Student Author(s)

Grant Seyller, Hope College

Faculty Mentor(s)

Dr. Brooke Odle, Engineering

Document Type

Poster

Event Date

4-12-2024

Abstract

Lower back disorders are common among the general population, and are the leading cause of disability worldwide. Nurses and others in the healthcare profession are the most at risk for lower back pain, due to the repeated lifting and handling of patients. In a survey from 2001, over 40,000 nurses from 5 different countries were surveyed, and 39% said they would leave their occupation in the next year because of the physical demands. Because of the prevalence of low back pain in nurses, understanding how patient handling tasks and the weight of patients affect the lower back is important to help reduce lower back disorders. To better understand the effects of weight on the lower back, a method was developed using force plates and a motion capture system. Five different movements, simulating patient handling tasks, were performed with 0lb (no weight), 6lb, and 8lb dumbbells. Seventy-six reflective markers were placed on the bony landmarks and appendages of five participants without patient-handling experience. The tasks and weights were randomized to prevent fatigue. Data were processed using Motive and Visual 3D software. Three different models were created for each subject to reflect each weight held in the hands. Joint moments (in N*m) of the lumbar region were calculated for each trial. The range of the moments was calculated for each trial and separated by movement and weight. The average range of moments was calculated for each movement and weight and plotted. Overall, the trends of lumbar moments increased as weight increased, which was expected. Since this study was a Proof-Of-Concept, this method can be applied to unknown weights such as a patient. This approach is encouraging and may be beneficial in quantifying the internal loads exerted on the low backs of nurses during tasks.

Comments

This research was supported by the National Science Foundation under Grant No. 2029372 and the Bair Talent Development Fund.

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Engineering Commons

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