Search Results for "sensor motion"

LSTM-Human-Activity-Recognition is a machine learning project that demonstrates how recurrent neural networks can be used to recognize human activities from sensor data. The repository implements a deep learning model based on Long Short-Term Memory (LSTM) networks to classify physical activities using time-series data collected from wearable sensors. The project uses the well-known Human Activity Recognition dataset derived from smartphone accelerometer and gyroscope signals. Through the use of sequential neural network architectures, the system learns patterns in motion data that correspond to activities such as walking, sitting, standing, or climbing stairs. ...

...The repository includes links to code in MATLAB, Python, summaries of algorithms, datasets, and relevant research papers. Feature extraction method summaries (e.g. motion, sensor, vision). Deep learning for activity recognition references.