Accelerometer Signal

Accelerometer signals, representing three-dimensional acceleration data, are increasingly used to monitor a wide range of dynamic processes, from human activity and animal behavior to structural health and machine diagnostics. Current research focuses on developing robust machine learning models, including deep learning architectures like CNNs and LSTMs, and simpler methods like Random Forests and Rocket, to classify and interpret these complex time-series data. This work is significant because it enables non-invasive, cost-effective monitoring across diverse applications, improving healthcare, animal welfare, and industrial maintenance practices.