Literature DB >> 11094805

Phase determination during normal running using kinematic data.

A Hreljac1, N Stergiou.   

Abstract

Algorithms to predict heelstrike and toe-off times during normal running at subject-selected speeds, using only kinematic data, are presented. To assess the accuracy of these algorithms, results are compared with synchronised force platform recordings from ten subjects performing ten trials each. Using a single 180 Hz camera, positioned in the sagittal plane, the average RMS error in predicting heelstrike times is 4.5 ms, whereas the average RMS error in predicting toe-off times is 6.9 ms. Average true errors (negative for an early prediction) are +2.4 ms for heelstrike and +2.8 ms for toe-off, indicating that systematic errors have not occurred. The average RMS error in predicting contact time is 7.5 ms, and the average true error in predicting contact time is 0.5 ms. Estimations of event times using these simple algorithms compare favourably with other techniques requiring specialised equipment. It is concluded that the proposed algorithms provide an easy and reliable method of determining event times during normal running at a subject selected pace using only kinematic data and can be implemented with any kinematic data-collection system.

Mesh:

Year:  2000        PMID: 11094805     DOI: 10.1007/BF02345744

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  14 in total

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Authors:  N Stergiou; B T Bates; S L James
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2.  Algorithms to determine event timing during normal walking using kinematic data.

Authors:  A Hreljac; R N Marshall
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Journal:  J Biomech       Date:  1987       Impact factor: 2.712

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Journal:  J Biomech       Date:  1995-03       Impact factor: 2.712

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Journal:  J Biomech       Date:  1985       Impact factor: 2.712

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Authors:  R J Minns
Journal:  J Biomed Eng       Date:  1982-10

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Authors:  C Peham; M Scheidl; T Licka
Journal:  J Biomech       Date:  1999-10       Impact factor: 2.712

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  4 in total

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3.  Comparison of methods for kinematic identification of footstrike and toe-off during overground and treadmill running.

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4.  A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy-Which markers work best for which gait patterns?

Authors:  Yong Kuk Kim; Rosa M S Visscher; Elke Viehweger; Navrag B Singh; William R Taylor; Florian Vogl
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