Abstract

Older adults with dementia are increasing in Japan. Because of this, “communication robots” are being introduced into nursing settings to substitute for the shortage of nurses and other care workers. Our research group is currently developing a humanoid nursing robot with caring function (HNR), specifically for the functional and practical use of older adults with dementia. The purpose of this study was to clarify improvement points of the current function of humanoid robot’s (Pepper) (SoftBank Robotics) dialog pattern for improving optimal communication between humanoid robot and older adults. Dialog programs were installed in the humanoid robot Pepper, including the application program Care Prevention Gymnastics Exercises for Pepper (Pepper-CPGE) that was made by Xing Company, Japan. Dialogues between older adults and Pepper-CPGE were recorded by video camera. Data from transcriptions of the conversations captured from video and from field notes were analyzed focusing on human-robot interaction. From the recorded scenes and conversations, the following were points to be improved: 1) Intonation of the words vocalized by Pepper-CPGE was different from that expected by the older adult resulted in inappropriate responses by the older adult; 2) The timing between Pepper’s questions and the responses of the older adult were not timely and did not match (differences in the question-response time), which lead to confusion among the older adults; and 3) Other surroundings older adults were interested in the dialogue with Pepper-CPGE. However, Pepper-CPGE cannot communicate with multiple older adults. ImprovingPepper-CPGE’s ability to communicate with multiple older adults as an older adult’s dialogue with Pepper-CPGE can cause other older adults to also interact not only with the older adult that Pepper-CPGE is interacting with but also with Pepper-CPGE. This study shows that transactive relations among humanoid robots and older adults can be facilitated. Improving communication between humanoid robots and the older adults by optimizing a structured dialogue is needed to enhance appropriate engagement and participation. It is necessary to create a “Caring dialogue Database” for HNRs in order to know the patient/client and to share the aesthetic experiences of human-robot interactions. Also, it is important to develop a dialog pattern that enables humanoid robots to sympathize with older adults.

Highlights

  • As the aging society with low birth rate progresses [1], elderly populations with dementia are increasing in Japan [2] [3], as well as the increasing burden of care for the elderly with dementia [4]

  • Dialog programs were installed in the humanoid robot Pepper, including the application program Care Prevention Gymnastics Exercises for Pepper (Pepper-CPGE) that was made by Xing Company, Japan

  • From the recorded scenes and conversations, the following were points to be improved: 1) Intonation of the words vocalized by Pepper-CPGE was different from that expected by the older adult resulted in inappropriate responses by the older adult; 2) The timing between Pepper’s questions and the responses of the older adult were not timely and did not match, which lead to confusion among the older adults; and 3) Other surroundings older adults were interested in the dialogue with Pepper-CPGE

Read more

Summary

Introduction

As the aging society with low birth rate progresses [1], elderly populations with dementia are increasing in Japan [2] [3], as well as the increasing burden of care for the elderly with dementia [4]. This phenomenon is observed in many developed countries all over the world [5]. Less opportunities for elderly dialogue cause risk for developing dementia [8]. Supportive communication is essential to promote good quality dementia care. Nurses and other care workers are decreasing or are in short supply [11] [12]; for this reason, “communication robots” have been introduced into nursing settings as an alternative for the shortage of nurses and other care workers to support caring for elderly [13]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call