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Health monitoring is crucial in hospitals and rehabilitation centers. Challenges can affect the reliability and accuracy of health data. Human error, patient compliance concerns, time, money, technology, and environmental factors might cause these issues. In order to improve patient care, healthcare providers must address these challenges. We propose a non-intrusive smart sensing system that uses a SensFloor smart carpet and an inertial measurement unit (IMU) wearable sensor on the user’s back to monitor position and gait characteristics. Furthermore, we implemented machine learning (ML) algorithms to analyze the data collected from the SensFloor and IMU sensors. The system generates real-time data that are stored in the cloud and are accessible to physical therapists and patients. Additionally, the system’s real-time dashboards provide a comprehensive analysis of the user’s gait and balance, enabling personalized training plans with tailored exercises and better rehabilitation outcomes. Using non-invasive smart sensing technology, our proposed solution enables healthcare facilities to monitor patients’ health and enhance their physical rehabilitation plans. info:eu-repo/semantics/publishedVersion

Recent findings have shown that exergames can facilitate physiotherapy. Environmental conditions, such as the inclusion of positive distractions also seem to play a role in health recovery, but prior studies have never analyzed their role in virtual environments. In this study, we developed an exergame for the exercise of upper limbs by designing virtual environments with nature elements and testing the impact of including additional positive distractions. Participants (N=124, 81 females) were randomly assigned to one of two virtual environments: positive distractions vs. no distractions. To test whether these two environments matched the users’ characteristics, sensation seeking was examined as a moderator. Measures of affect, sense of presence, intrinsic motivation, and vitality, were applied after the sessions and game performance was assessed. Results showed that both environments were positively evaluated for all the dependent variables, regardless of the positive distractions and the sensation-seeking traits. However, game performance was affected by the environment and the participants’ sensation-seeking traits, suggesting that the additional distractions can reduce performance and that individual differences also seem to impact performance. info:eu-repo/semantics/acceptedVersion

The paper presents a simulation tool that emulates the development environment of Foundation Fieldbus (FF) applications. The idea is to use the resources provided by LabVIEW®—in particular its dataflow programming paradigm—to design, execute, and debug FF control applications. Function blocks are implemented as virtual instruments, data links are represented by virtual wires, and bus monitoring tools are replaced by application debugging tools. The simulator can easily be connected to virtual (simulated) processes or to physical (real) processes. Tests were made to evaluate the capabilities of the simulator and to assess its degree of fidelity against commercial FF systems. The goal was to release an easy-to-use, low-cost training tool to disseminate knowledge about process control using the FF technology. info:eu-repo/semantics/publishedVersion

WOS:000341527800011 (Nº de Acesso Web of Science) The new era of mobile health ushered in by the wide adoption of ubiquitous computing and mobile communications has brought opportunities for governments and companies to rethink their concept of healthcare. Simultaneously, the worldwide urbanization process represents a formidable challenge and attracts attention toward cities that are expected to gather higher populations and provide citizens with services in an efficient and human manner. These two trends have led to the appearance of mobile health and smart cities. In this article we introduce the new concept of smart health, which is the context-aware complement of mobile health within smart cities. We provide an overview of the main fields of knowledge that are involved in the process of building this new concept. Additionally, we discuss the main challenges and opportunities that s-Health would imply and provide a common ground for further research.

WOS:000346338500031 (Nº de Acesso Web of Science) The challenges of climate change, population growth, demographic change, urbanization and resource depletion mean that the world's great cities need to adapt to survive and thrive over the coming decades. Slashing greenhouse gas emissions to prevent catastrophic climate change, while maintaining or increasing quality of life, can be a costly and difficult process. Two factors that directly affect the life quality in the XXI century cities are the water and air quality that can be monitored using the combination of low cost sensing modules, machine to machine (M2M) and internet of things (IoT) technologies. In this context, this study presents a wireless sensor network architecture that combines low cost sensing nodes and a low cost multi-parameters sensing probe for reliable monitoring of water quality parameters of surface waters (lakes, estuaries and rivers) in urban areas. A particular attention is dedicated to the design of the conductivity, temperature and turbidity signal conditioning circuits, highlighting important issues related to linearisation, measuring dynamic range and low-cost implementation by using commercial off-the-shelf components and devices. Several issues related to the wireless sensor network implementation are included in this study, as well as several simulation and experimental results.

The purpose of the paper is to report mainly the work developed in the areas of distributed instrumentation and geographic information systems for dolphins' environment assessment. A smart sensing node mounted in a buoy expressed by eater quality transducers, a low cost hydrophone materialize ans a GPS deliver the informations for an acquisition and wireless communication module that is connected through Wi-Fi to a laptop PC that is installed in a ship. Using the internet available connection (3G/UMTS modern is installed on the laptop PC) the data from different sensing nodes are transmitted to a host PC where specific software implemented materializing the geographic information system dor dolphin life assessment (GIS). Thus, on-line environment assessment through dynamic web pages is carried out.