The recognition of the head movements is a challenging task in the Human-Computer Interface domain. The medical, automotive, or computer games domains are only several fields where this task can find practical applicabilities. Currently, the head movement recognition is performed using complex systems based on video information or using an IMU sensor with nine freedom degrees. In this paper, we describe a new approach for recognizing head movements using a new type of IMU sensor with six freedom degrees placed on top of a headphone pair. The system aims to provide an easy control method for people suffering from tetraplegia for a specific set of activities. The system collects data from the inertial sensor placed on top of the headphone to analyze and then extract the features for head movement recognition. We did construct and evaluated eight predictive models of classifying head movements activity to determine which one is the best fit for the proposed head movement recognition system. The comparison and performance evaluation provided by each predictive model lead to demonstrate the performances delivered by our new system for head movements recognition.