TF-C Pretrain Gesture

- Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

- Paper link: 

- Github repo: https://github.com/mims-harvard/TFC-pretraining

- Project website: 

Gesture contains accelerometer measurements of eight simple gestures that differed based on the paths of hand movement. The eight gestures are: hand swiping left, right, up, down, hand waving in a counterclockwise circle, or in clockwise circle, hand waving in a square, and waving a right arrow. The classification labels are those eight different types of gestures. The original paper reports inclusion of 4,480 gesture measurements, but through UCR Database we were only able to recover 440 measurements. The dataset is balanced with 55 samples each class and is of a suitable size for our purpose of fine-tuning experiments. Sampling frequency is not explicitly reported in the original paper but is presumably 100 Hz. The dataset uses three channels corresponding to three coordinate directions of linear acceleration.