In this paper, we propose a hand gesture sequence recognition technique for human–computer interactions wherein a user grasps an object. Our aim is to develop a technique which can recognize input in the form of various grasp types by recognizing their gesture sequence. We introduce a prototype using electromyography signals and report the results of a user study to validate the proposed technique for interactions in hands-busy situations and evaluate the recognition accuracy of the user gestures. The results demonstrate that our proposed technique showed 93.13% average accuracy for basic grasp types according to a classic taxonomy of grasping. We also discuss the findings of the user study and perspectives for the practical application of the proposed technique.