Date of Award
Master of Science (MS)
William M. Mihalko, PhD.
Brook A. Sanford, PhD. Kunal Singhal, PhD. Audrey R. Zucker-Levin, PhD
Backpain, Electromyography, hamstrings, loading, lumbar modeling
Introduction: Low Back Pain (LBP) is a leading cause of activity limitation worldwide and results in 149 million lost work days annually in the United States. The total costs of LBP are estimated to be $100 to $200 billion annually. Specific causes of LBP account for less than 15% of LBP cases. Heavy loading of the lumbar spine and tight hamstrings have been identified as risk factors for LBP. Tight hamstrings pull the pelvis posteriorly and reduce the lordosis of the spine, resulting in increased loading of the lumbar vertebral bodies of the spine. While this mechanism has been described, a link between hamstring stretching and reduced lumbar vertebral body loading has not been established. Development of an objective method to measure lumbar loading would assist is determining a link between tight hamstrings and lumbar loading. Electromyography (EMG) modeling is a non-invasive tool shown to report physiologically appropriate lumbar loading. In this thesis I developed a non-invasive EMG model to measure L4/5 compressive loading and applied the model to measure differences in L4/5 compressive loading before and after a six-week hamstring stretching program. Background: Instrumented Vertebral Body Replacements (VBR), as well as Biomechanical and EMG modeling have all been previously reported as methods to determine spinal lumbar loads. VBR is useful for measuring loads in vivo, but cannot be used for healthy subject populations. Biomechanical modeling using inverse dynamics has been shown to report physiologically accurate values, but may not match underlying muscle activity. Electromyography modeling reports physiological compressive loading, but currently makes use of a single gain value relating muscle force to EMG muscle activity, assuming a linear relationship for all subjects. Muscle force to EMG relationships previously revealed non-linear relationships and high percent error values for general relationships. In this thesis, I attempted to develop a patient specific EMG model for measuring L4/L5 compressive loading. I hypothesize that use of a subject specific muscle force to EMG relationships will reduce percent error of muscle force estimation. Methods: Ten volunteer subjects with tight hamstrings and no history of back injury were recruited. EMG’s were placed on six major trunk muscles. Subjects completed 3 isokinetic voluntary contraction trials (VCT) at 30 and 60°/sec. After addition of 53 reflective markers on key anatomical landmarks, subjects performed a series of tasks including straight leg stoop lifting (SLSL). All testing was repeated after a six week stretching protocol. VCT trials and EMG data was used to build subject specific and general relationships for each muscle. Subject specific relationships were used to calculate compressive lumbar loading during SLSL trials. Compressive loading calculated using an AnyBody lower body model and from three subjects from VBR provided by Orthoload were used for comparing models. Compressive loading values before and after the six week stretching protocol were also compared by both AnyBody and the EMG model to determine the effects of hamstring stretching. Results: Subject specific relationships showed a decreased percent error in estimating muscle forces compared to general relationships. The EMG model appeared to vary in loading estimations more than both Orthoload and AnyBody, though most subjects fell within an appropriate range. Same day intra-subject variability testing showed a small difference in impulse measurements between testing sessions. The AnyBody lower body model consistently reported lower loading than both Orthoload and the EMG model. Neither the AnyBody model nor the EMG model found any differences in compressive loading when comparing pre and post hamstring stretching. Discussion: Our model is an initial step in the development of a patient specific EMG model. Inclusion of additional muscles and accounting for antagonist muscle activity during VCT trials would improve the accuracy of our model and are potential next steps. Lack of differences in pre and post hamstring stretching implies that total compressive loading across the L4/L5 disk pre and post hamstring stretching does not change, though it’s possible the distribution of the load on the disc changes.
Dopico, Pablo Joaquin (http://orcid.org/0000-0001-9325-6854), "A Subject Specific Surface Electromyography Model For Estimating L4/L5 Compressive Loading" (2016). Theses and Dissertations (ETD). Paper 414. http://dx.doi.org/10.21007/etd.cghs.2016.0420.