Clinical Screening Interview Using a Social Robot for Geriatric Care

Abstract

Social robots are coming to our homes and have already been used to help humans in a number of ways in geriatric care. This article aims to develop a framework that enables social robots to conduct regular clinical screening interviews in geriatric care, such as cognitive evaluation, falls’ risk evaluation, and pain rating. We develop a social robot with essential features to enable clinical screening interviews, including a conversational interface, face tracking, an interaction handler, attention management, robot skills, and cloud service management. Besides, a general clinical screening interview management (GCSIM) model is proposed and implemented. The GCSIM enables social robots to handle various types of clinical questions and answers, evaluate and score responses, engage interviewees during conversations, and generate reports on their well-being. These reports can be used to evaluate the progression of cognitive impairment, risk of falls, pain level, and so on by caregivers or physicians. Such a clinical screening capability allows for early detection and treatment planning in geriatric care. The framework was developed and implemented on our 3-D-printed social robot. It was tested on 30 older adults with different ages, achieved satisfying results, and received their high confidence and trust in the use of this robot for human well-being assessment. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the goal of using a social robot to perform geriatric well-being assessment through clinical screening interviews. In order to conduct clinical screening interviews, the social robot needs the following essential features: having a verbal conversational interface, adapting to different types of clinical screening interviews, scoring and evaluating answers, having nondirective listening responses, and enabling directive listening responses. The proposed general clinical screening interview management (GCSIM) model demonstrates these capabilities on the social robot. The robot can give structured clinical screening interviews with different question–answer sheets. This will help advance assistive technologies for use by geriatric physicians, nurses, and social service professionals to keep older adults healthy, safe, and independent at home. Robots will become more and more essential in working alongside geriatric practitioners to help monitor older adults at home and to provide early detection and warning of cognitive/mental health problems, falls’ risk, and so on. This early detection property can improve quality-of-care and help older adults remain living at home.