A Virtual Training System for Children with Upper Extremity Disability:

tems utilize multisensory information including force and torque signals, or specialized sensor-gloves that capture hand gestures during the performance of a laparoscopic task. The signal data obtained are modeled with advanced computational techniques, such as Hidden Markov and Multivariate Autoregressive Models, in order to generate an assessment index based on the data collected. These methods allow association with quantifiable parameters that correlate with surgical experience.