Fig. 3: Model design for tapping coordinate data.

a depicts the model structure for the coordinate data tapping model (inputs: x, y coordinates and timestamp). The model contains six convolutional layers, six max-pooling layers, and one fully connected layer. b Experiments were designed to search for the optimal data processing methods and network hyperparameters, including the normalization strategy on the coordinates and the timestamps, augmentations with 2D-rotation and time scale, and the network optimizer. Best performing models by augmentation and centering groups are enclosed in squares. c A combined model is generated by averaging the prediction scores from accelerometer and from coordinates.