Assessment of Gait Kinetics Using Triaxial Accelerometers

被引:1
|
作者
Fortune, Emma [1 ]
Morrow, Melissa M. B. [1 ]
Kaufman, Kenton R. [1 ]
机构
[1] Mayo Clin, Dept Orthoped Surg, Motion Anal Lab, Rochester, MN 55905 USA
基金
美国国家卫生研究院;
关键词
ground reaction force; loading rate; body-worn sensors; ankle acceleration; vertical axis; PHYSICAL-ACTIVITY; WOMEN; COUNTS; BONE;
D O I
10.1123/JAB.2014-0037
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Repeated durations of dynamic activity with high ground reaction forces (GRFs) and loading rates (LRs) can be beneficial to bone health. To fully characterize dynamic activity in relation to bone health, field-based measurements of gait kinetics are desirable to assess free-living lower-extremity loading. The study aims were to determine correlations of peak vertical GRF and peak vertical LR with ankle peak vertical accelerations, and of peak resultant GRF and peak resultant LR with ankle peak resultant accelerations, and to compare them to correlations with tibia, thigh, and waist accelerations. GRF data were collected as ten healthy subjects (26 [19-34] years) performed 8-10 walking trials at velocities ranging from 0.19 to 3.05 m/s while wearing ankle, tibia, thigh, and waist accelerometers. While peak vertical accelerations of all locations were positively correlated with peak vertical GRF and LR (r(2) > .53, P < .001), ankle peak vertical accelerations were the most correlated (r(2) > .75, P < .001). All peak resultant accelerations were positively correlated with peak resultant GRF and LR (r(2) > .57, P < .001), with waist peak resultant acceleration being the most correlated (r(2) > .70, P < .001). The results suggest that ankle or waist accelerometers give the most accurate peak GRF and LR estimates and could be useful tools in relating physical activity to bone health.
引用
收藏
页码:668 / 674
页数:7
相关论文
共 50 条
  • [31] Measuring true acceleration vectors with triaxial accelerometers
    Han, S.
    McConnell, K.G.
    Experimental Techniques, 1990, 14 (03) : 36 - 40
  • [32] Selected Aging Effects in Triaxial MEMS Accelerometers
    Luczak, Sergiusz
    Zams, Maciej
    Baginski, Karol
    JOURNAL OF SENSORS, 2019, 2019
  • [33] Online Gait Phase Detection with Automatic Adaption to Gait Velocity Changes Using Accelerometers and Gyroscopes
    Seel, Thomas
    Landgraf, Lucian
    Escobar, Victor Cermeno
    Schauer, Thomas
    BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 2014, 59 : S766 - +
  • [34] Smart Belt-Using Dual-Accelerometers for Gait Analysis
    Shieh, Wann-Yun
    Cho, Hsin-Hung
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2013, 3 (01) : 65 - 71
  • [35] Gait event detection for FES using accelerometers and supervised machine learning
    Williamson, R
    Andrews, BJ
    IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, 2000, 8 (03): : 312 - 319
  • [36] Quantitative evaluation of gait ataxia by accelerometers
    Shirai, Shinichi
    Yabe, Ichiro
    Matsushima, Masaald
    Ito, Yoichi M.
    Yoneyama, Mitsuru
    Sasaki, Hidenao
    JOURNAL OF THE NEUROLOGICAL SCIENCES, 2015, 358 (1-2) : 253 - 258
  • [37] Principal component analysis for ataxic gait using a triaxial accelerometer
    Akira Matsushima
    Kunihiro Yoshida
    Hirokazu Genno
    Shu-ichi Ikeda
    Journal of NeuroEngineering and Rehabilitation, 14
  • [38] Principal component analysis for ataxic gait using a triaxial accelerometer
    Matsushima, Akira
    Yoshida, Kunihiro
    Genno, Hirokazu
    Ikeda, Shu-ichi
    JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2017, 14
  • [39] Novel attachment methods for assessing activity patterns using triaxial accelerometers on stingrays in the Bahamas
    Chris R. E. Ward
    Ian A. Bouyoucos
    Edward J. Brooks
    Owen R. O’Shea
    Marine Biology, 2019, 166
  • [40] FALL DETECTION USING THREE WEARABLE TRIAXIAL ACCELEROMETERS AND A DECISION-TREE CLASSIFIER
    Luo, Kan
    Li, Jianqing
    Wu, Jianfeng
    Yang, Hua
    Xu, Gaozhi
    BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2014, 26 (05):