Examination surveillance is one of main challenges in online examination. Traditional approaches mainly focus on the identification of examinees and lack of flexible and scalable solutions to detect the misbehavior of the examinees in online examinations. We provide a new solution to monitor the examinees’ behavior based on somatosensory information. Meanwhile, to reduce false alarm rate, a two-dimensional gesture detection scheme is proposed, in which both the duration and frequency of the detected gesture events are adopted to describe the target misbehavior. Examinees’ states are discriminated by analyzing the duration and frequency of the events happened within a time window. Experiments demonstrate that our proposed solution can effectively distinguish the examinees’ misbehavior from their normal actions.