Forces and moments acting on joints is of great importance in different fields of biomechanics such as ergonomics, sports biomechanics, and rehabilitation. EMG driven models can be used to estimate forces and moments acting on joints. The current study aimed to propose a model for prediction of knee joint moment using EMG signals detected from muscles and knee joint angle. Electromyography of knee muscles, knee joint angle and moment were recorded simultaneously during the extension-flexion movement in three young men using an isokinetic system. The model for estimating knee joint moment was developed using multiple linear regression. In order to calibrate and validate the model, new data was entered into the model and the estimated moment was compared with the measured moment. The model estimated knee joint moment with an acceptable accuracy, so that coefficient of detection (R2 ) was between 0.9 and 0.95.
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