Biodynamic Modelling of the Glove-arm System

Abstract

Occupational exposure to the hand-transmitted vibration causes health problems and difficulties in the operators of hand-held power tools. Arm vibration can be effectively controlled by wearing vibration-damping gloves. In this study, a biodynamic glove-arm system model is developed to predict the vibration transmission rate when using such gloves. The arm system is segmented into substructures—including the index finger, middle finger, palm, forearm, upper arm, and shoulder—which are interconnected by linear stiffness and damping elements. The glove is represented by seven mass blocks, each attached to the index finger, middle finger, palm, finger skin, palm skin, and both sides of the tool handle. The root-mean-square error between the experimentally measured and model-predicted transfer rates is used as the objective function for parameter identification, employing a particle swarm optimization (PSO) multi-objective error minimization approach. Simulation results demonstrate that the fitted vibration transfer rates for each segment closely match the experimental data, validating the effectiveness of the proposed model.