Comparison of Healthcare Workers Transferring Patients Using Either Conventional Or Robotic Wheelchairs: Kinematic, Electromyographic, and Electrocardiographic Analyses

Author:

Matsumoto Hiromi1,Ueki Masaru2,Uehara Kazutake2,Noma Hisashi3,Nozawa Nobuko2,Osaki Mari1,Hagino Hiroshi14

Affiliation:

1. Rehabilitation Division, Tottori University Hospital, Nishi-cho 36-1, Yonago, Tottori 683-8504, Japan

2. Center for Promoting Next-Generation Highly Advanced Medicine, Tottori University Hospital, Nishi-cho 36-1, Yonago, Tottori 683-8504, Japan

3. Department of Data Science, The Institute of Statistical Mathematics, Midori-cho 10-3, Tachikawa, Tokyo 190-8562, Japan

4. School of Health Science, Faculty of Medicine, Tottori University, Nishi-cho 86, Yonago, Tottori 683-8503, Japan

Abstract

Objectives. The aim of this study was to compare the musculoskeletal and physical strain on healthcare workers, by measuring range of motion (ROM), muscle activity, and heart rate (HR), during transfer of a simulated patient using either a robotic wheelchair (RWC) or a conventional wheelchair (CWC).Methods. The subjects were 10 females who had work experience in transferring patients and another female adult as the simulated patient to be transferred from bed to a RWC or a CWC. In both experimental conditions, ROM, muscle activity, and HR were assessed in the subjects using motion sensors, electromyography, and electrocardiograms.Results. Peak ROM of shoulder flexion during assistive transfer with the RWC was significantly lower than that with the CWC. Values for back muscle activity during transfer were lower with the RWC than with the CWC.Conclusions. The findings suggest that the RWC may decrease workplace injuries and lower back pain in healthcare workers.

Funder

Ministry of Education, Culture, Sports, Science, and Technology

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3