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Computer-Based Algorithmic Determination of Muscle Movement Onset Using M-Mode Ultrasonography
Andrew J Tweedell1, Courtney A Haynes1, Matthew S Tenan1
1U.S. Army Research Laboratory, Human Research & Engineering Directorate, Aberdeen Proving Ground, Maryland, USA.
Ultrasound in Medicine & Biology
|February 26, 2017
Summary
Computer algorithms can objectively determine muscle contraction onset using M-mode ultrasonography, offering a reliable alternative to visual analysis in human movement science.
Area of Science:
- Biomechanics
- Human Movement Science
- Medical Imaging
Background:
- Muscle contraction onset is traditionally determined through subjective visual analysis of M-mode ultrasonography.
- This subjective method can introduce variability and limit precision in human movement studies.
Purpose of the Study:
- To evaluate computer-automated algorithms as an objective replacement for subjective visual determination of muscle contraction onset.
- To compare the accuracy and reliability of different algorithmic approaches against visual assessment.
Main Methods:
- M-mode ultrasonography images of biceps and quadriceps contractions were analyzed.
- Three algorithm classes were employed: pixel standard deviation (SD), high-pass filter, and Teager Kaiser energy operator transformation.
- Algorithmic parameters and threshold criteria were systematically varied and compared to visual determination.
Main Results:
- High-pass filtered algorithms (30 Hz cutoff, 20 SD above baseline) demonstrated strong agreement (ICC=0.74, mean diff=37.7 ms).
- Teager Kaiser energy operator transformation (1200 absolute SD above baseline) also showed good performance (ICC=0.80, mean diff=61.8 ms).
- SD at 10% pixel deviation yielded an ICC of 0.72 with a mean difference of 109.8 ms.
Conclusions:
- Computer-automated determination of muscle contraction onset is a viable objective alternative to visual assessment.
- High-pass filtering algorithms show particular promise for enhancing objectivity and precision in human movement science research.
