Presentation Title

Seated Postural Changes with Foot Position at a Tall Workstation

Presenter's Name(s)

Sarah Nelson, UVMFollow

Abstract

Back pain is a leading cause of disability costing 100 billion in healthcare and missed work in the United States alone15. While traditional workstations have been extensively studied, non-traditional workstations have not been as rigorously investigated for ideal settings and possible improvement4. The motivation for this project was to investigate an understudied but growing workstation setup—a tall workstation. The aim of this project was to assess tall workstations and the effect of foot position on back posture. Posture is a growing area of research as we understand that the spinal loading of sitting for long periods of time can have long lasting deleterious effects3, 26. In this study we determined the feasibility of quantifying back posture during two 30-minute data collections and developed methods for analyzing time-varying back posture. This study involved collecting a single dataset from a volunteer who sat a tall workstation setup, where feet are not meant to touch the floor, with two different foot positions. For the first foot position, the subject placed their feet under the table on a bar made for that purpose, and the second position was to place the feet on the circular ring under the chair also designed for this use. The three-dimensional position of 11 retroreflective markers adhered to the spine and back were collected for thirty minutes in each position (60 minutes total). Lastly, two reference posture datasets were collected for one minute—a standing posture and a traditional seated posture. Marker position movement was quantified by taking the absolute distance of each marker position from its own starting point as the origin. Marker positions along the spine were fit to a 5th order polynomial on each timeframe to investigate changes in the shape of the spine over time and between foot positions. At each marker location, the slope of the 5th order polynomial was determined to assess in which anatomical locations the spine changed shape over time and between foot positions. The slopes along the spine were subtracted from the first timeframe and the preferred postures, and the absolute value was then summed and averaged across all the markers. The plot of marker positions over time showed that the subject moved increasingly farther away from the origin in both foot positions. The 5th order polynomials showed that both foot positions were significantly more curved than the preferred postures and they both curved more overtime though the FUT posture curved slightly more. Overall, this thesis demonstrates the feasibility of quantifying back posture with varying foot position at a tall workstation. Ongoing subject recruitment and data collections will generate results for which statistical comparisons can be made for temporal changes in back posture and foot positions.

Primary Faculty Mentor Name

Niccolo Fiorentino

Graduate Student Mentors

John Ramsdell

Faculty/Staff Collaborators

Niccolo Fiorentino (Mentor) John Ramsdell (Graduate Student Collaborator)

Status

Undergraduate

Student College

College of Engineering and Mathematical Sciences

Program/Major

Mechanical Engineering

Primary Research Category

Engineering & Physical Sciences

Abstract only.

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Seated Postural Changes with Foot Position at a Tall Workstation

Back pain is a leading cause of disability costing 100 billion in healthcare and missed work in the United States alone15. While traditional workstations have been extensively studied, non-traditional workstations have not been as rigorously investigated for ideal settings and possible improvement4. The motivation for this project was to investigate an understudied but growing workstation setup—a tall workstation. The aim of this project was to assess tall workstations and the effect of foot position on back posture. Posture is a growing area of research as we understand that the spinal loading of sitting for long periods of time can have long lasting deleterious effects3, 26. In this study we determined the feasibility of quantifying back posture during two 30-minute data collections and developed methods for analyzing time-varying back posture. This study involved collecting a single dataset from a volunteer who sat a tall workstation setup, where feet are not meant to touch the floor, with two different foot positions. For the first foot position, the subject placed their feet under the table on a bar made for that purpose, and the second position was to place the feet on the circular ring under the chair also designed for this use. The three-dimensional position of 11 retroreflective markers adhered to the spine and back were collected for thirty minutes in each position (60 minutes total). Lastly, two reference posture datasets were collected for one minute—a standing posture and a traditional seated posture. Marker position movement was quantified by taking the absolute distance of each marker position from its own starting point as the origin. Marker positions along the spine were fit to a 5th order polynomial on each timeframe to investigate changes in the shape of the spine over time and between foot positions. At each marker location, the slope of the 5th order polynomial was determined to assess in which anatomical locations the spine changed shape over time and between foot positions. The slopes along the spine were subtracted from the first timeframe and the preferred postures, and the absolute value was then summed and averaged across all the markers. The plot of marker positions over time showed that the subject moved increasingly farther away from the origin in both foot positions. The 5th order polynomials showed that both foot positions were significantly more curved than the preferred postures and they both curved more overtime though the FUT posture curved slightly more. Overall, this thesis demonstrates the feasibility of quantifying back posture with varying foot position at a tall workstation. Ongoing subject recruitment and data collections will generate results for which statistical comparisons can be made for temporal changes in back posture and foot positions.