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1.
Artigo em Inglês | MEDLINE | ID: mdl-37966937

RESUMO

The development of artificial intelligence and virtual reality technology has enabled rehabilitation service systems based on virtual scenarios to provide patients with a multi-sensory simulation experience. However, the design methods of most rehabilitation service systems rarely consider the physician-manufacturer synergy in the patient rehabilitation process, as well as the problem of inaccurate quantitative evaluation of rehabilitation efficacy. Thus, this study proposes a design method for a smart rehabilitation product service system based on virtual scenarios. This method is important for upgrading the rehabilitation service system. First, the efficacy of rehabilitation for patients is quantitatively assessed using multimodal data. Then, an optimization mechanism for virtual training scenarios based on rehabilitation efficacy and a rehabilitation plan based on a knowledge graph are established. Finally, a design framework for a full-stage service system that meets user needs and enables physician-manufacturer collaboration is developed by adopting a "cloud-end-human" architecture. This study uses virtual driving for autistic children as a case study to validate the proposed framework and method. Experimental results show that the service system based on the proposed methods can construct an optimal virtual driving system and its rehabilitation program based on the evaluation results of patients' rehabilitation efficacy at the current stage. It also provides guidance for improving rehabilitation efficacy in the subsequent stages of rehabilitation services.


Assuntos
Inteligência Artificial , Realidade Virtual , Criança , Humanos , Simulação por Computador , Interface Usuário-Computador
2.
Artigo em Inglês | MEDLINE | ID: mdl-36901311

RESUMO

As China's urbanization process deepens, more and more residents of small and medium-sized cities are moving to large cities, and the number of left-behind children is increasing. In this paper, using data from the China Education Panel Survey (CEPS), a nationally representative survey sample, we examine the well-being of left-behind children with urban household registration at the junior high school level and the causal effects of parental migration on their well-being. Research findings indicate that children who are left behind in urban areas are at a disadvantage in most aspects of their well-being compared to urban non-left-behind children. We examine the determinants of urban household registration for left-behind children. Children in families with lower socioeconomic status, more siblings, and poorer health were more likely to be left behind. In addition, our counterfactual framework reveals that, on average, staying behind negatively impacts the well-being of urban children, based on the propensity score matching (PSM) method. Compared to non-migrant children, left-behind children had significantly lower physical health, mental health, cognitive ability, academic performance, school affiliation, and relationships with their parents.


Assuntos
Migrantes , Humanos , Criança , Características da Família , Inquéritos e Questionários , Relações Pais-Filho , China , População Rural
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