Upper limb amputees experience severe discomfort when performing daily life activities owing to the loss of motor and sensory hand functions (Antfolk et al., 2012). The hand prosthesis is a representative assistive device that compensates for the lost motor functions of upper limb amputees. Multi-degree-of-freedom (DOF) myoelectric hand prostheses, which are actuated by a motor, are among the most commonly used hand prostheses (Belter et al., 2013). They are used for gripping objects with a high DOF or performing various hand motions as a means of communication. However, these prosthetic hands require the mounting of multiple motors on the fingers, palm, and wrist to enable hand performance with a high DOF; in practice, they are more similar to robotic hands than human hands. Consequently, the manufacturers of the Michelangelo hand prosthesis (Ottobock Inc.) and I-limb hand (Touch Bionics Inc.) provided a dedicated cover for their developed products resembling the shape of a human hand. Because the cover mimics the fingerprint and skin color of a human hand, the multi-DOF myoelectric hand prostheses with the cover not only perform

According to the International Labor Organization, 317 million accidents occurs on the work-related diseases and injuries each year(1). In addition, occupational diseases that showed a declining trend until 2011 are expected to rise again in 2013. Occupational disease, in the self-assessment, among the approximately 1.2 million workers, people who had experienced occupational diseases were judged to be ill due to their job or cause of the disease. Overseas, there is interest and high level research on the factors that affect occupational diseases. In Europe, there is a survey of occupational diseases in the European Union countries through the European Working Conditions Survey (EWCS), which measures the working environment and correlates various aspects, and research that contributes to European policy development, in particular the quality of work and employment issues. In Korea, the EWCS is supplemented with the contents of the question according to the characteristics of Koreans, and KWCS (Korean Working Conditions Survey) is being conducted for Koreans. In this system, KWCS data is used to analyze occupation of upper limb, lower back and lower limb. We have developed a probability prediction system that can cause musculoskeletal disorders. In this system, a decision tree, a logistic regression, and a neural network are selected as the data mining method for predicting the occurrence of detailed occupational diseases, and the decision tree algorithm which is the most reliable in the ROC curve is selected and applied.