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

논문 기본 정보

자료유형
학술저널
저자정보
Yeo, Sang Seok (Department of Physical Therapy, College of Health Sciences, Dankook University)
저널정보
대한물리치료학회 대한물리치료학회지(JKPT) 대한물리치료학회지 제29권 제6호
발행연도
2017.1
수록면
303 - 306 (4page)

이용수

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

초록· 키워드

오류제보하기
Purpose: Gait variability is defined as the intrinsic fluctuations which occur during continuous gait cycles. Increased gait variability is closely associated with increased fall risk in older adults. This study investigated the influence of attention-demanding tasks on gait variability in elderly healthy adults. Methods: We recruited 15 healthy elderly adults in this study. All participants performed two cognitive tasks: a subtraction dual-task (SDT) and working memory dual-task (WMDT) during gait plus one normal gait. Using the $LEGSys^+$ system, we measured the coefficient of variation (CV %=$100{\times}$[standard deviation/mean]) for participants' stride time, stride length, and stride velocity. Results: SDT gait showed significant increment of stride time variability compared with usual gait (p<0.05), however, stride length and velocity variability did not difference between SDT gait and usual gait (p>0.05). WMDT gait showed significant increment of stride time and velocity variability compared with usual gait (p<0.05). In addition, stride time variability during WMDT gait also significantly increased compared with SDT gait (p<0.05). Conclusion: We reported that SDT and WMDT gait can induce the increment of the gait variability in elderly adults. We assume that attention demanding task based on working memory has the most influence on the interference between cognitive and gait function. Understanding the changes during dual task gait in older ages would be helpful for physical intervention strategies and improved risk assessment.

목차

등록된 정보가 없습니다.

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

최근 본 자료

전체보기

댓글(0)

0