The global trend of increasing life expectancy introduces new challenges with far-reaching implications. Among these, the risk of falls among older adults is particularly significant, affecting individual health and the quality of life, and placing an additional burden on healthcare systems. Existing fall detection systems often have limitations, including delays due to continuous server communication, high false-positive rates, low adoption rates due to wearability and comfort issues, and high costs. In response to these challenges, this work presents a reliable, wearable, and cost-effective fall detection system. The proposed system consists of a fit-for-purpose device, with an embedded algorithm and an Inertial Measurement Unit (IMU), enabling real-time fall detection. The algorithm combines a Threshold-Based Algorithm (TBA) and a neural network with low number of parameters based on a Transformer architecture. This system demonstrates notable performance with 95.29% accuracy, 93.68% specificity, and 96.66% sensitivity, while only using a 0.38% of the trainable parameters used by the other approach.

Across European countries, the SHAPES Project is piloting AI-based technologies that could improve healthcare delivery for older people over 60 years old. This article aims to present a study developed inside the SHAPES Project to find a theoretical framework focused on AI-assisted technology in healthcare for older people living in the home, to assess the SHAPES AI-based technologies using the ALTAI tool, and to derive ethical recommendations regarding AI-based technologies for ageing and healthcare. The study has highlighted concerns and reservations about AI-based technologies, namely dealing with living at home, mobility, accessibility, data exchange procedures in cross-board cases, interoperability, and security. A list of recommendations is built not only for the healthcare sector, but also for other pilot studies.

The successful adoption of assistive technologies for older adults requires considering and evaluating many different factors and dimensions such as effectiveness, usability, cost and equity of access, to name some of the most relevant. In line with this, the energy requirements to power such assistive technologies remains a hidden factor that might to some extent influence the success in their adoption and the user experience in a wider sense. Very often energy availability is taken for granted and its associated costs and operational requirements are mostly neglected. In this paper, the energy-related requirements of assistive technologies are analysed from a general perspective. This analysis is subsequently particularised for a use case within the SHAPES project, in the context of active and healthy ageing. This use case includes a wide variety of assistive technologies, namely: wearable devices, home sensors and a smart mirror, which provides connectivity and a set of software services. The energy requirements of all these technologies are evaluated and analysed to investigate their impact and relevance on the overall cost and user experience, following the proposed protocol.

Internet of Things cybersecurity is gaining attention as the number of devices installed in IoT environments is exponentially increasing while the number of attacks successfully addressed to these devices are also proliferating. Security concerns have, however, been mainly addressed to service availability and information integrity and confidentiality. Code integrity, on the other hand, is not receiving proper attention, mainly because of the limited resources of these devices, thus preventing the implementation of advanced protection mechanisms. This situation calls for further research on how traditional mechanisms for code integrity can be adapted to IoT devices. This work presents a mechanism for code integrity in IoT devices based on a virtual-machine approach. A proof-of-concept virtual machine is presented, specially designed for providing code integrity during firmware updates. The proposed approach has been experimentally validated in terms of resource consumption among the most-widespread micro-controller units. The obtained results demonstrate the feasibility of this robust mechanism for code integrity.

Overnight postural changes and surveillance are two important issues to provide assistance to older individuals particularly when there is reduced mobility and cognitive decline. This paper presents a preliminary analysis of a cost-effective monitoring system based on force sensing resistors, to provide assistance to caregivers and facilitate the prevention of falls and pressure ulcers. A prototype of the proposed solution is presented, and the preliminary tests and measurements obtained using a real setup in a nursing home are analysed. The solution based on force-sensing resistors seeks simplicity, reduced costs, unobtrusiveness and privacy preservation. The prototype consists of 3 force-sensing resistor strips installed under the mattress and microcontroller board with wireless connectivity, to record measurements, transfer data, perform local analysis and generate warning messages. The positioning of the sensors has been analysed during the test to achieve a successful identification of the most relevant in-bed postures. The proposed solution can also be employed to monitor daily activities and assess sleep quality in combination with other sensors such as inertial measuring units in wearable devices or cameras.

Life expectancy has increased, so the number of people in need of intensive care and attention is also growing. Falls are a major problem for older adult health, mainly because of the consequences they entail. Falls are indeed the second leading cause of unintentional death in the world. The impact on privacy, the cost, low performance, or the need to wear uncomfortable devices are the main causes for the lack of widespread solutions for fall detection and prevention. This work present a solution focused on bedtime that addresses all these causes. Bed exit is one of the most critical moments, especially when the person suffers from a cognitive impairment or has mobility problems. For this reason, this work proposes a system that monitors the position in bed in order to identify risk situations as soon as possible. This system is also combined with an automatic fall detection system. Both systems work together, in real time, offering a comprehensive solution to automatic fall detection and prevention, which is low cost and guarantees user privacy. The proposed system was experimentally validated with young adults. Results show that falls can be detected, in real time, with an accuracy of 93.51%, sensitivity of 92.04% and specificity of 95.45%. Furthermore, risk situations, such as transiting from lying on the bed to sitting on the bed side, are recognized with a 96.60% accuracy, and those where the user exits the bed are recognized with a 100% accuracy.

The increasing trend in the percentage of older people among the European population, and in the number of older people living alone, poses a number of challenges, some of which can be addressed from digital solutions monitoring and supporting comfort, physical activity and health. Nowadays, research efforts seek to ensure, through technology-based solutions, the quality of life as people age and the needs that arise during the process. The home environment can host modern home-automation solutions supporting information gathering, monitoring and early intervention to prevent risks to lead to major consequences. Smart homes can thus make a positive contribution to the Active and Healthy Ageing paradigm. However, one of the biggest limitations preventing smart homes from being a reality is the lack of interoperability among different-vendor devices or the fact that most of the commer-tial solutions rely on cloud-based solutions. This work faces these limitations and proposes an architecture that, based on the use of commercial sensors, ensures that information is gathered and processed locally, independently of the commercial solution provided by the manufacturer of the device. The architecture has been experimentally validated by implementing a monitoring system based on environmental and security sensors interconnected by means of the ZigBee wireless communication protocol. The proposed system also supports caregivers caring for their older people who will be granted access to collected data. Thus, the system offers a remote monitoring system based on an information storage and visualisation solution. This system is intended to provide a solution that improves the quality of life and extends the time of independent living at home for older people.

While the importance of physical activity in older adults is beyond doubt, there are significant barriers limiting the access of older adults to physical exercise. Existing technologies to support physical activity in older adults show that, despite their positive impacts on health and well-being, there is in general a lack of engagement due to the existing reluctance to the use of technology. Usefulness and usability are two major factors for user acceptance along with others, such as cost, privacy, equipment and maintenance requirements, support, etc. Nevertheless, the extent to which each factor impacts user acceptance remains unclear. Furthermore, other stakeholders, besides the end users, should be considered in the decision-making process to develop such technologies, including caregivers, therapists and technology providers. In this paper, and in the context of physical rehabilitation and exercise at home, four different alternatives with incremental characteristics have been defined and considered: a software-based platform for physical rehabilitation and exercise (Alternative 1), the same software platform with a conventional RGB camera and no exercise supervision (Alternative 2), the same software platform with a convention RGB camera and exercise supervision (Alternative 3) and finally, the same software platform with a depth camera and exercise supervision (Alternative 4). A multiple attribute decision-making methodology, based on the ordinal priority approach (OPA) method, is then applied using a group of experts, including end users, therapists and developers to rank the best alternative. The attributes considered in this method have been usefulness, cost, ease of use, ease of technical development, ease of maintenance and privacy, concluding that Alternative 3 has been ranked as the most appropriate.

Despite the technology advances in the field of virtual assistant and activity monitoring devices, older adults are still reluctant to embrace this technology, specially when it comes to employ it to manage health-related issues. This paper presents a work in progress for a virtual caregiver, based on the Internet of Thing paradigm, that employs different technological solutions for information gathering and intervention delivery. The ultimate goal of this virtual caregiver is to support people empowerment to actively contribute to frailty and multimorbidity management and risk mitigation. To this end, user acceptance and willingness to use the propose solution has to be ensured. This work in progress starts with the hypothesis that by embedding the proposed technology in a smart mirror device will improve user acceptance and willingness to use. This paper presents the vision and overall architecture and future work will address the evaluation of user acceptance and the use intention.

The main objective of this work is to determine whether social networks can be used to improve self-management skills in people with Intellectual or Developmental Disability (IDD) given the high rate of acceptance of such tools among them. The proposed methodology applies an employment-based intervention to evaluate whether social network services help improve self-management skills. A fit-for-purpose social networking service is built, and different evaluation mechanisms are applied to determine the degree to which users with IDD could use the tool without assistance. The working hypothesis is that in order to ensure the usability of the implemented tool, users (with and without IDD) should be involved throughout the whole software development cycle, following a co-design methodological approach. Results demonstrate that this methodological approach leads to high satisfaction and motivation rates. In terms of effectiveness and efficiency, results demonstrate that the tool is useful and usable for people with IDD. It can therefore be concluded that social network services built having users with IDD at its center will help improve their self-management skills. The main implication of this research is that when using social network services as a tool to support interventions, special attention should be paid to previously evaluating the usability and motivation rate as a measure of how autonomously the person with IDD can use the tool. Nevertheless, further research is needed to determine the impact that such tools can have on other types of intervention.

The benefits that technology can provide in terms of health and support for independent living are in many cases not enough to break the barriers that prevent older adults from accepting and embracing technology. This work proposes a hardware and software platform based on a smart mirror, which is equipped with a set of digital solutions whose main focus is to overcome older adults' reluctance to use technology at home and wearable devices on the move. The system has been developed in the context of two use cases: the support of independent living for older individuals with neurodegenerative diseases and the promotion of physical rehabilitation activities at home. Aspects such as reliability, usability, consumption of computational resources, performance and accuracy of the proposed platform and digital solutions have been evaluated in the initial stages of the pilots within the SHAPES project, an EU-funded innovation action. It can be concluded that the SHAPES smart mirror has the potential to contribute as a technological breakthrough to overcome the barriers that prevent older adults from engaging in the use of assistive technologies.

The general aim of a cognitive Cyber Physical System of Systems (CPSoS) is to provide managed access to data in a smart fashion such that sensing and actuation capabilities are connected. Whilst there is significant funding and research devoted to this area, focus remains purely on creating bespoke systems. This paper presents a novel approach, based on a set of components to leverage Situational Awareness and Smart Actuation in large manufacturing industries with the focus on enabling predictive maintenance for asset and abnormal situation management. This paper presents a novel generic platform, named AtiCoS, that combines case-based and common-sense reasoning, as the enabling methodologies for enhancing CPSoS with cognitive capabilities.

Nowadays, the amount of elder people living alone is increasing, with all the risks that it involves, maybe the most dangerous threat that they face is fall off with nobody around to help them. A fall at an advanced age usually leads to consequences like bones and hip fracture, which in addition to the low mobility that these people present, make to stand up impossible for them. This situation can get worse if after the fall a person loses consciousness, making it impossible to contact to a third party for help by means of a mobile phone or something similar. Different solutions have been developed in order to accomplish this problem, but some of them are not realistic enough, for example some video solutions invade our privacy, and those which are based on mobile phones expect the user to go everywhere with it. In this paper, it is proposed a low cost solution based on an 9-axis IMU (Inertial Measure Unit), which counts with an accelerometer, gyroscope and magnetometer that will give us the needed information to build a fall detector supported by machine learning. This system will include a gateway, which will be responsible of the data collection and the most complex computations.

The fields of robotics and game consoles offer an interesting and broad range of lab platforms with appropriate characteristics for teaching Computer Architecture concepts. This work analyzes the impact of one approach based on game consoles and another one based on robotics from a triple dimension: student motivation, acquired knowledge, and perception of the employed platform. The study has been carried out on a sample of 96 students using the Arduino-based robot and 75 students using the Nintendo-DS console. A mixed methodology is employed encompassing quantitative and qualitative approaches. Five instruments are used to measure the three aforementioned dimensions. Results show that despite both platforms performing similarly in the three considered dimensions (student motivation, acquired knowledge, and perception of the employed platform), the robotics platform does it slightly better than game console, based on the obtained average scores for the considered instruments. Despite this outperforming, motivation and perception decrease for the students using the robotics platform as result of some identified constraint. This suggests that changes are required in the organization of the lab sessions to promote teamwork skills and to overcome the lack of simulators to remove the obstacles hinting motivation and performance. However, a clear correlation between motivation and perception and acquired knowledge has not been identified on computer architecture. Implications of affordances and constraints of both platforms, types of activities, and their impact on results have been discussed.

Detecting emotions in a learning environment can make the student-learning process more efficient, avoiding stressful situations that might eventually lead to failure, frustation and demotivation. The work presented here describes a perceptive desktop devised to capture the sensations of any person facing learning activities. To this end, we propose a perceptive environment enhanced with capabilities to perform an analysis of electroencephalography, facial expression, eye tracking and particularly a very distinctive indicator of stress as it is the galvanic response of the skin. This work focuses on the galvanic response of the skin, comparing the performance of two devices in the context of the perceptive desktop. One of the devices was very attractive to our environment as it was a mouse that fit very well to our computer-based desktop, equipped with low-cost sensors to detect the galvanic response. The other device is more tedious to place and more expensive but we use it as a reference to know if the mouse is accurate. Four people were exposed to an experiment with the two devices connected, and observing the results it can be concluded that there is no correlation between the captures of both devices. Therefore, we could not select the mouse for our environment even though at first it looks like a very promising device.

People suffering from rheumatoid arthritis are normally prescribed with physical exercises. The realization of these exercise routines should be supervised to prevent wrongly adopted postures or bad movements that end up harming the affected articulations. The motivational component associated with a supervised session is also important. On the contrary, having access to qualified supervision is not always possible due to different reasons, such as tight schedules, limited mobility, or economic reasons. This article presents a system for at-home rehabilitation, based on Microsoft Kinect, that resembles the role played by the physiotherapist during the supervision of an exercise session. The system not only supervises the realization of exercises but it also collects and manages information about the exercise-session history. Additionally, and despite affecting young people, rheumatoid arthritis is a disease that mainly affects seniors. For this reason, the system provides a natural interface to ease the interaction. Finally, the performance of the proposed system has been evaluated using a three-dimensional dynamic measurement system as a gold standard to validate the accuracy of the measurements. Obtained results demonstrate the potential of the Kinect-based system for at-home rehabilitation exercise routines.

The Internet of Things (IoT) paradigm poses a great variety of application domains where million of devices work uninterruptedly to improve some aspect of our lives. To support the continuous execution of the applications working on the devices, energy harvesting systems enable to extract the energy found naturally in the environment (for instance from the sun or from the wind) and convert it into energy able to either sustain the device's operation and recharge its batteries which, in conjunction with an appropriate scheduling strategy, led to the device to an electrically sustainable state (i.e. an energy-neutral state). Most of the works found in literature oriented to achieve energy neutrality are however evaluated by means of simulation which means that, in spite of precisely modeling hardware features and energy productions, lack of the realism that we find in a real deployment. A minor part of the works are based on a real deployment but do not share the collected data that permit to replicate the analysis. With this purpose in mind, in this article we describe a testbed designed for outdoor monitoring purposes in the IoT context, equipped with several sensors for weather conditions monitoring and with a solar panel to provide application lifetimes potentially infinite. The testbed was deployed on the roof of a building and it executed uninterruptedly an application able to generate a dataset with the collected information over a period of more than two months. This dataset has been online published to be used for different researching purposes, as for instance, prediction models of the energy production.

Framed within the PLATINO research project we have prototyped an energy-harvesting device specifically designed for supporting a set of smart farming applications. To this purpose, our prototype is equipped, among other components, with several sensors for environmental and energy conditions monitoring and a LoRa communication module to enable a Low-Power Wide Area Network. The physical network will be composed of dozens of PLATINO devices acting as end-nodes and of a drone with limited time of flight acting as a mobile gateway, which will receive the data temporally stored on the end-devices. This paper analyzes the set of constraints imposed by the European LoRa regulations and by the drone itself to design an efficient communication protocol between the drone and the end-devices.

To make sustainable large IoT deployments in smart cities, a promising approach is to develop a new generation of solar energy harvesting IoT devices based on the concept of energy neutrality. Key to this concept are the models for the forecast of energy production, which provide input to the energy-neutral schedulers governing the activities of the IoT devices. The development of such models however need to be validated against real-world conditions. To this purpose we propose a testbed aimed at the collection of real-world dataset about the energy parameters of energy harvesting IoT devices, and, on the base of such a dataset, we perform a comparative assessment of state of the art and novel energy production forecast models.

Outdoor Internet of Things (IoT) applications usually exploit energy harvesting systems to guarantee virtually uninterrupted operations. However, the use of energy harvesting poses issues concerning the optimization of the utility of the application while guaranteeing energy neutrality of the devices. In this context, we propose a new dynamic programming algorithm for the optimization of the scheduling of the tasks in IoT devices that harvest energy by means of a solar panel. We show that the problem is NP-hard and that the algorithm finds the optimum solution in a pseudo-polynomial time. Furthermore, we show that the algorithm can be executed with a small overhead on three popular IoT platforms (namely TMote, Raspberry PI, and Arduino) and, by simulation, we show the behavior of the algorithm with different settings and at different conditions of energy production.