CHS: Large: Collaborative Research: Participatory Design and Evaluation of Socially Assistive Robots for Use in Mental Health Services in Clinics and Patient Homes

美国的一个重大问题涉及精神健康障碍，特别是抑郁症;美国国家精神卫生研究所（NIMH）估计，1730万18岁或以上的成年人（占美国成年人口的7.1%）在2017年至少有过一次重度抑郁发作该项目的主要目标是使患者和临床医生与研究人员合作，设计一种社交辅助机器人，为抑郁症提供支持，并作为缓解抑郁症症状的干预措施。这款名为Therabot的机器人目前以狗的形式出现，旨在作为宠物般的伴侣。该项目将允许患者和临床医生定制机器人的功能和行为，以改善患者的健康和福祉。改进后的机器人的有效性将在临床环境中进行评估，并在患者家中长期使用。项目成果将包括医疗机器人技术的进步和人机交互的改进，这要归功于机载传感器的组合，这些传感器为临床医生提供额外的信息，沿着人工智能，以定制机器人与患者的交互。这项活动也有望改变精神卫生保健干预措施，并通过允许许多患者在他们的辅助支持机器人的帮助下留在家中更长时间来降低心理健康问题的医疗保健成本。本研究课题是感兴趣的多样性的学生，以及临床医生，并将促进教育培训和机会，在科学，技术，工程和mathematics.This项目领域将采用分层设计（PD）的方法来开发一个适应社会辅助机器人平台，通过扩展Therabot的功能和能力。 将确定适当的治疗干预措施，并使用该平台评估其有效性，以满足被诊断患有抑郁症的个人的需求。主要的研究贡献是将PD方法应用于心理健康的社会辅助机器人，特别关注临床和家庭环境中的桥接治疗，进一步发展适应性强的机器人系统的技术，并为实验室外的长期互动提供交互式社会参与架构和工具包的扩展。该项目将开发PD活动，以扩展Therabot的设计，与现成的系统不同，Therabot可以进行修改，以适应不同患者和临床医生随着时间的推移不断变化的需求和偏好。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

A significant concern in the United States relates to mental health disorders, especially depression; the National Institute of Mental Health (NIMH) has estimated that 17.3 million adults aged 18 or older (7.1% of the adult population in the U.S.) had at least one major depressive episode in 2017. The primary goal of this project is to enable patients and clinicians working together with researchers to design a socially assistive robot to provide support for, and as an intervention to alleviate the symptoms of, depression. The robot, Therabot, currently takes the form of a dog and is intended to serve as a pet-like companion. The project will allow both patients and clinicians to customize the capabilities and behaviors of the robot in order to improve patient health and well-being. The effectiveness of the modified robots will be evaluated in clinical settings and by means of longer-term use in patient homes. Project outcomes will include advances in healthcare robotics and improvements in human-robot interaction, thanks to a combination of onboard sensors that provide additional information to clinicians along with artificial intelligence to customize the interactions of the robot with the patient. This activity is also expected to transform mental healthcare interventions, and to reduce healthcare costs for mental health concerns by allowing many patients to remain in their homes longer with the aid of their assistive support robot. This research topic is of interest to a diversity of students, as well as clinical practitioners, and will promote educational training and opportunities in the areas of science, technology, engineering, and mathematics.This project will employ Participatory Design (PD) methods to develop an adaptable socially assistive robot platform by extending the features and capabilities of Therabot. Appropriate therapeutic interventions will be identified and their effectiveness evaluated using this platform to address the needs of individuals diagnosed with depression. The main research contributions are to apply PD methods to socially assistive robots for mental health with particular focus on bridging therapy in clinical and home settings, to further the technical development of adaptable robotic systems, and to provide an extension to the Interactive Social Engagement Architecture and Toolkit for long-term interaction outside of the laboratory. The project will develop PD activities to expand the design of Therabot which, unlike off-the-shelf systems, can be amended to suit the changing needs and preferences of diverse patients and clinicians over time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.