A computerized video coding system for biomechanical analysis of lifting tasks

Abstract

This paper illustrates the design of a computerized postural coding system using information from field survey videotapes and limited input (e.g., load, weight, and height) to provide a timely estimation of kinematic and kinetic data for biomechanical analysis of sagittal lifting task evaluation and design. The main objectives of the study were to report the development of this technique, assess its applicability, and examine its prediction tolerance under several lifting conditions. A computer graphical user interface was developed, relying on interactive graphical three-dimensional animation to assist the prediction of a subject's lifting movement. The subject's motion was predicted based on the identification of major joint angles of key posture events extracted from the lifting video clips of the analyzed task. The key prediction outcome of this approach is the estimation of joint loading over time, including the compressive force on the lumbosacral (L5/S1) joint. Biomechanical experiments were conducted to evaluate the proposed method under several sagittal lifting conditions. The results showed that the proposed method is comparable to the use of a complex system. While there existed a tolerance between both systems in estimation of the lower back compressive force, the maximum error percentage (≈10%) is considered within a reasonable range. The implication of this approach is to provide a feasible method for performing on-site evaluations of the biomechanics of lifting tasks which cannot be performed otherwise due to the limitations of time and resources. It can also be used for pilot studies to timely identify and select the most critical tasks for more detailed analyses. Relevance to industry This study presents a design that is capable of performing the biomechanical assessment of manual lifting tasks using only the field survey videotapes and limited input data. For industrial-based in situ analyses, this approach may provide an alternative for biomechanical assessment of manual lifting tasks while still maintaining the quality of results.