Brian 2.1: A Socially Assistive Robot for the Elderly and Cognitively Impaired

By Derek McColl, Wing-Yue Geoffrey Louie, and Goldie Nejat

NOTE: This is an overview of the entire article, which appeared in the March 2013 issue of the IEEE Robotics & Automation Magazine.
Click here to read the entire article.

On one hand, as the world’s elderly population continues to grow, more and more people have age-related cognitive impairments; at the same time, the available care needed to assist them is already lacking and shows a steady decline. Recent studies have supported the positive effects that cognitive training interventions can have on the cognitive functioning of older adults. The authors have stated,
The goal of our research is to advance knowledge in cognitive/social interventions for elderly individuals suffering from cognitive impairments via the development of robotic technology. We aim to design humanlike, socially assistive robots capable of providing cognitive assistance and social interaction in self-maintenance (i.e., eating, dressing, and grooming) and activities of daily living (i.e., cognitively and socially stimulating leisure activities). These robots focus on the core impairments of dementia and the ability to support working memory, attention, awareness, and focus on task behavior, to reduce a person’s dependence on caregivers and provide him/her social interaction during the course of these activities. Our long-term goal is to study how such robots can contribute to therapeutic protocols aimed at improving or maintaining residual social, cognitive, and global functioning in persons suffering from dementia.

Figure 1. The expressive, humanlike, socially assistive robot, Brian 2.1.Figure 1. The expressive, humanlike, socially assistive robot, Brian 2.1.

In this article, we present the development of our unique, expressive, humanlike, socially assistive robot, Brian 2.1 (Figure 1). Brian 2.1 can engage elderly individuals in both self-maintenance and cognitively stimulating leisure activities.

The robot has human-like functionalities from the waist up. Motion is possible in the neck, arms, waist, and face. Importantly for social interaction, the robot’s “face” is able to simulate emotional reactions. It has a synthesized voice for providing appropriate verbal suggestions to a participant. Sensors include IR and visual light cameras and some sensors outside the body for meal-eating assistance.

Brian 2.1 was used to determine whether an expressive robot could encourage residents of a long-term care facility to engage in activities and to express positive attitudes toward the robot. Over a two day period, residents (with a mix of congnitive impairment) interacted with Brian 2.1. Observers explained the robot, and recorded the degree and amount of interaction. They also obtained completed questionnaires from participants. The two activities that Brian 2.1 engaged in with residents were (a) meal-eating, where the robot provided comments and gestures to encourage eating, and (b) playing a card-matching game. Both of these activities are of therapeutic significance, since research has found that individuals with cognitive impairments who reside in nursing homes have low activity levels and are at a higher risk for understimulation because they lack the initiative to begin or sustain activities of daily living, including eating. The article explains in detail how the robot was equipped to engage in the two activities.

The questionnaire asked participants about their reaction to the robot and how positively they viewed the interaction. In addition, the observers noted for each interaction the degree to which participants engaged with the robot and how completely the participants complied with the robot’s requests. Overall, the article reports quite positive responses by participants. Most participants both engaged with and complied with the robots requests.

 

ABOUT THE AUTHORS

Derek McColl (derek.mccoll@mail.utoronto.ca) is with the Department of Mechanical and Industrial Engineering, University of Toronto, Canada.

Wing-Yue Geoffrey Louie (geoffrey.louie@mail.utoronto.ca) is with the Department of Mechanical and Industrial Engineering, University of Toronto, Canada.

Goldie Nejat (nejat@mie.utoronto.ca) is with the Department of Mechanical and Industrial Engineering, University of Toronto, Canada.