Abstract: A comprehensive method based on pressure sensors and LiDAR is proposed to recognize the ambulation states of electric wheeled walker users. Firstly, pressure sensors are used to acquire the hand force data on the handle, which are denoised to extract the valid motion intentions. Then, a LiDAR sensor is adopted to track the lower-limb motion speed, and leg motion patterns are fitted using the least squares method for accurate position estimation. Through multi-sensor fusion, the system identifies critical states, including normal walking, turning, and falling, and activates adaptive control strategies. This method enhances the real-time monitoring accuracy and stable control by capturing the upper-limb pressure changes and lower-limb motion trajectories, and significantly improves the safety for elderly users by preventing falls and enabling reliable assistance, demonstrating potential for clinical rehabilitation applications.