The World Health Organization estimates that 970 million people around the world live with a mental disorder. However, new developments in Social Robotics and Artificial Intelligence hold great promise to revolutionize mental healthcare. Social robots are commonly designed to interact with humans, for instance, by means of having a conversation or showing emotions. Such interaction can be leveraged by using (data-centric) artificial intelligence. Examples of social robots using artificial intelligence can be found in education, elderly care, and healthcare. In fact, there is evidence that social robots can be used as a tool for implementing therapies oriented toward improving people's mental health. However, at the intersection of social robotics, artificial intelligence, and mental healthcare, there are still many open challenges and opportunities to be faced.
The complexity and pervasiveness of anxiety, depression, and disruptive behaviors, among other mental disorders, require new studies, methods, and approaches considering the social implications of mental disorders, the currently available data, and the feasibility of collecting health-related data.
In this sense, research at the intersection of social robotics and data-centric artificial intelligence may shed new light on (i) how to improve intervention mechanisms for patients with mental disorders, (ii) how to diagnose them at early stages, and (iii) how to treat and characterize such mental disorders. The objective of this Research Topic is to consolidate and present novel contributions at the intersection of social robotics and artificial intelligence with applications to mental health disorders.
This Research Topic invites researchers and practitioners to submit articles presenting theoretical and applied research, computational models, case studies, innovative applications, and systematic reviews characterizing the current state of the art. Areas of interest include, but are not limited to:
1) Social robots for mental health care.
2) AI in social robots for mental health care.
3) Affective computing models for social robotics.
4) Cognitive architectures for social robots in mental health care.
5) Human-robot interaction studies in the context of mental health care.
6)Artificial intelligence models for social robotics.
7) Characterization and diagnosis of mental health disorders based on human-robot interaction.
8) Social robots for interventions in mental health disorders.
9) Diagnosis and treatment of mental health disorders using social robots.
10) NLP and LLMs for social robotics and mental health.
11) Generative artificial intelligence for social robotics.
12) Data-based human social behavior modeling for human-robot interaction.
13) Privacy and ethical issues for social robotics in mental health care.
Keywords:
Artificial Intelligence, Social Robots, Cognitive Systems, Affective computing, Mental Healthcare.
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The World Health Organization estimates that 970 million people around the world live with a mental disorder. However, new developments in Social Robotics and Artificial Intelligence hold great promise to revolutionize mental healthcare. Social robots are commonly designed to interact with humans, for instance, by means of having a conversation or showing emotions. Such interaction can be leveraged by using (data-centric) artificial intelligence. Examples of social robots using artificial intelligence can be found in education, elderly care, and healthcare. In fact, there is evidence that social robots can be used as a tool for implementing therapies oriented toward improving people's mental health. However, at the intersection of social robotics, artificial intelligence, and mental healthcare, there are still many open challenges and opportunities to be faced.
The complexity and pervasiveness of anxiety, depression, and disruptive behaviors, among other mental disorders, require new studies, methods, and approaches considering the social implications of mental disorders, the currently available data, and the feasibility of collecting health-related data.
In this sense, research at the intersection of social robotics and data-centric artificial intelligence may shed new light on (i) how to improve intervention mechanisms for patients with mental disorders, (ii) how to diagnose them at early stages, and (iii) how to treat and characterize such mental disorders. The objective of this Research Topic is to consolidate and present novel contributions at the intersection of social robotics and artificial intelligence with applications to mental health disorders.
This Research Topic invites researchers and practitioners to submit articles presenting theoretical and applied research, computational models, case studies, innovative applications, and systematic reviews characterizing the current state of the art. Areas of interest include, but are not limited to:
1) Social robots for mental health care.
2) AI in social robots for mental health care.
3) Affective computing models for social robotics.
4) Cognitive architectures for social robots in mental health care.
5) Human-robot interaction studies in the context of mental health care.
6)Artificial intelligence models for social robotics.
7) Characterization and diagnosis of mental health disorders based on human-robot interaction.
8) Social robots for interventions in mental health disorders.
9) Diagnosis and treatment of mental health disorders using social robots.
10) NLP and LLMs for social robotics and mental health.
11) Generative artificial intelligence for social robotics.
12) Data-based human social behavior modeling for human-robot interaction.
13) Privacy and ethical issues for social robotics in mental health care.
Keywords:
Artificial Intelligence, Social Robots, Cognitive Systems, Affective computing, Mental Healthcare.
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.