About this Research Topic
For the last few decades, the population of patients with neurological issues such as depression or dementia has been constantly increasing and we are currently witnessing this increase worldwide. WHO reported that approximately 280 million people in the world have depression symptoms and more than 55 million people live with dementia. Furthermore, since the COVID-19 pandemic began, medical workers have been affected by the stressful situation and over-workload. Thus, currently, new forms of healthcare technologies such as telemedicine or telehealth systems supporting booking consultation, arranging in-person examination appointments, or allowing for remote diagnosis, have been developed more actively. In particular, robots or virtual avatars have been gradually installed in clinics or nursing homes as a supporting system allowing for a fast, personalized, and reactive medical approach toward patients.
Both verbal and non-verbal cues are generally used for communication, and our cognitive and mental situations reflect on them, thus combined with a human-computer interaction system and monitoring verbal and non-verbal cues are used as the main indicators to detect neurological issues. However, there are still challenges in developing user-friendly support systems for patients with neurological issues; which biometric data would be able to detect neurological issues, especially in the early stage; what kind of systems are patient-friendly; which type of systems are easy to install on daily life; what kind of tasks would help to avoid developing the symptoms
The goal of this Research Topic is to accelerate the development and discovery of supporting systems for patients with neurological disorders, in particular depression and dementia, supported by robots or virtual avatars systems based on human-machine interactions. Further knowledge is needed and novel technologies or proposed workflows and/or methodologies and protocols would be beneficial to advance the development of novel experimental setups and strategies allowing for a smooth and efficient interaction with technologies aiding patients with monitoring their disorders and planning targeted medical support.
We welcome articles addressing the following:
Strategy user-friendly human-computer interaction
1. Natural/friendly human-computer interaction systems: methods
2. Effect of computer assistants on patients with mental/neurological issues
Detecting neurological/mental issues
1. Sensing verbal or on-verbal information in human-computer interaction
2. Prediction of early mental/neurological disorders
3. Detecting the level of neurological/mental disorders
Both verbal and non-verbal cues are generally used for communication, and our cognitive and mental situations reflect on them, thus combined with a human-computer interaction system and monitoring verbal and non-verbal cues are used as the main indicators to detect neurological issues. However, there are still challenges in developing user-friendly support systems for patients with neurological issues; which biometric data would be able to detect neurological issues, especially in the early stage; what kind of systems are patient-friendly; which type of systems are easy to install on daily life; what kind of tasks would help to avoid developing the symptoms
The goal of this Research Topic is to accelerate the development and discovery of supporting systems for patients with neurological disorders, in particular depression and dementia, supported by robots or virtual avatars systems based on human-machine interactions. Further knowledge is needed and novel technologies or proposed workflows and/or methodologies and protocols would be beneficial to advance the development of novel experimental setups and strategies allowing for a smooth and efficient interaction with technologies aiding patients with monitoring their disorders and planning targeted medical support.
We welcome articles addressing the following:
Strategy user-friendly human-computer interaction
1. Natural/friendly human-computer interaction systems: methods
2. Effect of computer assistants on patients with mental/neurological issues
Detecting neurological/mental issues
1. Sensing verbal or on-verbal information in human-computer interaction
2. Prediction of early mental/neurological disorders
3. Detecting the level of neurological/mental disorders
Keywords: mental disorders, human-computer interface, supporting systems, virtual avatars, robots, dementia, depression
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.
