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Related Experiment Video

Updated: Jun 15, 2026

Methods to Quantify Pharmacologically Induced Alterations in Motor Function in Human Incomplete SCI
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Quantification method affects estimates of voluntary quadriceps activation.

Chandramouli Krishnan1, Glenn N Williams

  • 1Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, USA.

Muscle & Nerve
|March 16, 2010
PubMed
Summary
This summary is machine-generated.

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Quantification methods significantly impact voluntary quadriceps muscle activation estimates. Developing predictive equations aids researchers in comparing diverse activation measurement techniques for accurate results.

Area of Science:

  • Biomechanics
  • Human Movement Science
  • Exercise Physiology

Background:

  • Accurate measurement of voluntary muscle activation is crucial in exercise science and rehabilitation.
  • Different quantification methods exist, potentially leading to varied results and hindering cross-study comparisons.

Purpose of the Study:

  • To investigate how different quantification methods affect estimates of voluntary quadriceps muscle activation.
  • To develop predictive equations to reconcile results from distinct measurement techniques.

Main Methods:

  • Voluntary quadriceps activation was tested in 22 healthy individuals at 60 degrees of knee flexion.
  • Activation estimates were derived using the interpolated twitch technique (ITT), central activation ratio (CAR), and a modified CAR.
  • Statistical analyses and correlational assessments were performed to compare the methods.

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Last Updated: Jun 15, 2026

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Main Results:

  • Significant differences (P < 0.001) were found between the three quantification methods.
  • ITT yielded 93.0 ± 6.4% activation, CAR 95.9 ± 3.8%, and modified CAR 98.5 ± 4.1%.
  • Excellent correlation (r = 0.995) was observed between ITT and CAR, with weaker associations with the modified CAR.

Conclusions:

  • The choice of quantification method demonstrably influences voluntary quadriceps activation estimates.
  • The developed predictive equations offer a valuable tool for standardizing and comparing activation data across studies using different methodologies.