EVALUATION OF WEARABLE SENSORS TO QUANTIFY CONSTRUCTION WORKERS MUSCLE FORCE: AN ERGONOMIC ANALYSIS

Construction industry has one of the highest rates of bodily injuries including serious Work-related Musculoskeletal Disorders (WMSDs). The Occupational Safety and Health Administration (OSHA) identifies force level as a risk indicator associated with WMSDs. Without direct measurement, quantifying the force exerted during a given task performed by workers is difficult, if not impossible. Therefore, an indirect and non-intrusive way of identifying excessive force applied during physical tasks can effectively reduce the risk of WMSD injuries. In this research, a series of physical activities involving pushing and pulling are simulated by the research team in laboratory-scale experiments. The exerted force is measured using a work simulator tool and accelerometer data is collected from a smartphone sensor affixed on the working arm. Artificial Neural Network is trained with the accelerometer data and the force levels. Testing results indicate that the trained model can predict the force level with over 87.5% accuracy.