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Related Experiment Videos

Reliability of a Feedback-Controlled Treadmill Algorithm Dependent on the User's Behavior.

Casey Wiens1, Will Denton1, Molly Schieber1

  • 1Department of Biomechanics, University of Nebraska - Omaha, Omaha, NE.

IEEE International Conference on Electro Information Technology : [Proceedings]. IEEE International Conference on Electro Information Technology
|February 6, 2018
PubMed
Summary

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This study analyzed a feedback-controlled treadmill algorithm, finding it reliably reproduces mean belt speed. However, speed variation consistency requires same-day trials for optimal results in gait analysis.

Area of Science:

  • Biomechanics
  • Control Systems Engineering
  • Human Movement Science

Background:

  • Conventional treadmills have limitations in gait analysis.
  • Feedback-controlled treadmill algorithms offer enhanced control by adapting to user biomechanics.
  • Existing algorithms can be further refined to improve reliability.

Purpose of the Study:

  • To assess the reliability of a novel feedback-controlled treadmill algorithm in maintaining consistent belt speed.
  • To evaluate the algorithm's performance based on participant walking behavior and biomechanical factors.
  • To determine the within-day and between-day reliability of treadmill belt speed parameters.

Main Methods:

  • Nine healthy young adults participated in treadmill walking trials.

Related Experiment Videos

  • A feedback-controlled treadmill algorithm adjusted belt speed based on estimated walking speed derived from biomechanical data.
  • Participants completed one 16-minute and one 5-minute trial on day one, and one 16-minute trial on day two.
  • Statistical analyses included mean, standard deviation, interclass correlation coefficient (ICC), and standard error of measurement (SEM).

    • Main Results:

    • High interclass correlation coefficients (ICC) were observed for mean treadmill speed, both within-day and between-day.
    • Treadmill speed standard deviation and coefficient of variation demonstrated significant reliability within-day.
    • Between-day reliability for speed variation (standard deviation and coefficient of variation) was not as robust as for mean speed.

    Conclusions:

    • The developed algorithm reliably reproduces the mean treadmill belt speed across multiple trials and days.
    • Consistent treadmill speed variation (standard deviation, coefficient of variation) is more reliably achieved when trials are conducted on the same day.
    • This user-behavior-adaptive algorithm enhances control and minimizes constraints associated with conventional treadmill use in research settings.