Analysis and assessment of an ergonomic computer chair

The aim of this study was to assess and evaluate an ergonomic chair and also determine if the protocol used for this study should be recommended for evaluation of such chairs. Subjects (n = 30) were evaluated while carrying out 3 different computer related tasks to simulate routine activities the chair will be subjected to. A body discomfort survey and questionnaire were used to obtain subjective data from test subjects. Participants were asked to rate their general discomfort and discomfort at various anatomical locations on a scale of 0-10, indicating no discomfort and extreme discomfort respectively. An electromayograph (EMG) was used to measure and record muscle activity; Root Mean Square (RMS) values generated were used as objective data and analyzed accordingly. The Rapid Upper Limb Assessment (RULA) was used to evaluate the most dominant working postures to determine if the chair being assessed provided the appropriate support required to correct or prevent poor posture while carrying out computer related tasks. Using data collected, the 400-D hydraulic chair (Chair A) was compared to another randomly selected ergonomic chair (Chair B). A Comparison of chair A to chair B served as one of the methods used in analyzing the ergonomic chair. Differences in means and variances were noted in this study. No significant correlation could be established between population demographics, RMS values, and RULA scores (-0.6> r <0.6). It was determined that there was a difference in mean muscular activity of a smoker versus a non-smoker at the right flexor and right deltoid muscles. Results obtained from applying Fisher's and Tukey's methods of multiple comparison, showed that chair A produced a significant increase in discomfort at the lower back from start of the study to finish. A test for non-parametric data on the RMS values for chair A and chair B revealed significant differences between the two chairs at the left flexor, left deltoid, and lower back. An attempt was made to predict RMS values for eight different muscle groups given certain demographic information. Statistically significant relationships could not be established between subjective and objective data.