|dc.description.abstract||Low back pain is a common musculoskeletal disorder that affects 80 percentages of people at some point in their lives. In the United States it is the most common cause of job-related disability, a leading contributor to missed work and health care expenditures related to low back pain can be substantial. In recent years, the United States has been facing skyrocketing health care cost, with health care expenditures reaching $1.2 trillion and accounting for 13.6 percentage of the gross domestic product.
The aim of this study was to develop a test procedure to study the effect of carrying a unilateral load or laptop bag or briefcase on the posture and trunk biomechanics when walking (Gait). The objective was to quantify movements of the trunk during walking using traditional and non-linear methods. The study was approved by the Institutional Review Boards (IRB) of Auburn University, AL as well as the Palmer College of Chiropractic, IA. Nine participants were recruited from the population of the Palmer College of Chiropractic students and employees. All volunteers signed IRB approved informed consent. Data were recorded from 8 healthy participants after being screened for eligibility by licensed clinicians during walking. Participants were asked to walk back and forth at their comfortable speed carrying loads on one hand on the right hand side of 0,5,10, 15, 20, and 25 pounds on a wooden walking platform (5 ft * 8 ft) for a maximum of 30 steps/cycles. Participants walked with self-selected speed to ensure that any potential discomfort is minimized during walking. Motion data were recorded from T1, L1, L3, and S1 vertebrae at a frequency of 120 Hz. Range of Motion (ROM), Correlation Dimension (CoD), and Approximate Entropy (ApEn) was determined using custom written MatLab programs. EMG data were recorded from six muscle groups bilaterally ( right and left): Erector Spinae, Multifidus, Latissimus Dorsi, Internal Obliques, External Obliques and Rectus Abdominis at a frequency of 1200 Hz. For EMG, root mean square EMG values, Mean and Median Frequency of the EMG data were calculated to see the effect of increasing load on muscle fatigue using custom developed MatLab program. Ground reaction force data were collected using a force plate. Vertical ground reaction forces, 1st peak force (Fz1), 2nd Peak force (Fz3) and minimum force (Fz2) between 1st peak and 2nd peak forces were calculated during gait cycle.
The ROM values varied from 2.6 – 3.2 deg. for Lumbar LB, 6.7- 8.7 deg. for Thoracic LB. ApEn values ranged from 0.20-0.40 for Lumbar motion and 0.30– 0.50 for Thoracic motion. No significant difference (p>0.05) were found for ROM values and ApEn values for lumbar LB and Thoracic LB as the load increased from 0 lb to 25 lb. And the CoD values ranged from 1.20 – 1.40 for lumbar LB and 1.20-1.30 for Thoracic LB. No significant difference (p>0.05) were found for CoD values for Thoracic LB but for Lumbar LB, significant difference (p<0.05) were found for CoD values as load increased from 0lb to 25 lb. Normalized GRF (Fz1, Fz2 and Fz3) increased during walking with increased load. No significant difference (p>0.05) were found for mean and median frequencies values from muscles activity during walking as load increased from 0lb to 25 lb.
In conclusion, both traditional linear and nonlinear tools were applied successfully to study the spinal motion and trunk muscle activation during walking with increased loads. Our finding revealed that variability of spinal motion did not change significantly during walking as load increased. Also significance difference (P<0.05) were found for vGRF parameters during walking as load increased. The EMG results (Mean and Median Frequency) indicated that fatigue was not induced during walking in participant’s muscles as load increased which might have helped them provide required neuromuscular response to increasing loads.
Future studies are needed to consider some recommendations for obtaining more meaningful data based on healthy subjects. This developed test procedure can apply on low back pain participants may provide results helpful for low back pain treatment. Data acquisition part needs to be smoother. Wireless EMG electrodes and motion sensor can be used to avoid noise in data captured because of wires sway during walking. The test procedure developed from this study need to be fine tuned before it can be applied on larger population.||en_US