Search Results (235)

Currently, high-tech assistive technologies (ATs), particularly Socially Assistive Robots (SARs), virtual reality (VR) and conversational AI (ConvAI), are considered very useful in supporting professionals in Speech and Language Therapy (SLT) for children with communication disorders. However, despite a positive public perception, therapists face difficulties when integrating these technologies into practice due to technical challenges and a lack of user-friendly interfaces. To address this gap, a design-based research approach has been employed to streamline the integration of SARs, VR and ConvAI in SLT, and a new software platform called “ATLog” has been developed for designing interactive and playful learning scenarios with ATs. ATLog’s main features include visual-based programming with graphical interface, enabling therapists to intuitively create personalized interactive scenarios without advanced programming skills. The platform follows a subprocess-oriented design, breaking down SAR skills and VR scenarios into microskills represented by pre-programmed graphical blocks, tailored to specific treatment domains, therapy goals, and language skill levels. The ATLog platform was evaluated by 27 SLT experts using the Technology Acceptance Model (TAM) and System Usability Scale (SUS) questionnaires, extended with additional questions specifically focused on ATLog structure and functionalities. According to the SUS results, most of the experts (74%) evaluated ATLog with grades over 70, indicating high acceptance of its usability. Over half (52%) of the experts rated the additional questions focused on ATLog’s structure and functionalities in the A range (90–100), while 26% rated them in the B range (80–89), showing strong acceptance of the platform for creating and running personalized interactive scenarios with ATs. According to the TAM results, experts gave high grades for both perceived usefulness (44% in the A range) and perceived ease of use (63% in the A range). Full article

Children with physical disabilities are increasingly using socially assistive robots (SARs) as part of therapy to enhance motivation, engagement, enjoyment, and adherence. Research on SARs in rehabilitation has primarily focused on verbal and visual interaction, but little is known about tactile interaction (physical touch). The objective of this scoping review was to examine empirical studies published between 2010 and 2024 focusing on tactile interaction between SARs and children with physical disabilities, such as cerebral palsy (CP). Nine studies were identified as being eligible after a rigorous selection process, showing that although touch-based SAR interventions have been used in pediatric rehabilitation, structured methodologies and standardized tools are lacking for measuring tactile engagement. In light of the studies’ findings, it is evident that few studies evaluate the therapeutic effects of touch-sensitive SARs, underscoring the need for validated frameworks to assess their efficacy. In this review, SAR and tactile sensing researchers, rehabilitation specialists, and designers are given critical insights into how tactile interaction can enhance the role of SARs in physical therapy. Full article

We present here an approach to the deployment of social robots in a science laboratory to monitor the behavior of students with respect to safety regulations to prevent accidents. Our vision is that the social robot should act as a friendly companion for students and encourage them to follow safe laboratory practices. Towards this goal, we developed a Laboratory Safety Assistant Framework (LSA) using a Misty II Plus robot and designed three dashboards within it as interventions. This LSA framework was evaluated using a participatory design (PD) study with twenty university students (eleven from Japan and nine from Egypt). For this study, we designed a questionnaire that contains 42 questions on the prior knowledge of students about socially assistive robots and their expectations about how socially assistive robots can create a secure environment in the scientific laboratory. The chi-square test revealed that there are no differences between groups in their perceptions of using Misty II to achieve safety inside science laboratories. In their perception of the capabilities of social robots and the sharing of feelings, students believe that using social robots like Misty II inside the science laboratory can make the lab safe and decrease risk inside the science laboratory without using the three dashboards of the LSA framework. However, the Wilcoxon signed-rank test revealed that there is a significant improvement in students’ perceptions ((Median = 106.5, Z = −2.39, p < 0.05, r = 0.53)) between students’ expectations of using social robots to achieve safety in scientific laboratories before and after they interacted with the social robot and knew about the feasibility of the three dashboards we designed. Furthermore, the t-test revealed participants’ experiences of sharing feelings with a social robot, and the intervention suggested by the LSA framework was to design a system integrating this into a social robot to enhance safety within the scientific laboratory (t (19) = 3.39, p = 0.003). Full article

Social robots in Ambient Assisted Living (AAL) environments offer a promising alternative for enhancing senior care by providing companionship and functional support. These robots can serve as intuitive interfaces to complex smart home systems, allowing seniors and caregivers to easily control their environment and access various assistance services through natural interactions. By combining the emotional engagement capabilities of social robots with the comprehensive monitoring and support features of AAL, this integrated approach can potentially improve the quality of life and independence of elderly individuals while alleviating the burden on human caregivers. This paper explores the integration of social robotics with ambient assisted living (AAL) technologies to enhance elderly care. We propose a novel framework where a social robot is the central orchestrator of an AAL environment, coordinating various smart devices and systems to provide comprehensive support for seniors. Our approach leverages the social robot’s ability to engage in natural interactions while managing the complex network of environmental and wearable sensors and actuators. In this paper, we focus on the technical aspects of our framework. A computational P2P notebook is used to customize the environment and run reactive services. Machine learning models can be included for real-time recognition of gestures, poses, and moods to support non-verbal communication. We describe scenarios to illustrate the utility and functionality of the framework and how the robot is used to orchestrate the AAL environment to contribute to the well-being and independence of elderly individuals. We also address the technical challenges and future directions for this integrated approach to elderly care. Full article

Large Language Models (LLMs), particularly those enhanced through Reinforcement Learning from Human Feedback, such as ChatGPT, have opened up new possibilities for natural and open-ended spoken interaction in social robotics. However, these models are not inherently designed for embodied, multimodal contexts. This paper presents a user-centred approach to integrating an LLM into a humanoid robot, designed to engage in fluid, context-aware conversation with socially isolated older adults. We describe our system architecture, which combines real-time speech processing, layered memory summarisation, persona conditioning, and multilingual voice adaptation to support personalised, socially appropriate interactions. Through iterative development and evaluation, including in-home exploratory trials with older adults (n = 7) and a preliminary study with young adults (n = 43), we investigated the technical and experiential challenges of deploying LLMs in real-world human–robot dialogue. Our findings show that memory continuity, adaptive turn-taking, and culturally attuned voice design enhance user perceptions of trust, naturalness, and social presence. We also identify persistent limitations related to response latency, hallucinations, and expectation management. This work contributes design insights and architectural strategies for future LLM-integrated robots that aim to support meaningful, emotionally resonant companionship in socially assistive settings. Full article

Background/Objectives: Minimally verbal autistic children face significant communication challenges, often unmet by traditional therapies. Social robots, like NAO, offer predictable, structured interactions that may improve engagement and language skills. This study aimed to evaluate the effectiveness of NAO-assisted therapy in improving communication and social interaction in minimally verbal autistic children compared to standard therapeutic approaches. Methods: In a single-blind, randomized, controlled study, 37 autistic children aged 4–12 years were assigned to either NAO-assisted therapy or standard speech therapy. Participants were assigned to either an NAO-assisted therapy group or a standard speech therapy control group. The intervention included 12 weekly 45 min sessions. Communication outcomes were measured using the Language Development Level Test (TVL) and mand request observations. Results: All 37 participants completed the 12 sessions without adverse events, highlighting the intervention’s feasibility and safety. Children in the NAO-assisted therapy group showed greater improvements in verbal communication (on average, 159 ± 49% more children exhibited improvement across verbal aspects (range: 107–284%; p < 0.001)) particularly in spontaneous communication, compared to the control group. The therapy also increased mand production (from 6.8 ± 4.3 in session 1 to 16.7 ± 7.7 in session 12; p < 0.001; average gain: 0.9 per session), demonstrating steady growth in communicative initiative. These findings underscore the structured and engaging nature of NAO-assisted therapy in supporting consistent progress in communication skills. Conclusions: NAO-assisted therapy is a promising, safe, and effective intervention for enhancing communication in minimally verbal autistic children, offering unique benefits in promoting spontaneous and consistent verbal engagement. Full article

Artificial intelligence (AI) and assistive robotics can transform older-person care by offering new, personalised solutions for an ageing population. This paper outlines recent advances in AI-driven applications and robotic assistance in silver care, emphasising their role in improved healthcare services, quality of life and ageing-in-place and alleviating pressure on healthcare systems. Advances in machine learning, natural language processing and computer vision have enabled more accurate early diagnosis, targeted treatment plans and robust remote monitoring for elderly patients. These innovations support continuous health tracking and timely interventions to improve patient outcomes and extend home-based care. In addition, AI-powered assistive robots with advanced motion control and adaptive response mechanisms are studied to support physical and cognitive health. Among these, companion robots, often enhanced with emotional AI, have shown potential in reducing loneliness and increasing connectedness. The combined goal of these technologies is to offer holistic patient-centred care, which preserves the autonomy and dignity of our seniors. This paper also touches on the technical and ethical challenges of integrating AI/robotics into eldercare, like privacy and accessibility, and alludes to future directions on optimising AI-human interaction, expanding preventive healthcare applications and creating an effective, ethical framework for eldercare in the digital age. Full article

Background: This study performed an evaluation of technology acceptance of the therapeutic system E-BRAiN (Evidence-Based Robot Assistance in Neurorehabilitation) by stroke survivors receiving therapy with the system. Methods: The evaluation was based on a 49-item questionnaire addressing technology acceptance (I) with its constituents, i.e., perceived usefulness, perceived ease of use, perceived adaptability, perceived enjoyment, attitude, trust, anxiety, social influence, perceived sociability, and social presence (41 items), and (II) more general items exploring user experience in terms of both technology acceptance (3 items) and usability (5 open-question items). Results: Eleven consecutive sub-acute stroke survivors who had received either arm rehabilitation sessions (n = 5) or neglect therapy (n = 6) led by a humanoid robot participated. The multidimensional “strength of acceptance” summary statistic (Part I) indicates a high degree of technology acceptance (mean, 4.0; 95% CI, 3.7 to 4.3), as does the “general acceptance” summary statistic (mean, 4.1; 95% CI, 3.3 to 4.9) (art II) (scores ranging from 1, lowest degree of acceptance, to 5, highest degree of acceptance, with a score of 3 as neutral experience anchor). Positive ratings were also documented for all assessed constituents (Part I), as well as the perception that it makes sense to use the robot technology for stroke therapy and as a supplement for users’ own therapy (Part II). Conclusions: A high degree of technology acceptance and its constituents, i.e., perceived functionality and social behaviour of the humanoid robot and own emotions while using the system, could be corroborated among stroke survivors who used the therapeutic system E-BRAiN. Full article

The growing aging population has raised concerns about the treatment of age-related diseases, such as dementia. An emerging technology that could assist individuals with dementia is the development of social robots. However, interactions with these robots have been underexplored. This study aimed to examine the interactions between a robot cat and older adults with mild dementia during robotherapy sessions. Thirteen older adults with mild dementia who used a robot cat during robotherapy sessions in a day hospital in Spain were interviewed. Following semi-structured interviews, a thematic qualitative analysis of the data was conducted, revealing four main themes: (1) therapeutic effects of robotherapy (relaxation, mood improvement, cognitive stimulation, and increased social interaction); (2) preferences regarding the types of robotherapy activities; (3) interaction with the robot cat during the sessions; and (4) technological characteristics of the robot cat. Overall, the findings indicate positive interactions and suggest promising benefits for older adults with mild dementia participating in robotherapy with robot cats. Full article

Cognitive load refers to the mental resources used for executing simultaneous tasks. Since these resources are limited, individuals can only process a specific amount of information at a time. Daily activities often involve mentally demanding tasks, which is why social robots have been proposed to simplify them and support users. This study aimed to verify whether and how a social robot can enhance the performance and support the management of cognitive load. Participants completed a baseline where a cognitive activity was carried out without support, and three other conditions where similar activities of increasing difficulty were collaboratively made with the NAO robot. In each condition, errors, time, and perceived cognitive load were measured. Results revealed that the robot improved performance and perceived cognitive load when compared to the baseline, but this support was then thwarted by excessive levels of cognitive load. Future research should focus on developing and designing collaborative human–robot interactions that consider the user’s mental demand, to promote effective and personalized robotic help for independent living. Full article

The enactive approach offers a powerful theoretical lens for designing artificial intelligence (AI) systems intended to support the health and well-being of non-neurotypical individuals, including those on the autism spectrum and those with with ADHD, dyslexia, or other forms of neurodivergence. By emphasizing embodiment, relationality, and participatory sense-making, enactivism encourages AI-based interventions that are highly personalized, context-sensitive, and ethically aware. This paper explores how existing AI applications—ranging from socially assistive robots and virtual reality (VR) therapies to language-processing apps and personalized treatment planning—may be enhanced by incorporating enactivist principles. Despite their promise, practical adoption of AI technologies in real-world clinical practice remains limited, and persistent challenges such as algorithmic bias, privacy concerns, and the tendency to overlook subjective dimensions raise cautionary notes. Drawing on relevant philosophical literature, empirical studies, and cross-disciplinary debates (including the friction and potential synergies between predictive processing and enactivism), we argue that AI solutions grounded in enactivist thinking can more effectively honor user autonomy, acknowledge the embodied nature of neurodiverse cognition, and avoid reductive standardizations. This expanded, revised version integrates insights on neurodiversity, mental health paradigms, and the ethical imperatives of AI deployment, thereby offering a more comprehensive roadmap for researchers, clinicians, and system developers alike. Full article

Social robots designed to assist the elderly must function reliably in changing environments where usage conditions vary. Ensuring both reliability and readiness is crucial for effective daily interactions. This paper focuses on optimizing the operational processes of a social robot for elderly care. It presents a model that improves task planning and maintains consistent robot readiness. The study introduces an operational model that considers reliability, safety, and usability states. It applies Markov processes to predict transitions between usability states and assess readiness. It also proposes optimization methods to improve the robot’s readiness index. By addressing these aspects, the study enhances the efficiency and dependability of social robots, ultimately improving the quality of life for elderly and disabled users. Full article

As the interest in social and assistive support robots (SASRs) grows, a review of 17 systematic reviews was conducted to assess their use in healthcare, emotional well-being, and therapy for diverse populations, including older adults, children, and individuals with autism and dementia. SASRs have demonstrated potential in alleviating depression, loneliness, anxiety, and stress, while also improving sleep and cognitive function. Despite these promising outcomes, challenges remain in identifying the most effective interventions, refining robot designs, and evaluating long-term impacts. User acceptance hinges on trustworthiness and empathy-driven design. Compared to earlier review studies, recent research emphasizes the ongoing significance of emotional engagement, the refinement of robot functionalities, and the need to address ethical issues such as privacy and autonomy through robust cybersecurity and data privacy measures. The field is gradually shifting towards a user-centered design approach, focusing on robots as tools to augment, rather than replace, human care. While SASRs offer substantial benefits for emotional well-being and therapeutic support, further research is crucial to enhance their effectiveness and address concerns about replacing human care. Algorethics (AI ethics), interdisciplinary collaboration, and standardization and training emerge as key priorities to ensure the responsible and sustainable deployment of SASRs in healthcare settings, reinforcing the importance of rigorous methodologies and ethical safeguards. Full article

Traumatic brain injury (TBI) represents a significant public health issue, causing long-term disabilities and imposing considerable socioeconomic and healthcare challenges. While advancements in acute care have improved survival rates, the demand for effective neurorehabilitation is increasing. This narrative review explores the evidence on neurorehabilitation strategies for TBI, focusing on interventions targeting cognitive, motor, and psychological recovery. A total of 32 studies were included and categorized into six approaches: non-invasive brain stimulation, virtual reality (VR), computer-based training, telerehabilitation, robot-assisted therapy (RAT), and mixed approaches. Non-invasive brain stimulation techniques, such as transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), showed variable effectiveness in improving cognitive outcomes. VR-based therapies enhanced attention and executive functions, while RAT, such as Lokomat and exoskeletons, improved gait symmetry and functional mobility. Computer-assisted programs demonstrated benefits in rehabilitating social cognition and executive functions. Telerehabilitation and telephone-based treatments provided short-term gains but lacked sustained effects. Overall, cognitive improvements were better described and represented, while several motor improvements lacked consistency. Despite the promising results, significant gaps remain, including heterogeneity in methodologies, small sample sizes, and limited long-term outcome data. Full article

Background/Objectives: Pediatric cerebral palsy (CP) is a neurological disorder that affects motor skills, posture, and muscle coordination, impacting children’s daily functioning and quality of life. Treatment approaches in occupational therapy aim to enhance motor function and functional independence through a variety of rehabilitative techniques. Recently, new technologies—such as virtual reality, robotics, and assistive devices—have emerged as promising tools in occupational therapy to complement traditional interventions and potentially enhance motor and sensory outcomes in children with CP. This systematic review aims to analyze the effectiveness of these innovative technological interventions in the rehabilitation of children with CP. Methods: A systematic review was conducted and different scales were used to assess the risk of bias and methodological quality. The degree of evidence and level of recommendation were established according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). The review adhered to PRISMA guidelines, with a comprehensive literature search performed across multiple databases, including Cochrane, Web of Science, and PubMed. This systematic review has been registered in the PROSPERO database with the registration number CRD42025630162. Results: The reviewed studies indicate that technologies such as functional electrical stimulation, robotic assistance, and adaptive devices have shown improvements in mobility, motor control, posture, strength, and autonomy in children with CP. Similarly, virtual environments support the correction of facial dysfunctions and enhance social interaction through video games and social networks. While these tools hold significant potential for rehabilitation, further adjustments are needed to achieve more consistent results. Conclusions: Emerging technologies appear to be effective tools in occupational therapy for pediatric CP, with positive impacts on motor skills and functional capabilities. Nevertheless, further studies with larger sample sizes and rigorous methodological designs are necessary to confirm these findings and establish more robust evidence on their long-term efficacy. Full article