People with language impairments can have difficulties expressing themselves to others, leading to major limitations to their safety, independence, and quality of life in general. Aphasia is an example of an acquired language impairment that affects many people (around 2 million in the United States), being commonly caused by stroke, but also by other brain injuries. Several augmentative and alternative communication solutions are available to help people with communication difficulties, but they are generally not suitable for all contexts of use (e.g., lying in bed). In the scope of the “APH-ALARM” project, which aimed at developing solutions to support people with Aphasia, we envision a system for the bedroom that enables conveying messages to be sent to a caregiver or relative, for example. Focusing on gesture input, in this contribution, we investigated if smartwatch sensors and machine learning (ML) can be used to recognise arm gestures executed while lying. We explored different factors, namely the feature set, size of the sliding window used for feature extraction, and ML classifier. The results obtained with data gathered from ten subjects are promising, with the best factor combinations for the user-independent solution leading to a mean macro F1 score of 94% or 95%. They demonstrate the potential of using wearables to develop a gesture input modality for the in-bed scenario, which can also potentially be extended to other contexts (e.g., sitting in a bed, chair, or sofa, or standing). This research also provides useful insights that inform future work, including the development and deployment of communication support systems that can benefit not only people with communication difficulties (e.g., more independence), but also those caring for them (e.g., more peace of mind). • A new gesture-based interaction modality for communication support is proposed. • The proposal is aligned with the needs of users with Aphasia while lying in bed. • The use of wearable sensors for arm gesture recognition is investigated. • The best achieved mean F1 score was of 95%, for a user-independent solution.

The evolution and miniaturization of technology allows the development of portable solutions for physiology assessment, and the chance to mimic real world settings using Virtual Reality (VR). This work proposes an end-to-end framework for assisting Exposure Therapy (ET) with VR serious games and physiology monitoring. It relies on a generic architecture changing the VR stimuli, i.e., the phobia being considered, while the remaining modules can be re-used for data collection and analysis by a therapist team. It also integrates customizable bio-feedback, triggering specific events or adjusting the amount of stimuli based on the physiological response. The VR serious games were assessed with 16 participants before being integrated into the architecture. The framework’s capacity to acquire bio-signals and other metrics in a synchronous manner was evaluated in two user studies with a total of 23 participants.

Cities are continuously growing in population, vehicles, infrastructures and intelligence. Using and deploying smart technologies in the cities infrastructure can improve the multiple existing areas of a city, such as mobility by improving the road network, infrastructure by improving the urban planning and population by contributing with better services. Porto city has an in-place infrastructure of xed and moving sensors in more than 400 buses and roadside units, with both GPS and mobility sensors in moving elements, and with environmental sensors in xed units. This infrastructure can provide valuable data that can extract information to better understand the city and, eventually, support actions to improve the city mobility, urban planning, and environment. This work has the objective of using the information generated by the sensors placed in the buses of Porto, and using it to analyze the road tra c information based on the mobility patterns of the buses. The data from the environmental sensors deployed in Porto is also provided and used to analyze the air quality of the city and its in uence by the tra c. The developed system provides a full stack integration of the information into a city dashboard that displays and correlates the data generated from the buses movement and the environment from the xed sensors, allowing di erent visualizations over the road tra c and the environment in the city, and decisions over the current status of the city. A good example is the relation of bus speed variation with possible anomalies on the road or tra c jams. Visualizing such information with a superior level of detail on the road tra c, more anomalies can be found, adding more value to a city manager when taking urban planning decisions to improve the city mobility in a smart way.

In this paper we propose VANESS, a naming service that supports user-to-user communication on mobile devices within a heterogeneous scenario comprising typical Internet Service providers and ad-hoc networks formed by vehicles and roadside units, VANETs. VANESS provides real-time mapping between user

The European Union Digital Library (EUDL) is the central repository for all content published by the different branches of the European Alliance for Innovation (EAI). EUDL also hosts or indexes content from selected partner or member organizations and affiliates.

This paper proposes REINVENT, a software architectural solution to decouple the specificities of using vehicular network communication resources in Android smartphone applications. REINVENT provides a REST based message passing interface based on Android's content provider to abstract vehicular network communication services. Using REINVENT, Android applications can use transparently the communication resources avoiding network transport layer details. REINVENT was tested in both laboratory and real world scenarios in the road with WAVE/IEEE 802.11p technology, to assess its usefulness in two Android applications, (VNChat and iThere). The real experiments also assess how REINVENT supports a mobile application to log relevant parameters in typical vehicular networks testing in different network scenarios.

Between first responder professionals, firefighters registered the highest number of deaths on duty. An abnormal high proportion is associated with cardiovascular events. Our main goal is to identify fatigue/stress during daily routine activities, focusing on the cardiovascular analysis. To accomplish this purpose, ECG wave morphological alterations are analyzed. It was observed that the RR, PP and ST segment significantly differentiate the most stressful tasks from the others.

Video can be a valuable source of information for monitoring first responders during operations in the field. In this paper we propose the MonitorMe, an application that supports online video monitoring of first responders. MonitorMe allows capturing video from a personal perspective, using a smartphone camera, and sending it to a remote observer. In order to reduce battery consumption and bandwidth usage, MonitorMe modulates the video frame rate according to the user activity/speed. The latter are estimated using the smartphone built-in accelerometer. The results have shown the potential of MonitorMe as a reliable non-GPS solution, which can be used for remote online monitoring of first responders in action.

Professionals such as First Responders are frequently exposed to extreme environmental conditions, which induce stress and fatigue during extensive periods of time. In this scenario, the main issues are the quantification and evaluation of stress and fatigue, since uncontrolled levels have a profound and negative impact on human health and performance. Based on an existing wearable monitoring solution - the Vital Jacket®- we propose an individual and team monitoring mobile solution called DroidJacket. DroidJacket is based on Android mobile devices and provides data aggregation, processing, visualization and optionally relaying services. The DroidJacket design is plugin oriented, integrating analysis modules, namely an online ECG plugin for both real time pulse and arrhythmia detection.