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      다국어 초록 (Multilingual Abstract)

      Portable low-cost Kinect sensor was used to analyze standing balance ability of the elderly. Eighty subjects who can walk alone and have a normal cognitive level participated in this experiment. Based on Berg Balance scale (BBS) test with 52 points, subjects were divided into Healthy older (HO: 46 persons, BBS: 53.80 ± 1.19) and Impaired older (IO: 34 persons, BBS: 49.06 ± 2.03) group. Each subject performed 30 seconds four different standing balance tests (EO: Eyes Open, EC: Eyes Close, EOf: Eyes Open on foam, ECf: Eyes Close on foam). Five variables (Mean distance, Range of distance, Root mean square, Mean velocity, 95% ellipse area) were calculated from the hip joint center movement of Kinect sensor. Results showed that there were significant differences between groups for four different standing tests. Calculated variables from kinect sensor showed significant correlation with BBS score. Especially, mediolateral mean distance, mediolateral root mean square, mediolateral range of distance and 95% ellipse area showed discriminative ability for all tests. Mean values of variables of IO were higher than those of HO, which means the decreased balance ability in IO compared with HO. Therefore, it was possible to estimate simple balance assessment of the elderly using portable low-cost Kinect sensor.
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      Portable low-cost Kinect sensor was used to analyze standing balance ability of the elderly. Eighty subjects who can walk alone and have a normal cognitive level participated in this experiment. Based on Berg Balance scale (BBS) test with 52 points, s...

      Portable low-cost Kinect sensor was used to analyze standing balance ability of the elderly. Eighty subjects who can walk alone and have a normal cognitive level participated in this experiment. Based on Berg Balance scale (BBS) test with 52 points, subjects were divided into Healthy older (HO: 46 persons, BBS: 53.80 ± 1.19) and Impaired older (IO: 34 persons, BBS: 49.06 ± 2.03) group. Each subject performed 30 seconds four different standing balance tests (EO: Eyes Open, EC: Eyes Close, EOf: Eyes Open on foam, ECf: Eyes Close on foam). Five variables (Mean distance, Range of distance, Root mean square, Mean velocity, 95% ellipse area) were calculated from the hip joint center movement of Kinect sensor. Results showed that there were significant differences between groups for four different standing tests. Calculated variables from kinect sensor showed significant correlation with BBS score. Especially, mediolateral mean distance, mediolateral root mean square, mediolateral range of distance and 95% ellipse area showed discriminative ability for all tests. Mean values of variables of IO were higher than those of HO, which means the decreased balance ability in IO compared with HO. Therefore, it was possible to estimate simple balance assessment of the elderly using portable low-cost Kinect sensor.

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      목차 (Table of Contents)

      • Abstract
      • 1. 서론
      • 2. 본론
      • 3. 결과
      • 4. 고찰
      • Abstract
      • 1. 서론
      • 2. 본론
      • 3. 결과
      • 4. 고찰
      • 5. 결론
      • References
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      참고문헌 (Reference)

      1 김창국, "노인들의 낙상관련 위험요인의 기여도 분석" 한국사회체육학회 (43) : 609-618, 2011

      2 R. A. Clark, "Validity of the Microsoft Kinect for assessment of postural control" 36 (36): 372-377, 2012

      3 X. Xu, "The validity of the first and second generation Microsoft Kinect for identifying joint center locations during static postures" 49 : 47-54, 2015

      4 S. Tyson, "The psychometric properties and clinical utility of measures of walking and mobility in neurological conditions: a systematic review" 23 (23): 1018-1033, 2009

      5 J. S. Choi, "The development and evaluation of a program for leg-strengthening exercises and balance assessment using Kinect" 28 (28): 33-37, 2016

      6 J. A. Raymakers, "The assessment of body sway and the choice of the stability parameter(s)" 21 (21): 48-58, 2005

      7 B. Galna, "Retraining function in people with Parkinson’s disease using the Microsoft kinect: game design and pilot testing" 11 (11): 2014

      8 Y. Yang, "Reliability and validity of Kinect RGB-D sensor for assessing standing balance" IEEE 14 (14): 1633-1638, 2014

      9 S. Vernon, "Quantifying individual components of the timed up and go using the kinect in people living with stroke" 29 (29): 48-53, 2015

      10 M. L. Latash, "Movement sway: changes in postural sway during voluntary shifts of the center of pressure" 150 (150): 314-324, 2003

      1 김창국, "노인들의 낙상관련 위험요인의 기여도 분석" 한국사회체육학회 (43) : 609-618, 2011

      2 R. A. Clark, "Validity of the Microsoft Kinect for assessment of postural control" 36 (36): 372-377, 2012

      3 X. Xu, "The validity of the first and second generation Microsoft Kinect for identifying joint center locations during static postures" 49 : 47-54, 2015

      4 S. Tyson, "The psychometric properties and clinical utility of measures of walking and mobility in neurological conditions: a systematic review" 23 (23): 1018-1033, 2009

      5 J. S. Choi, "The development and evaluation of a program for leg-strengthening exercises and balance assessment using Kinect" 28 (28): 33-37, 2016

      6 J. A. Raymakers, "The assessment of body sway and the choice of the stability parameter(s)" 21 (21): 48-58, 2005

      7 B. Galna, "Retraining function in people with Parkinson’s disease using the Microsoft kinect: game design and pilot testing" 11 (11): 2014

      8 Y. Yang, "Reliability and validity of Kinect RGB-D sensor for assessing standing balance" IEEE 14 (14): 1633-1638, 2014

      9 S. Vernon, "Quantifying individual components of the timed up and go using the kinect in people living with stroke" 29 (29): 48-53, 2015

      10 M. L. Latash, "Movement sway: changes in postural sway during voluntary shifts of the center of pressure" 150 (150): 314-324, 2003

      11 D. A. Winter, "Motor mechanisms of balance during quiet standing" 13 (13): 49-56, 2003

      12 T. E. Prieto, "Measures of postural steadiness: differences between healthy young and elderly adults" 43 (43): 956-966, 1996

      13 A. Ejupi, "Kinect-based five-timessit-to-stand test for clinical and in-home assessment of fall risk in older people" 62 (62): 118-124, 2015

      14 D. A. Winter, "Human balance and posture control during standing and walking" 3 (3): 193-214, 1995

      15 U. Laessoe, "Fall risk in an active elderly population can it be assessed?" 6 (6): 2007

      16 L. F. Yeung, "Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway" 40 (40): 532-538, 2014

      17 P. Silsupadol, "Effects of single-task versus dual-task training on balance performance in older adults: a double-blind, randomized controlled trial" 90 (90): 381-387, 2009

      18 B. Lange, "Development and evaluation of low cost game-based balance rehabilitation tool using the Microsoft Kinect sensor" 1831-1834, 2011

      19 E. Auvinet, "Detection of gait cycles in treadmill walking using a Kinect" 41 (41): 722-725, 2015

      20 U. S. D. Nguyen, "Correlations of clinical and laboratory measures of balance in older men and women" 64 (64): 1895-1902, 2012

      21 M. O’Sullivan, "Correlation of accelerometry with clinical balance tests in older fallers and non-fallers" 38 (38): 308-313, 2009

      22 F. B. Horak, "Components of postural dyscontrol in the elderly: a review" 10 (10): 727-738, 1989

      23 B. Galna, "Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease" 39 (39): 1062-1068, 2014

      24 D. W. Kang, "A study on balance assessment according to the levels of difficulty in postural control" 28 (28): 1832-1835, 2016

      25 E. Maranesi, "A statistical approach to discriminate between non-fallers, rare fallers and frequent fallers in older adults based on posturographic data" 32 : 8-13, 2016

      26 H. Cohen, "A Study of the Clinical Test of Sensory Interaction and Balance" 73 (73): 346-351, 1993

      27 A. Ejupi, "A Kinect and inertial sensor-based system for the self-assessment of fall risk: a home-based study in older people" 31 : 261-293, 2015

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 학술지 통합 (기타) KCI등재
      2001-01-01 평가 등재학술지 유지 (등재유지) KCI등재
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.27 0.27 0.24
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.21 0.19 0.366 0.08
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