A new approach is proposed to identify gait events in non-laboratory environments with a single inertial measurement unit (IMU) embedded inside shoe. The aim of our work is to develop a useful clinical tool for monitoring individuals walking disability and detect specific pathological gait patterns. Temporal parameters of gait are determined by classification of accelerations and angular velocities. Wavelets denoising of IMU signals allows for an important amount of information that is exploited in different manners for event identification. It was found that wavelet denoising enhanced specific turning points which could effectively identify gait events. The method is verified by comparing the results of video-based motion capture system and force plates as conventional standards. This portable gait-monitoring system allows for versatile application beyond gait laboratory.