Determination of the effect of lift characteristics on dynamic performanceprofiles during manual materials handling tasks

In any quantitative gait or occupational biomechanics investigation, the qu antification of the different kinematic, kinetic, and electromyographic par ameters is essential towards assessment of functional capacity and developm ent of a biomechanical profile of the task demands. In the current study, t he authors presented a methodology for using inferential statistics to eval uate the effect of lift characteristics on phase-dependent and phase-indepe ndent variability in performance. Using a database of kinematic and kinetic profiles obtained from a manual lifting study, the phase-dependent effects of lift characteristics: box mass (load), mode (technique of lift), and sp eed (frequency of lift) were investigated through the use of analysis of va riance (ANOVA) techniques, which recognize the vectorial constitution of th e profiles. In addition, the Karhunen-Loeve Expansion (KLE) feature extract ion method was used for representing the lifting patterns of measured joint angular position, velocity, acceleration, and net muscular torque profiles obtained from a 2-D biomechanical lifting model in order to study the phas e-independent effects. In comparison to traditional descriptive statistical analyses currently used in various occupational biomechanics experimental investigations, this method allows the significant information content of t he time varying signal to be captured, enhancing the sensitivity of subsequ ent hypothesis testing procedures. The application of this technique to MMH investigations allows identification of the lift characteristics that domi nate the variability of task demands, hence aiding in the design and assess ment of ergonomic solutions.