메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술대회자료
저자정보
신을수 (인제대학교) 김유창 (동의대학교)
저널정보
대한산업공학회 대한산업공학회 춘계공동학술대회 논문집 2015년 대한산업공학회 춘계공동학술대회 논문집
발행연도
2015.4
수록면
2,783 - 2,788 (6page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

이 논문의 연구 히스토리 (4)

초록· 키워드

오류제보하기
This study is designed to figure out the level of Functional Movement Screen (FMS) of 122 automobile manufacturing workers and to set the FMS score for predicting risk for musculoskeletal disorders.
Although today’s industrial sites have been becoming automated rapidly, the risks of work-related musculoskeletal disorders (WMSDs) have been on the rise. In the case of WMSDs, it is I mportant to care in the early stage. Early detection of WMSDs is very important for the successful treatment. However, the medical examination puts agreat financial burden on most workers. To reduce their burden, there are one tests to check the musculoskeletal functional condition and to predict the risk of injury, which are called FMS.
For the 122 subjects, the average score of FMS is 14.63±2.27. There is a negative correlation between FMS and their ages and BMI(p<0.05), however, FMS does not affected by their working years. Also, FMS is irrelevant to job satisfaction, intensity of labor, and working proficiency. There is no difference in the level of FMS among working groups, and it is not affected by drinking and smoking. However, FMS is higher when exercising regularly(p<0.05). The FMS scores of musculoskeletal disorder patients are lower that those of normal patients(p<0.05). While it is more likely to become a musculoskeletal disorder patient when FMS is less than 14, it is more likely to become a normal patient when more than or equal to 14.
According to this study, therefore, FMS can be expected to have positive effect on prevention of WMSDs in working sites.

목차

Abstract
1. 서론
2. 방법
3. 연구결과
4. 결론 및 고찰
참고문헌

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2016-530-001314441