Computational modeling of posteroanterior lumbar traction by an automated massage bed: predicting intervertebral disc stresses and deformation

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Abstract

Spinal traction is a physical intervention that provides constant or intermittent stretching axial force to the lumbar vertebrae to gradually distract spinal tissues into better alignment, reduce intervertebral disc (IVD) pressure, and manage lower back pain (LBP). However, such axial traction may change the normal lordotic curvature, and result in unwanted side effects and/or inefficient reduction of the IVD pressure. An alternative to axial traction has been recently tested, consisting of posteroanterior (PA) traction in supine posture, which was recently shown effective to increase the intervertebral space and lordotic angle using MRI. PA traction aims to maintain the lumbar lordosis curvature throughout the spinal traction therapy while reducing the intradiscal pressure. In this study, we developed finite element simulations of mechanical therapy produced by a commercial thermo-mechanical massage bed capable of spinal PA traction. The stress relief produced on the lumbar discs by the posteroanterior traction system was investigated on human subject models with different BMI (normal, overweight, moderate obese and extreme obese BMI cases). We predict typical traction levels lead to significant distraction stresses in the lumbar discs, thus producing a stress relief by reducing the compression stresses normally experienced by these tissues. Also, the stress relief experienced by the lumbar discs was effective in all BMI models, and it was found maximal in the normal BMI model. These results are consistent with prior observations of therapeutic benefits derived from spinal AP traction.

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Cardoso, L., Khadka, N., Dmochowski, J. P., Meneses, E., Lee, K., Kim, S., … Bikson, M. (2022). Computational modeling of posteroanterior lumbar traction by an automated massage bed: predicting intervertebral disc stresses and deformation. Frontiers in Rehabilitation Sciences, 3. https://doi.org/10.3389/fresc.2022.931274

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