Related Experiment Video
Updated: May 16, 2026

07:52
Mouse Lumbar Vertebra Uniaxial Compression Testing with Embedding of the Loading Surface
Published on: December 1, 2023
Optimized prediction of contact force application during side-lying lumbar manipulation
Casey A Myers1, Brian A Enebo, Bradley S Davidson
1Mechanical and Materials Engineering, University of Denver, Denver, CO, USA.
Journal of Manipulative and Physiological Therapeutics
|December 5, 2012
Summary
This study developed a new method to predict lumbar spine contact force during manipulation. The weighted least squares (WLS) method accurately predicted forces, unlike the common least squares (CLS) method.
Area of Science:
- Biomechanics
- Spinal Manipulation Therapy Research
Background:
- Accurate measurement of spinal contact forces is crucial for understanding spinal manipulative therapy (SMT).
- Existing methods for measuring forces during SMT have limitations.
Purpose of the Study:
- To develop a mathematical framework for predicting L3 contact force during side-lying lumbar manipulation.
- To evaluate the accuracy of common least squares (CLS) and weighted least squares (WLS) methods in predicting L3 contact force.
Main Methods:
- Five participants underwent lumbar spinal manipulations in a side-lying position.
- Participant-specific algorithms were generated using directly measured L3 contact force data.
- Algorithms predicted L3 contact force during therapeutic-level manipulations.
- CLS and WLS methods were compared for accuracy and effectiveness.
Main Results:
- The WLS method demonstrated high accuracy, with differences of -3.6 ± 9.1 N compared to criterion standard measurements.
- The CLS method showed significantly larger differences (621.0 ± 193.5 N) and overestimated forces.
- WLS provided a narrower range of agreement ( -21.9 to 14.7 N) compared to CLS (234.0 to 1008.0 N).
Conclusions:
- A novel framework combining direct and indirect measurements effectively predicts spinal contact force.
- This method preserves clinically relevant practitioner-participant interactions.
- The framework supports advancements in SMT training and research.