인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Objective: The main objective of this study was to investigate the relationship between self-reported back pain severity and muscle recruitment patterns while conducting common physical exercises. Background: Non-specific low back pain has been one of major concerns in various occupational environments. Reliable and quantitative assessment of the severity of non-specific low back pain is important in injury prevention as well as rehabilitation of injured individuals. While self-reported questionnaires such as the Oswestry Low Back Disability questionnaire have been frequently used to assess the severity of non-specific low back pain, no quantitative and objective assessment tool or system has yet been developed. Method: Twenty seven participants who had low back pain symptoms were grouped into three groups by their Oswestry disability score (less than 22; 23-30; greater than 30), and participated in a laboratory experiment. Myoelectric signals (EMG) of the lumbar erector spinae muscles and abdominal muscles were collected from each participant during common physical exercises, including walking, plank, bird-dog, and isometric back extension. Mean amplitude of each muscle, bilateral difference between left and right side muscles, and co-contraction ratio between abdominal and low back muscles were compared between the three Oswestry score groups. Results: Significant differences between score groups were observed only from the bird-dog exercise. Greater bilateral difference of the L2 lumbar erector spinae muscles and smaller bilateral difference of the recturs abdominal muscles were observed from groups with higher Oswestry scores. Conclusion: Severity of non-specific low back pain could be quantitatively assessed from the evaluation of muscle recruitment patterns in non-symmetric exercises such as bird-dog. Application: Results of this pioneering study could be used to develop reliable and easyto-use low back health monitoring systems.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-ECN-0101-2016-530-002499432