RIS Based Hand Gesture Recognition Dataset

Therefore, the ris_random and ris_optimized folders contain 10 frames × 115 measurements × 3 gestures = 3450 files, while the ris_random2 and ris_optimized2 folders contain 1 × 115 measurements × 3 gestures = 345 files. **data_synthetic_variab** This dataset consists of two modes: ris_random and ris_optimized. The main difference between the two subfolders is the configuration of the RIS (random or optimized). This dataset consists of four subfolders: ris_random, ris_random2, ris_optimized, and ris_optimized2.

The main difference between the subfolders is the format of the data: - ris_random and ris_optimized: Data is stored in individual files for each frame, named as 'frame_{i}{posture}{n_med}' - ris_random2 and ris_optimized2: Data has already been processed and combined into single files for all frames using the compact_files_frames.txt function, named as 'all_frames_{posture}_{n_med}' For each gestures = {close, two, open}, we have n_med values from 0 to 8 and 10 frames.

This dataset provides additional synthetic data with variations in hand position to increase the dataset's diversity. Each gesture is represented by 8 different ways, where the hand position was slightly modified between each sample. These real data were used as a basis for generating synthetic data.

By using the functions in the files "multiply_files.txt" and "add_gaussian_noise.txt," the dataset was expanded and made more realistic by adding Gaussian noise to the images. Therefore, the ris_random and ris_optimized folders contain 10 frames × 8 measurements × 3 gestures = 240 files, while the ris_random2 and ris_optimized2 folders contain 1 × 8 measurements × 3 gestures = 24 files. **Functions**

• **add_gaussian_noise.txt:** This script adds Gaussian noise to the images to simulate real-world conditions and improve the robustness of the model.
• **compact_files_frames.txt:** This script combines multiple frames into a single image, which can be useful for certain types of analysis.