João Pavão

Abstract
This study aimed to identify: (i) the relevant applications based on information technologies and requiring smart cities' infrastructure to facilitate the mobility of older adults in URBAN SPACES; (ii) the type of data being used by the proposed applications; (iii) the maturity level of these applications; and (iv) the barriers TO their dissemination. An electronic search was conducted on Web of Science, Scopus, and IEEE Xplore databases, combining relevant keywords. Then, titles and abstracts were screened against inclusion and exclusion criteria, and the full texts of the eligible articles were retrieved and screened for inclusion. A total of 28 articles were included. These articles report smart cities' applications to facilitate the mobility of older adults using different types of sensing devices. The number of included articles is reduced when compared with the total number of articles related to smart cities, which means that the mobility of older adults it is still a not significant topic within the research on smart cities'. Although most of the included studies aimed the implementation of specific applications, these were still in an early stage of development, without the assessment of potential end-users. This is an important research gap since it makes difficult the creation of market-oriented solutions. Another research gap is the integration of knowledge generated by other research topics related to smart cities and smart mobility. Consequently, important issues (e.g., user privacy, data standardization and integration, Internet of Things implementation, and sensors' characteristics) were poorly addressed by the included studies.

Abstract
This study aimed to determine the methodological quality of user-centered usability evaluation of Ambient Assisted Living (AAL) solutions by (i) identifying the characteristics of the AAL studies reporting on user-centered usability evaluation, (ii) systematizing the methods, procedures and instruments being used, and (iii) verifying if there is evidence of a common understanding on methods, procedures, and instruments for user-centered usability evaluation. An electronic search was conducted on Web of Science, Scopus, and IEEE Xplore databases, combining relevant keywords. Then, titles and abstracts were screened against inclusion and exclusion criteria, and the full texts of the eligible studies were retrieved and screened for inclusion. A total of 44 studies were included. The results show a great heterogeneity of methods, procedures, and instruments to evaluate the usability of AAL solutions and, in general, the researchers fail to consider and report relevant methodological aspects. Guidelines and instruments to assess the quality of the studies might help improving the experimental design and reporting of studies on user-centered usability evaluation of AAL solutions.

Abstract
Cognitive health status is a determining factor for quality of life. Since early identification of mild cognitive impairment is critical to better manage further decline, and to guide therapeutic and rehabilitation interventions, there is the need for efficient clinical instruments able to monitor the individuals, particularly older adults, in their residential environments. This paper presents a scoping review to identify of innovative digital solutions to detect cognitive impairments and that might be used as a screening tool for age related cognitive impairment of community-dwelling older adults. Nineteen articles were included in this scoping review. As a main conclusion, most of the included articles report digital solutions to support the application of existing paper-based clinical instruments to assess specific or multiple cognitive functions. However, six studies explore new approaches to assess cognitive functions including virtual reality and serious games.

Abstract
Data visualization is key in the Big Data context, enabling different cognitive perspectives over large datasets. These visual perspectives can prompt relevant advantages with regard to healthcare records, because they may contribute to a faster, more understandable, and adequate way to capture patients' health history and overall condition, thus improving healthcare quality. Timelines are well-known visual artifacts that help healthcare professionals to visualize patients' electronic health records (EHR) over a time period. As data stored in EHR tend to quickly grow with each interaction between patient and healthcare system both number and size, traditional linear timelines are can increasingly become more difficult to manage visually, as they often span over different screens. Considering that a holistic analysis is desirable to provide proper and quality health services, data visualization should enable a seamless understanding of patients' health history and overall condition. When dealing with critical episodes - such as an emergency - where time is an important factor, this is even more decisive. Furthermore, traditional timelines do not support multidimensional data representation. This paper presents a new visual model of time-dependent EHR based on radial models. It is capable of simultaneously displaying several data categories that characterize patients' medical history, enabling medical professionals to be aware of different data categories over time in a single display, without the need to scroll between screens.

Abstract
Falls, especially in the elderly, are one of the main factors of hospitalization. Time-consuming intervention can be fatal or cause irreversible damages to the victims. On the other hand, there is currently a significant amount of smart clothing equipped with various sensors, particularly gyroscopes and accelerometers, which can be used to detect accidents. The creation of a tool that automatically detects eventual falls allows helping the victims as soon as possible. This works focuses in the automatic fall detection from sensors signals using long short-term memory networks. To train and test this approach, the Sisfall dataset is used, which considers the simulation of 23 adults and 15 older people. These simulations are based on everyday activities and the falls that may result from their execution. The results indicate that the procedure provides an accuracy score of 97.1% on the test set. © 2021, Springer Nature Switzerland AG.