Automated Limb Volumetry System for Lymphedema Screening via a 1D Convolutional Neural Network-Based Volume Correction Algorithm

This dataset contains the supporting materials associated with the study “Automated Limb Volumetry System for Lymphedema Screening via a 1D Convolutional Neural Network-Based Volume Correction Algorithm.” The study develops an automated limb volume measurement system using motor-driven infrared grating scanning and a 1D-CNN-based volume correction framework. Data were collected from 14 healthy participants, including measurements from 28 arms. Simulated limb swelling was created using predefined EVA foam volume increments and different attachment patterns, resulting in 1,596 samples. Each sample contains an original one-dimensional infrared grating sequence and a corresponding reference volume. The repository includes the main lymphedema project materials, software deployment documentation, hardware parts lists, the volume correction algorithm, 3D structural design files, and experimental data. These resources are provided to support reproducibility, validation, and further research on automated limb volumetry, lymphedema screening, infrared sensing, and deep learning-based volume correction.