The use of innovative technology in the field of Speech and Language Therapy (SLT) has gained significant attention nowadays. Despite being a promising research area, Socially Assistive Robots (SARs) have not been thoroughly studied and used in SLT. This paper makes two main contributions: firstly, providing a comprehensive review of existing research on the use of SARs to enhance communication skills in children and adolescents. Secondly, organizing the information into tables that categorize the interactive play scenarios described in the surveyed papers. The inclusion criteria for play scenarios in the tables are based only on their effectiveness for SLT proven by experimental findings. The data, systematically presented in a table format, allow readers to easily find relevant information based on various factors, such as disorder type, age, treatment technique, robot type, etc. The study concludes that the despite limited research on the use of social robots for children and adolescents with communication disorders (CD), promising outcomes have been reported. The authors discuss the methodological, technical, and ethical limitations related to the use of SARs for SLT in clinical or home environments, as well as the huge potential of conversational Artificial Intelligence (AI) as a secondary assistive technology to facilitate speech and language interventions.

Contemporary technologies, such as mainstream and specialised Assistive Technologies (ATs), are seen as effective. However, there is a noticeable gap between technological progress and the ability to customise these technologies to meet the unique needs and characteristics of neurodivergent individuals, particularly those on the Autism Spectrum and people with Intellectual Disability (pwID). The goal of this study is to investigate the present requirements and future priorities acknowledged by specialists in the field regarding the progress of social inclusion for this population, making use of ATs. A qualitative survey involving 24 international experts, and its respective thematic analysis reveals challenges in social inclusion, emphasizing communication and physical accessibility, awareness gaps, and stigma. Concurrently, issues surrounding ATs include limited access, insufficient training, and a lack of awareness and skills, with individuals, and families being inadequately involved. The study proposes strategies for overcoming these challenges, with a focus on accessibility, awareness, skills, family involvement, and customization. Identified research needs encompass scientific development, inclusive approaches, and changes in technological development paradigms.

Advancements in Assistive Technologies (ATs) have significantly improved the quality of life and autonomy for people with intellectual disabilities and autistic individuals, enhancing education, social interaction, employment, and mental health. Nevertheless, several barriers still emerge in the daily implementation of such technologies, highlighting the need to explore them in depth. Using a two-round Delphi method, we conducted a research study with an expert panel of 284 participants from 31 European countries, collecting quantitative and qualitative data. We tested ten future-oriented projections and gathered insights on participants’ backgrounds and attitudes towards ATs for this demographic. To enhance representation, experts from academia, service providers, industry, and disability organizations, as well as individuals with disabilities and their families, were included. Although the findings show strong consensus among experts on the positive impact and desirability of ATs for promoting the social inclusion of people with intellectual disabilities and autistic individuals, they also reveal differing perceptions across expert groups and identify two distinct future scenarios linked to different cultural, social, and economic hindrances. In this sense, our study provides diverse global perspectives, with the potential to help governing bodies understand the expectations, concerns, and needs related to ATs for often underrepresented groups–people with intellectual disabilities and autistic individuals in this case.

The humanoid robot NAO is widely used in therapy scenarios for children with neurodevelopmental disorders, however it has poor speech recognition and dialog based on a predefined lexicon that results in limited vocabulary and limited number of predefined dialog scenarios. The integration of Conversational Artificial Intelligence (AI) in NAO can significantly enhance and expand the robot's capabilities for intensive speech and listening exercises for children with speech and language disorders. Applying design-based research, the authors present the ongoing effective iteration in the building-testing cycles of a software architecture for Conversational AI in the robot NAO by integrating different AI cloud services for NLP into NAO's native software. Examining the aims and methods of stakeholders interested in integrating Conversational AI in NAO for speech and language therapy, we revealed several technical and ethical challenges. These challenges were successfully addressed with solutions implemented in the Node-RED platform, such as achieving more accurate and speech recognition, generating human-like text based on a context, and implementing multilingual text-to-speech synthesis. Additionally, implementation raises ethical considerations for both developers and therapists, especially regarding the assessment of risks linked with AI systems. We followed the guidelines set in the European AI Act, which categorizes AI systems according to their associated risk levels.

In the era of artificial intelligence and rapidly advancing robotics, the field of Human–Robot Interaction (HRI) has taken center stage across multiple domains, including psychology. From a psychological perspective, it is therefore essential to deepen our understanding of the factors that shape the quality of these interactions and their implications. This emphasis also aligns with the principles of Industry 5.0, which prioritize human well-being and use technologies to promote sustainable progress. The present study employs an exploratory mixed-method approach and aims to examine perceptions of warmth, competence and discomfort with the Furhat social robot in a psychological assessment setting. Specifically, we investigated young adults’ interactions with the Furhat social robot while it administered the Depression, Anxiety and Stress Scale (DASS-21). Following the interaction, the participants completed the short version of the Robot Social Attributes Scale (RoSAS-SF) to assess perceived warmth, competence and discomfort, and provided qualitative feedback regarding their interactional experiences and acceptance of the robot. The findings provide preliminary insights into the respondents’ perceptions of and openness toward robot-administered psychological screening, suggesting that the Furhat social robot may have potential as an assistive tool in mental health assessment contexts. These results highlight the need for further research with larger samples to examine the role of social robots in psychological practice more comprehensively.

Brain health is a critical part of well-being because it is a foundation for the ability to communicate, make decisions and solve real-life problems. Virtual reality games involve motor and sensory activities that can help to improve brain connectivity by providing an immersive and interactive experience that engages multiple brain regions simultaneously. Reinforcing sensorimotor activities influences cognitive skills and improves brain health. Sensorimotor play in virtual reality is a relatively new concept that is gaining attention as a tool for promoting brain health and cognitive abilities. It is believed that this type of play can have positive impact on brain health and cognitive function, such as improving memory, enhancing focus, and reducing stress and anxiety. The aims of the current paper are (1) – to present evidence, based on neuro correlates, of the importance of the sensorimotor play to the brain health and (2) – to propose a conceptual model for a personalized VR game design using neurocognitive feedback obtained through Brain-Computer Interface that assesses brain areas during sensorimotor stimulation.