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

在美国，一个重要的问题与精神健康障碍有关，特别是抑郁症；国家精神健康研究所(NIMH)估计，18岁及以上的成年人有1730万(占美国成年人口的7.1%)。2017年至少有一次严重的抑郁发作。该项目的主要目标是使患者和临床医生能够与研究人员合作，设计一种社交辅助机器人，为抑郁症提供支持，并作为一种干预措施来缓解抑郁症状。这款机器人名为Therabot，目前以狗的形式出现，旨在充当宠物般的伴侣。该项目将允许患者和临床医生定制机器人的能力和行为，以改善患者的健康和福祉。改装后的机器人的有效性将在临床环境中进行评估，并通过在患者家中长期使用的方式进行评估。项目成果将包括医疗机器人技术的进步和人-机器人交互的改善，这要归功于向临床医生提供额外信息的机载传感器以及定制机器人与患者交互的人工智能的组合。这项活动还有望改变精神卫生保健干预措施，并通过允许许多患者在辅助支持机器人的帮助下在家中呆更长时间来降低因精神健康问题而产生的医疗保健成本。这一研究课题吸引了不同的学生和临床从业者，并将促进科学、技术、工程和数学领域的教育培训和机会。该项目将采用参与式设计(PD)方法，通过扩展Therabot的特性和功能来开发一个可适应的社交辅助机器人平台。将利用这一平台确定适当的治疗干预措施并评估其有效性，以满足被诊断为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交辅助机器人，特别侧重于临床和家庭环境中的桥梁治疗，进一步开发可适应的机器人系统，并为互动社会参与架构和工具包提供扩展，以便在实验室外进行长期互动。该项目将开发PD活动，以扩展Therabot的设计，与现成的系统不同，该系统可以进行修改，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智力优势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.