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What is Applied Machine Learning On Phase of Gait about?

The article presents a machine learning approach to classify phases of gait using joint angle measurements from inertial measurement units (IMUs), aiming to reduce the number of required features without significantly impacting accuracy. The study demonstrates that reducing features from six to three only decreases classification accuracy by 4.04%, while further reduction to two features results in a 7.46% drop. This method has potential applications in medical and assistive technologies, enhancing gait mon

Author

یاسین

Language

EN