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Related Experiment Videos

Computer algorithms to characterize individual subject EMG profiles during gait.

R A Bogey1, L A Barnes, J Perry

  • 1Department of Pathokinesiology Service, Rancho Los Amigos Medical Center, Downey, CA.

Archives of Physical Medicine and Rehabilitation
|September 1, 1992
PubMed
Summary

The intensity filtered average (IFA) and packet analysis (PAC) methods accurately determine gait electromyography (EMG) onset and cessation times, unlike the ensemble average (EAV) method. IFA is recommended for clinical use due to its reliability and ease of automation.

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Area of Science:

  • Biomechanics
  • Neuroscience
  • Clinical Electrophysiology

Background:

  • Accurate determination of gait electromyography (EMG) onset and cessation is crucial for analyzing walking patterns.
  • Existing methods for EMG analysis may lack precision, particularly in individuals with gait pathologies.
  • Normalization techniques, such as manual muscle testing (%MMT), are used to standardize EMG signals.

Purpose of the Study:

  • To investigate and compare three precise methods for determining gait EMG onset and cessation times.
  • To evaluate the accuracy of the ensemble average (EAV), intensity filtered average (IFA), and packet analysis (PAC) methods.
  • To identify a reliable method for clinical application in analyzing gait EMG.

Main Methods:

  • Soleus muscle EMG was recorded from 24 normal adults and 32 individuals with gait pathologies during level walking.

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  • EMG data were normalized, rectified, integrated, and processed into linear envelopes at each percent gait cycle (%GC).
  • Three methods (EAV, IFA, PAC) were applied to generate EMG profiles, with results compared against control values using Dunnett's test.

    • Main Results:

    • The ensemble average (EAV) method showed significant differences from control values for onset, cessation, and duration in both normal and patient trials.
    • The intensity filtered average (IFA) and packet analysis (PAC) methods demonstrated no significant differences from control values.
    • IFA was found to be suitable for clinical use due to its ability to be automatically analyzed across all trials with minimal decision rules.

    Conclusions:

    • The IFA and PAC methods provide accurate and reliable determination of gait EMG onset and cessation times.
    • The EAV method is less reliable for precise temporal analysis of gait EMG.
    • The IFA method is recommended for clinical application owing to its accuracy, automation potential, and simplicity.