Did Anyone Say BINGO: A Socially Assistive Robot to Promote Stimulating Recreational Activities at Long-Term Care Facilities
Wing-Yue Geoffrey Louie, Runqi Han, Goldie Nejat
- 发表年份
- 2013
- 引用次数
- 7
摘要
One of greatest health threats to our aging population is cognitive decline, which can be a result of the natural aging process as well as more severe disorders such as dementia and hypertension [1]. Recent studies have demonstrated that non-pharmacological interventions such as participation in leisure activities, including general socialization, physical exercise, and/or cognitively stimulating activities (reading, playing board games and Bingo, playing musical instruments, doing crossword puzzles, etc.), are associated with a reduced risk of cognitive decline in the elderly [2]. For example, the group activity of Bingo has been shown to improve confrontational naming, memory, recall, and recognition in cognitively impaired older adults in adult day care centers [3]. Bingo also has physical and social benefits as it focuses on implementing accurate motor patterns when placing game pieces on the card and can also facilitate social interactions between the players themselves [3].However, the current state of long-term care facilities has shown that there is a need for increased staff-to-resident ratios to support and sustain recreational activities due to residents being understimulated [4]. Increased activity levels have been shown to reduce functional decline and mortality, and improve the moods of the elderly [5]. Although there exists a demand for more staff to incorporate such activities, it is projected that the supply of health care workers will substantially decrease as they too are aging and a large number of them will retire in the next several years [6]. Therefore, there is a need to investigate the use of technological solutions as alternative measures in order to improve the quality of care and quality of life of residents in long-term care facilities. For example, assistive robots can be integrated into long-term care facilities to assist with conducting and monitoring group recreational activities. Robot guided activities have already shown to aid in improving memory, social skills, cognitive attention, and the moods of the elderly, i.e., [7,8].Our work focuses on developing a unique autonomous socially assistive robot to facilitate group recreational activities such as Bingo in long-term care facilities to provide cognitive stimulation to the elderly, Figure 1(a). With respect to the game of Bingo, the socially assistive robot will monitor the actions of multiple elderly users to provide assistance when necessary or requested. In particular, the robot's assistive behaviors include: 1) calling out the Bingo numbers, 2) repeating to players, when needed, the numbers that have been already called out, 3) prompting players to mark the correct numbers on their card, and 4) verifying winning Bingo cards and celebrating with the Bingo winners. For the game, we have designed multiple number cards each marked with a unique identification symbol and a 5 × 5 grid of large easy to read numbers, Figure 1(b). Players mark the numbers that are called out by the robot by placing red circular markers on these numbers on their cards. The objective of the game is to obtain 5 consecutive numbers either in a row, column, or diagonal configuration in order to win the game and call out BINGO!A Creative 10MP webcam mounted on the head of the robot is used to monitor game progress and verify winning cards via a card identification and localization approach. The robot is being designed to provide game assistance by either: 1) actively navigating the game area and monitoring the Bingo cards of players, or 2) by directly responding to a player's raised hand. Each identification symbol on the cards has unique Speeded-Up Robust Features (SURF) [9], which can therefore be used by the robot to recognize a card of interest. Namely, the SURF feature vectors are determined on a captured image of the Bingo card and matched to a database which contains the SURF features for each of the identification symbols using a k-Nearest Neighbor algorithm [1
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