This study evaluates different levels of proactivity in socially assistive robots (SARs) within elderly care, focussing on user acceptance and comfort. Using the mPLiCA model, we categorise proactive behaviours from basic presence to full autonomy. A series of video scenarios was created to represent varying degrees of proactive interactions with SHARA, a socially assistive robot. Participants rated these scenarios based on usefulness, appropriateness, perceived intrusiveness and naturalness. Results indicate that higher levels of proactivity are perceived as more useful but also more intrusive. Intermediate levels, particularly dialogue-based interactions, were the most acceptable. This research offers insights into designing SARs that balance autonomy and user comfort in elderly care, contributing to the development of more effective assistive technologies.

Children with Autism Spectrum Disorder (ASD) often experience difficulties with tactile sensory processing, which can hinder their participation in daily activities and therapeutic interventions. To address this challenge, we introduce Twinkle Trace, a haptic interface designed to support engagement in classroom-based sensory activities. The system combines a crayon-like stylus, a tablet application to simulate crayon rubbing on textured surfaces using customizable vibration patterns inspired by familiar fruit textures: smooth (apple), rough (melon), bumpy (corn), sharp (pineapple) and adhesive (banana). Twinkle Trace includes a variety of interactive activities, such as free drawing, shape coloring, tactile scene coloring, tracing, and bubble popping, commonly used to promote sensory and fine motor control. We conducted a four-week classroom deployment study with six children with ASD using a comparison within-subjects against traditional crayon rubbing on textured surfaces. Therapist-rated engagement scores showed consistent directional trends favoring Twinkle Trace sessions over traditional activities, particularly in satisfaction, completion, and transitioning. Therapists progressively integrated the tool into daily routines, adapting it to weekly themes and individual needs. These findings suggest that embedding vibrotactile feedback within structured classroom exercises is associated with increased engagement and therapist appropriation in real-world special education contexts. Twinkle Trace provides a classroom-ready haptic system that integrates digital texture generation with therapeutic interaction design.

Affective computing enables robots to understand, interpret, and respond to human emotions, and this is fundamental to creating more natural, human-like interactions.In healthcare, emotionally intelligent robots can reduce patient anxiety and improve treatment outcomes by providing empathic interactions.In educational settings, these robots can be used to create learning environments that are adaptive to students' emotions, enhancing the educational experience.Despite the good results presented in the literature with the use of affective social robots, their full use in the areas of education and healthcare has often been hindered due to their high cost.In addition, there is a need for open-source robotic platforms that can be customized according to the needs and resources of human-robot interaction (HRI) researchers, developers, and target users.This thesis presents a proposal for an open-source robotics framework and platform and the development of affective social robots, which includes a new affective social robot named FRED.It is an open-source affective human-robot interaction (AHRI) research platform.This platform can help HRI researchers conduct studies with social robots, especially those aimed at answering affective robotics-related questions involving affective understanding and affective generation.To serve as a proof of concept, the proposed framework was instantiated in two real-world scenarios on two different robotic platforms.Finally, we run an experiment with FRED using the framework as a research instrument in HRI.

Replicating real-world textures using haptic technology poses significant challenges, particularly in accurately capturing complex tactile qualities such as smoothness, roughness, and sharpness through vibration-based information. This research investigates how vibration parameters, intensity, duration, and off-time, can be manipulated to simulate textures inspired by fruit skins, including smooth-apple, rough-melon, bumpy-corn, sharp-pineapple, and adhesive-banana. Using a user-centered design methodology, we developed five vibrotactile patterns and implemented them within the Cactus Mobile Haptic Interface. The patterns were delivered via two interaction devices, a thimble and a stylus pen, designed to enable touch-based activities and tactile experiences. An empirical study with 36 participants evaluated those devices within three tasks: Tolerance to 10-second exposures, change perception, and the ability to associate patterns with real-world textures. Results showed that most patterns were accurately classified (76% with the thimble and 78% the stylus), although the adhesive texture proved more difficult to identify. Rough and sharp textures received slightly lower comfort ratings. While there were notable confusions between similar patterns, such as the sharp–bumpy pair, the type of interaction device did not significantly affect classification accuracy. These findings highlight the potential of low-cost haptic interfaces to mimic sensations from natural, realistic textures and emphasize the importance of refining vibration design for improved perceptual clarity. This work contributes to the development of accessible, portable, and customizable haptic systems designed for sensory interaction in therapeutic, educational, and interactive environments. Future research will focus on refining ambiguous patterns and exploring sensory integration to expand the system’s usability in tactile therapy.

People with dementia (PwD) often exhibit behavioral, physiological, and social symptoms that affect their relationships and reduce their quality of life. Socially assistive robots (SARs) have proven effective in reducing some of these symptoms. However, the design of SARs for dementia care remains a challenging task. In this article, we present a human-centered design framework to assist researchers, designers, and roboticist from the conceptualization of engaging prototypes of SARs until the assessment of their efficacy at producing dementia-relevant health outcomes. The framework incorporates several key principles of a Human-Centered Artificial Intelligence (HCAI) approach. It incorporates the needs and perspectives of the different stakeholders into the design and evaluation of the interactions. It fosters accessibility and inclusion through personalization and encourages human–robot collaboration by facilitating natural and engaging interactions that build trust and rapport. We illustrate the use of the framework with the design of an SAR to support a Cognitive Stimulation Therapy. From this case study, we derive a set of design insights for the development of SARs behaviors and interactions for dementia care.

Socially Assistive Robots (SARs) have successfully been used in various types of health therapies as non-pharmacological interventions. A SAR called EVA (Embodied Voice Assistant) is an open-source robotics platform intended to serve as a tool to support research in Human-Robot Interaction. The EVA robot was originally developed to assist in non-pharmacological interventions for people with Dementia and has more recently been applied for children with Autism Spectrum Disorder. EVA provides multimodal interactions such as verbal and non-verbal communication, facial recognition and light sensory effects. Although EVA uses low-cost hardware and open-source software, it is not always possible, or practical, to have a physical robot at hand, particularly during rapid iterative cycles of design and evaluation of therapies. Thus, our motivation to develop a simulator that allows testing the scripts of therapies to be enacted by the EVA robot. This work proposes EvaSIM (EVA Robot Simulator), a simulator that can interpret an EVA script code and emulate the multimodal interaction capabilities of the physical robot, such as Text-To-Speech, facial expression recognition, controlling light sensory effects, etc. Several EVA scripts were run using the simulator attesting that they have the same behaviour as the physical robot. EvaSIM can serve as a support tool in the teaching/learning process of the robot’s scripting language, enabling the training of technicians and therapists in script development and testing for the EVA robot.

Several studies have been reported on the use of social robots for dementia care. These robots have been used for diverse tasks such as for companionship, as an exercise coach, and as daily life assistant. However, most of these studies have assessed impact on participants only at the time when the interaction takes place rather than their medium or long-term effects. In this work, we report on a nine-week study conducted in a nursing home in which a autonomous social robot, called Eva, acts as facilitator of a cognitive stimulation therapy (CST). During the study, eight persons with dementia interacted with the robot in a group session which included elements of music therapy, reminiscence, cognitive games, and relaxation. Using the Neuropsychiatric Inventory - Nursing Home version (NPI-NH), we analyzed the impact of the therapy guided by the robot. The results show a statistically significant decrease in the total score of NPI-NH. Also, three dementia-related symptoms: delusions, agitation/aggression, and euphoria/exaltation, show a statistically significant decrease after the intervention. In addition, a qualitative analysis on interviews conducted with caregivers shows that all participants exhibits positive short-term effects after the session and provides insights on why some changes in behavior prevailed beyond the therapy sessions. Our results provide evidence that a social robot could play a role in improving the quality of life of persons with dementia.

The increasing adoption of mobile personal devices and Internet of Things devices is leveraging the emergence of a wide variety of opportunistic sensing applications. However, the designers of this type of applications face a set of technical challenges related to the limitations and heterogeneity of the hardware and software platforms and to the dynamics of the scenarios where they are deployed. In this paper, we introduce a Semantic‐Centric Fog‐based framework aimed at effectively and efficiently supporting this type of applications. The proposed framework is composed of local and distributed algorithms that support the establishment and coordination of sensing tasks in the Fog. First, it performs ontology‐driven in‐network processing to locate the most adequate devices to carry out a given sensing task and then, it establishes efficient multihop routes that are used to coordinate relevant devices and to transport the collected sensory data to Fog sinks. We present a set of theorems that prove that the proposed algorithms are correct and the results of a series of detailed simulation‐based experiments in NS3 that characterize the performance of the proposed platform. The results show that the proposed framework outperforms traditional sensing platforms that are based on centralized services.

As the number of older adults increases, and with it the demand for dedicated care, geriatric residences face a shortage of caregivers, who themselves experience work overload, stress, and burden. We conducted a long-term field study in three geriatric residences to understand the work conditions of caregivers with the aim of developing technologies to assist them in their work and help them deal with their burdens. From this study, we obtained relevant requirements and insights to design, implement, and evaluate two prototypes for supporting caregivers’ tasks (e.g., electronic recording and automatic notifications) in order to validate the feasibility of their implementation in situ and their technical requirements. The evaluation in situ of the prototypes was conducted for a period of 4 weeks. The results of the evaluation, together with the data collected from 6 months of use, motivated the design of a predictive schedule, which was iteratively improved and evaluated in participative sessions with caregivers. PRESENCE, the predictive schedule we propose, triggers real-time alerts of risky situations (e.g., falls, entering off-limits areas such as the infirmary or the kitchen) and informs caregivers of routine tasks that need to be performed (e.g., medication administration, diaper change, etc.). Moreover, PRESENCE helps caregivers to record caring tasks (such as diaper changes or medication) and well-being assessments (such as the mood) that are difficult to automate. This facilitates caregiver's shift handover and can help to train new caregivers by suggesting routine tasks and by sending reminders and timely information about residents. It can be seen as a tool to reduce the workload of caregivers and medical staff. Instead of trying to substitute the caregiver with an automatic caring system, as proposed by others, we propose our predictive schedule system that blends caregiver assessments and measurements from sensors. We show the feasibility of predicting caregiver tasks and a formative evaluation with caregivers that provides preliminary evidence of its utility.

We present an approach for personalizing nonpharmacological interventions for people with dementia (PwD) using ontologies. We conducted two case studies to derive an ontological model to personalize the planning and execution of interventions to address problematic behaviors. The paper describes how the ontology was derived, and illustrates how it is used to tailor an ambient-assisted intervention system (AAIS) at two stages: first, to decide on the services that the AAIS will offer the PwD, and then to adapt these services at runtime using contextual information. The results of a deployment of an AAIS during 2 months in the home of a PwD, indicate that the AAIS successfully addressed some of the problematic behaviors exhibited by the PwD, helping to reduce the burden of the caregiver.

Healthy older adults experience physical and sensory performance decrease, reducing their interest in exercising and leading to a sedentary lifestyle. This increases natural decay, diseases, isolation and risk of falls and eventually death. Active-play video gaming, also referred as exergaming, might motivate positive changes in health behavior. However, such games need to take into account the physical characteristics of players and can also be used to foster their social ties. In this paper, we present a long-term intervention, using Action Research, aimed at developing insights for the design of full-body motion-control exergames for older adults experiencing age-related changes addressing problems raised by their motion capacity. The results of our study establish which physical characteristics need to be monitored to adapt gameplay, and other elements of social gameplay and spectator-centered design. Based on our study we present guidelines for the design of full-body interaction in exergames for older adults.

As SNS become ubiquitous, users are exploiting SNS content to enrich in-person gatherings. In this paper we present the results of a 26-weeks deployment study of an interactive display involving a lightweight Facebook client, and a movement-based social exergame, to explore how this technology impact in-person interactions with one extended family. Our results indicate that the use of the display is semi-public, and catalyzed opportunistic gatherings. We close discussing how the social implications of our results contribute to the use of public social displays, and its social implications for encouraging people to be socially engaged.

This paper presents the InCense research toolkit to facilitate researchers with little or no technical background to implement a sensing application for mobile phones. To reach this end, InCense provides a GUI and an interactive ontology to enable users to define the configuration of the sensing application, i.e. what sensing components to add, and the flow of the sensing session. We illustrate the ease of use of the InCense platform through a scenario in which both opportunistic and participatory sensing paradigms are used.

Ambient videogames can be used for frequent continuous monitoring of older adults in order to detect early signs of frailty. In this paper we propose a general architecture for health monitoring through ambient videogames and illustrate its instantiation with the development of two ambient casual games that have been designed to measure arm muscle strength utilizing a custom-designed interaction device that provides a natural user interface for the games. The games are designed to be used frequently and for short periods of time. We conducted a formative evaluation of the games with 5 older adults to assess ease of use and their interest in playing them. We compare the results of traditional measures of muscle strength using a clinical dynamometer with those obtained using the videogame.

We describe the use of a technique aimed at allowing users to realistically experience novel mobile applications in a naturalistic environment as part of the formative evaluation of the system. This technique, that we have named naturalistic enactment, is appropriate for application scenarios that are not easily replicated in a laboratory setting and might cause risks to users or other stakeholders if used at a prototyping stage, as is often the case in the healthcare domain. We present and discuss the use of this technique after the recent introduction of a mobile application aimed at assisting geriatric nurses in attending emergency calls. The technique provided nurses with the experience of operating the mobile application in a naturalistic environment (e.g., high ecological validity), thus allowing them to identify adoption issues that they would have missed otherwise.

Taking care of an elder with cognitive decline is not an easy task. Given their condition, elders could be involved in situations that may affect their physical integrity or quality of life, and caregivers may be unaware of the situation or not be able to attend it on time. This paper proposes a context-aware notification environment to support the work of caregivers. The aim is to increase the caregiver's awareness about the situations of care of older people in a nursing home, so that caregivers could act appropriately and timely to attend those situations. Firstly, we present the results of a study to understand the situations of care that occur at a nursing home. Later, we propose the design of a context-aware notification environment whose design was informed by this understanding. One of the main features of this environment is that it takes into consideration the contextual information both from the caregiver and from the elder in order to adapt the notification. Preliminary results of the evaluation of an implementation with an audio notification mechanism are promising. During the evaluation period caregivers perceived an increase in their awareness of the situations of care and a safer working environment regarding the provided quality of care.

The difficulties associated with the evaluation of ubiquitous computing (Ubicomp) technologies increase in application domains such as hospitals, where human life can be at risk, privacy of personal records is paramount, and labor is costly and highly distributed across space and time. For the last 6 years numerous Ubicomp technologies in support of hospital work have been created and pilot-tested. In this article, the lessons learned from these evaluations are discussed, using two criteria to classify them. The first criterion is ecological validity, namely, the extent to which the evaluation is conducted under realistic conditions. Alternatives range from controlled experiments to in situ evaluations. The article argues in particular for the advantages of intermediate approaches, which is referred to as in silico and in replica. The second criterion relates to the degree of integration of the technology with the environment, which is referred to as its pervasiveness. The evaluation grid that comes out of this exercise highlights the importance of ecological validity in evaluating ambient computing technology that supports the activities conducted in complex health care settings such as hospitals. This provides a framework for evaluating Ubihealth, which can be used to select appropriate techniques as a function of the technological and environmental complexity as well as to devise novel evaluation techniques.

Informal communication is an essential resource in hospital work; it is used as a means to collaborate and coordinate the way in which work is performed, as well as to locate and gather the artifacts and human resources required for patient care. The need of physical proximity to establish and hold informal communications has motivated the development of tools that support remote informal interaction. However, this kind of technology has not been widely adopted in hospitals, where workers experience intense mobility. In this paper, we present the results of an observational study in a hospital aimed at understanding how local mobility changes the rules in the provision of support for informal communication, and how technology could improve this form of communication. We found that local mobility fosters opportunities for colocated communication; however, it faces some inconveniences related to the affordances of the physical environment. We address these issues through the design of SOLAR, a collaborative application that supports colocated interactions in hospital work through the implementation and integration of five services that form a ubicomp infrastructure. Additionally, we present a discussion about the perception of users related to the usefulness of this tool.

This article presents an abstract structure capturing the essence of a mobile shared workspace (MSW), and how a particular MSW can be obtained by instantiating such structure. It is intended to assist designers of mobile groupware tools to conceive new products reusing other designers' knowledge. This approach facilitates the design of a particular MSW in an easy and fast way. We illustrate how the abstract structure can be instantiated in the development of MSWs to support hospital work and construction inspection activities.

Knowledge is a key asset in software engineering. Facilitating access to the knowledge that software engineers require for the task at hand can therefore bring many benefits. To accomplish this, it is important to understand how knowledge flows through the organization, to identify problems that may hinder a suitable flow, and to define strategies with which to address them. Process modeling has proved to be a useful technique for analyzing knowledge flows. Traditional process modeling languages do not, however, provide primitives to explicitly represent the knowledge involved in the processes within the models. In this paper, we illustrate how the Software Process Engineering Metamodel (SPEM) can be adapted, to be used as a process modeling language for analyzing knowledge flows in software processes. We have extended SPEM to represent knowledge and its sources in process models in an explicit way. We also discuss the experiences obtained from using this extension in a software organization and the lesson we have learned from it.

Collaborative applications enhanced with pervasive technology are gradually being introduced in hospitals to support the intense collaboration and coordination experienced by hospital workers. However, an environment filled with many different systems introduces an extra burden for hospital workers in selecting those services that are adequate to the task at hand. Activity-Based Computing has emerged as a new interaction and design paradigm to reorganize the way humans interact with computers by emphasizing the activity being executed rather than the technologies required to perform such activity. This is done by allowing users to handle activities as a basic computational unit instead of documents and applications. The problem of this paradigm is that humans must explicitly define computational activities and they often have trouble labeling and delimiting tasks. To cope with this, we propose to take this vision one step further by binding the physical, computing and user's context into the activity being executed by a user towards the design of activity-aware applications. Based on a workplace study conducted in a hospital, we propose an agent-based architecture and a set of design principles to let human activities be mirrored in computational activities associating resources and adapting the computational infrastructure based on the activity being executed. To exemplify the architecture and the principles proposed, we implemented an activity-aware map that personalizes the information shown to hospital workers, enforces availability, and sends collaboration and coordination warnings to the users.

The nature of a context-aware application in hospital work demands a reliable and accurate location system. The activity for which this location information is needed determines to a great extent the relevancy of this contextual variable, since a minor error in delivering patient-based information can be critical. In this correspondence, we present an enhanced technique to infer the location of users in a hospital setting based on the strength of radio-frequency signals received by mobile devices that are used to train a neural network. The approach uses the neighbors surrounding the location to be estimated to track users continuously. This neighborhood eases the training and is used to simulate previous time instant guesses to reduce the location estimation error and alleviate the hopping trajectories of users. The results obtained by using this approach are in the order of 1.3 m for the average distance error during continuous motion.

The Mexico Research Centre of the Web Intelligence Consortium was established in 2003 motivated by Mexico being selected as the host of the 2nd Atlantic Web Intelligence Conference. It currently has 18 members including faculty and doctoral students from 7 different institutions. The WIC-Mexico includes groups working in the areas of Intelligent Web Information Retrieval, Web Mining and Farming, Knowledge Management, and Agents in Ubiquitous Computing.

Hospitals are convenient settings for deployment of ubiquitous computing technology. Not only are they technology-rich environments, but their workers experience a high level of mobility resulting in information infrastructures with artifacts distributed throughout the premises. Hospital information systems (HISs) that provide access to electronic patient records are a step in the direction of providing accurate and timely information to hospital staff in support of adequate decision-making. This has motivated the introduction of mobile computing technology in hospitals based on designs which respond to their particular conditions and demands. Among those conditions is the fact that worker mobility does not exclude the need for having shared information artifacts particular locations. In this paper, we extend a handheld-based mobile HIS with ubiquitous computing technology and describe how public displays are integrated with handheld and the services offered by these devices. Public displays become aware of the presence of physicians and nurses in their vicinity and adapt to provide users with personalized, relevant information. An agent-based architecture allows the integration of proactive components that offer information relevant to the case at hand, either from medical guidelines or previous similar cases.

Hospital workers are highly mobile; they are constantly changing location to perform their daily work, which includes visiting patients, locating resources, such as medical records, or consulting with other specialists. The information required by these specialists is highly dependent on their location. Access to a patient's laboratory results might be more relevant when the physician is near the patient's bed and not elsewhere. We describe a location-aware medical information system that was developed to provide access to resources such as patient's records or the location of a medical specialist, based on the user's location. The system is based on a handheld computer which includes a trained backpropagation neural-network used to estimate the user's location and a client to access information from the hospital information system that is relevant to the user's current location.