REM, N2 and N3, while the best recognition rate for N1 is 37%. Finally, we discuss a preliminary design of the algorithm for determining correlations between daytime behaviour and sleep architecture.

For the last 10 years, ageing well in the community has become a key concern of the European Union and its member states. Action plans as well as distinct programs such as the Ambient Assisted Living (AAL) Joint Programme are evidence of this engagement. Since then, many AAL products and services have been developed and implemented in the European market. Up to now, however, access to, and the availability of these solutions is difficult, and the information on their use is scarce. ActiveAdvice, an AAL EU-funded project aims to develop an online platform which offers both information on AAL solutions as well as advice to end users. This paper discusses the application of a multi-stakeholder perspective approach. It discusses the user-centered development and reflects on the establishment of AAL ecosystems and the functional requirements of the ActiveAdvice platform. It includes an extended methodological framework, which explains conclusively the ActiveAdvice stakeholders’ identification process and the user-centered requirements analysis, built on 38 semi-structured interviews with three stakeholder groups – consumers, businesses and governments. The integration of different stakeholders in the development and implementation of AAL solutions is a necessity as well as a challenge. This holds also true for the development of the ActiveAdvice platform.

In the context of an ageing population, providing relevant information to support seniors’ daily activities plays an important role to promote these citizens’ quality of life. This study is part of the +TV4E project, which aims to develop an Interactive Television (iTV) platform to transmit personalized information regarding Services of General Interest (SGI) to senior citizens. In order to better assess seniors’ preferences and expectations this study aims to propose the Assistance Services of General Interest for Elderly (ASGIE) concept and taxonomy. To achieve this, we set out to collect contributions from specialists in welfare promotion and public policies development for the Portuguese elderly to elicit detailed perceptions on the information needs of these population segment. The validity and relevance of contributions gathered along with these specialists were subsequently confirmed in a survey with 23 seniors recruited in the context of the +TV4E project. The ASGIE taxonomy is composed by 7 domains of information: Healthcare and Welfare services, Social services, Financial services, Culture services, Security services, Transport services and Local authority services. Findings from this study are relevant for authorities in charge of designing, implementing and monitoring public policies for seniors, as they present valuable indicators of information needs of these citizens.