期刊文献+

Method for assessing the similarity and distance between curves/trials and its applications in gait analysis

Method for assessing the similarity and distance between curves/trials and its applications in gait analysis
在线阅读 下载PDF
导出
摘要 In clinical assessment or sports exercise,it is common that a subject is required to repeat a specific per- formance so that a stable movement pattern is obtained and analysed.In practice,however,the trials done by a sub- ject vary more or less,depending on the psychological or physical conditions.Some of the trials can be used as rep- resentatives of the stable movement pattern,and some not.Therefore,there is a demand for a new method to identify which trials/curves are similar.The traditional methods used to assess curve similarity are not perfectly suitable for the case where there are only a few of trials available.This study proposes a similarity-distance coefficient to assess the similarity of curves/trials.A group of designed curves are used to validate the coefficient.The results show that given joint kinematic data during gait as examples,the proposed coefficient can be used to quantitatively evaluate the similarity of trials,and thus find which trials would be representative (s) for the gait investigated.The proposed method could be applied in various situations where repeat movements have to be measured and analysed. In clinical assessment or sports exercise, it is common that a subject is required to repeat a specmc performance so that a stable movement pattern is obtained and analysed. In practice, however, the trials done by a subject vary more or less, depending on the psychological or physical conditions. Some of the trials can be used as representatives of the stable movement pattern, and some not. Therefore, there is a demand for a new method to identify which trials/curves are similar. The traditional methods used to assess curve similarity are not perfectly suitable for the case where there are only a few of trials available. This study proposes a similarity-distance coefficient to assess the similarity of curves/trials. A group of designed curves are used to validate the coefficient. The results show that given joint kinematic data during gait as examples, the proposed coefficient can be used to quantitatively evaluate the similarity of trials, and thus find which trials would be representative (s) for the gait investigated. The proposed method could be applied in various situations where repeat movements have to be measured and analysed.
出处 《仪器仪表学报》 EI CAS CSCD 北大核心 2008年第10期2017-2023,共7页 Chinese Journal of Scientific Instrument
基金 the Chinese National Education Committee for supporting his visit to UK in 1995.
关键词 曲线 相似性 模拟技术 测量方法 curve similarity distance multi trial gait analysis
  • 相关文献

参考文献20

  • 1ERNI T, COLOMBO G. Locomotor training in paraplegic patients: a new approach to assess changes in leg muscle EMG patterns [ J]. Electromyography and Motor Controlelectroencephalography and Clinical Neurophysiology, 1998,109 : 135-139.
  • 2LE BRIS R, BILLAT V, AUVINET B, et al. Effect of fatigue on stride pattern continuously measured by an accelerometric gait recorder in middle distance runners[ J ]. Journal of Sports Medicine and Physical Fitness, 2006, 46 : 227-231.
  • 3CAI S M, ZHOU P L, YANG H J, et al. Diffusion entropy analysis on the stride interval fluctuation of human gait[ J ]. Physica A-statistical Mechanics and Its Applications, 2007,375:687-692.
  • 4PIERRYNOWSKI M R, GALEA V. Enhancing the ability of gait analyses to differentiate between groups : scaling gait data to body size [ J ]. Gait & Posture, 2001,13:193- 201.
  • 5BENABDELKADER C, CUTLER R G, DAVIS L S. Gait recognition using image selfsimilarity [ J ]. Eurasip Journal on Applied Signal Processing, 2004,4:572-585.
  • 6DELUZIO K J, WYSS U P, ZEE B, et al. Principal component models of knee kinematics and kinetics : normal vs. pathological gait patterns[ J ]. Human Movement Science, 1997,16:201-217.
  • 7PIEROTYI S E, BRAND R A, GABEL R H, et al. Are leg electromyogram profiles symmetrical [ J ]. Journal of Orthopaedic Research, 1991,9:720-729.
  • 8CHEN CH, LIANG J M, ZHAO H, et al. Gait recognition using hidden markov model[ J ]. Advances in Natural Computation, PT 1 Lecture Notes in Computer Science, 2006,4221:399-407.
  • 9GROWNEY E, MEGLAN D, JOHNSON M, et al. Repeated measures of adult normal walking using a video tracking system[ J ]. Gait & Posture, 1997,6 : 147-162.
  • 10KAVANAGH J J, MORRISON S, JAMES D A, et al. Reliability of segmental accelerations measured using a new wireless gait analysis system [ J ]. Journal of Biomechanics, 2006,39:2863-2872.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部