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Monitoring the photoplethysmogram (PPG) signal is essential for cardiovascular patients in a hospital or at home, as well as for those working in front of a personal computer (PC) at the office every day. Therefore, we developed a wireless PPG mouse that consists of a PC mouse, PPG sensor, and Bluetooth mote. The sensor is located within the PC mouse therefore the structure of the ordinary mouse is not changed. A user's thumb can easily touch the surface of a sensor for PPG signal monitoring. However, it is challenging to process the signals collected from the PPG mouse, especially in cases where the mouse moves quickly or the user performs multiple actions on the mouse buttons. In this study, we propose a robust algorithm to detect the PPG peak under big motion artifact conditions. In the proposed algorithm, an adaptive method enables simultaneous detection of true peaks and eliminates fake peaks from the acquired PPG signal. Next, these detected error peaks can be corrected by a random error estimator. The combination of two sequential methods enhances the robustness of the algorithm for distinguishing irregular PPG patterns. The proposed algorithm presents an advantage for real-time applications and continuous heart rate monitoring systems using a wireless PPG sensor implemented in a PC mouse. . His current research interests include the design of ultra-low-power body sensor nodes with energy harvesting, wireless body sensor network, and biomedical signal processing.Wan-Young Chung received the B.Eng. and Master degrees in Electronic . His current research interests include wireless sensor networks, ubiquitous healthcare and automobile applications, smart lighting with visible light communication, and embedded systems. He is now the leader of team for next generation u-healthcare technology development, which is supported by the Brain Korea 21 (BK21) plus project.