Resampling and Data Augmentation For Equines’ Behaviour Classification Based on Wearable Sensor Accelerometer Data Using a Convolutional Neural Network

Monitoring horses' behaviors through sensors can yield important information about their health and welfare. Sampling frequency majorly affects the classification accuracy in activity recognition and energy needs for the sensor. The aim of this study was to evaluate the effect of sampling rate reduction of a tri-axial accelerometer on the recognition accuracy by resampling a 50 Hz experimental dataset to four lower sampling rates (5 Hz, 10 Hz,...