Recently, a research team from the Pontificia Universidad Católica del Perú utilized IMU and EMG sensor technologies to differentiate and classify walking styles between amputees and non-amputees, with the goal of optimizing the functional performance of smart prostheses to enhance the wearer's quality of life and mobility.
The experiment utilized a comprehensive dataset distribution strategy, and all types of subjects were evaluated exhaustively. It was found that the data collected by the IMU played an important role, especially when it was effectively fused with EMG signals, to accurately capture the dynamic gait changes of the subjects in different scenarios, such as walking on a flat surface, walking up and down ramps, and walking up and down stairs.

The results show that this fusion method significantly improves the accuracy and precision of gait recognition in both non-amputees and amputees, highlighting the great potential of IMU data fusion in improving the adaptability and functionality of intelligent prostheses, which is of great practical value in promoting the development of prosthetic technology in the direction of smarter and more personalized.