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This paper describes a gesture recognition algorithm based on electrooculographic (EOG) signals measured by a simple brain-computer interface to estimate a user's intentions. A dynamic programming (DP)-matching-based gesture recognition algorithm is proposed and its characteristics are discussed regarding improving the eye movement recognition rate, along with the potential for control applications in a hands-free manipulation systems. Experimental results show the feasibility and effectiveness of the estimation algorithm using the DP-matching-based method. The control of a walkthrough in 3D virtual space is described as a practical example. As an extension of the EOG gesture recognition algorithm, the recognition method is applied to estimate multiple directions of eye movement by using multiple electrodes attached around the eyes, with experimental results showing the feasibility of the method.