Human Motion Prediction Using Wearable Sensors And Machine Learning

This article discusses the use of wearable sensors and machine learning to accurately predict human movement. The study focuses on using inertial measurement units (IMU) and electromyography (EMG) sensors to capture data and a convolutional neural network (CNN) to analyze and distinguish different gait phases. Results show high accuracy in gait phase recognition, regardless of walking speed.