Literature DB >> 31987582

Pilot and Feasibility Study on Elderly Support Services Using Communicative Robots and Monitoring Sensors Integrated With Cloud Robotics.

Kazuko Obayashi1, Shigeru Masuyama2.   

Abstract

PURPOSE: This pilot before-after study investigated the possible effects of communicative robots, used with a sensing system supported by cloud robotics, in caring for elderly people.
METHODS: Two elderly women in nursing homes and 4 care workers participated in the trial. The overnight life rhythm assessments of the study participants and care workers were surveyed to determine when and how the robots should be integrated into care. The system consisted of the robot Sota, a noncontact vital sensor and a sheet-shaped bed sensor. Real-time sensing data and conversations between the participants and robots were sent to the servers, prompting a quick verbal response by the robot supported by cloud robotics.
FINDINGS: Care workers devoted 3 h to the maintenance of records during their most stressful periods. Automatic recording of vital information using robot sensors can improve the quality of nursing care work. Care workers' stress levels were maximized when responding to nurse calls. Temporary responses to nurse calls by the robots may help to effectively reduce the burden on nursing care workers. Robots can stimulate elderly people to communicate more with others (P < 0.05). Appropriate vocalization by communicative robots may prevent the deterioration of quality of life in elderly individuals. IMPLICATIONS: Communicative robots, used with a sensing system, may stimulate elderly people to activate a communication link with others and help care workers to effectively reduce the burden during the night shift. A follow-up study involving a broader research program on communicative robots and elderly care would be beneficial.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  activities of daily living; cloud robotics; communicative robot; elderly care; robotics utilization; support services

Year:  2020        PMID: 31987582     DOI: 10.1016/j.clinthera.2020.01.001

Source DB:  PubMed          Journal:  Clin Ther        ISSN: 0149-2918            Impact factor:   3.393


  4 in total

1.  Scenario-based dialogue system based on pause detection toward daily health monitoring.

Authors:  Kazumi Kumagai; Seiki Tokunaga; Norihisa P Miyake; Kazuhiro Tamura; Ikuo Mizuuchi; Mihoko Otake-Matsuura
Journal:  J Rehabil Assist Technol Eng       Date:  2022-10-13

Review 2.  6G and Artificial Intelligence Technologies for Dementia Care: Literature Review and Practical Analysis.

Authors:  Zhaohui Su; Barry L Bentley; Dean McDonnell; Junaid Ahmad; Jiguang He; Feng Shi; Kazuaki Takeuchi; Ali Cheshmehzangi; Claudimar Pereira da Veiga
Journal:  J Med Internet Res       Date:  2022-04-27       Impact factor: 7.076

3.  Artificial intelligence for older people receiving long-term care: a systematic review of acceptability and effectiveness studies.

Authors:  Kate Loveys; Matthew Prina; Chloe Axford; Òscar Ristol Domènec; William Weng; Elizabeth Broadbent; Sameer Pujari; Hyobum Jang; Zee A Han; Jotheeswaran Amuthavalli Thiyagarajan
Journal:  Lancet Healthy Longev       Date:  2022-04

4.  Comparison of the Mental Burden on Nursing Care Providers With and Without Mat-Type Sleep State Sensors at a Nursing Home in Tokyo, Japan: Quasi-Experimental Study.

Authors:  Sakiko Itoh; Hwee-Pink Tan; Kenichi Kudo; Yasuko Ogata
Journal:  JMIR Aging       Date:  2022-03-23
  4 in total

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