Abstract: A system, method, and computer readable medium for measuring limb range of motion. The method includes initializing a scanning area. A classifier trained to recognize limbs is loaded into memory. A frame representing a 3D point cloud having at least one limb of a person in motion is captured. A box fitting algorithm is performed on the captured at least one limb to enable the classifier to identify the at least one limb. One or more boxes generated from the box fitting algorithm are sliced into a plurality of 2D point clouds to measure and record the circumference of each 2D point cloud to obtain limb range of motion parameters. The limb range of motion parameters are a maximum and a minimum size of the at least one limb as a function of soft tissue expansion and contraction of the limb while under pressure, force, and/or motion.

Abstract: A system, method, and computer readable medium for measuring limb range of motion. The method includes initializing a scanning area. A classifier trained to recognize limbs is loaded into memory. A frame representing a 3D point cloud having at least one limb of a person in motion is captured. A box fitting algorithm is performed on the captured at least one limb to enable the classifier to identify the at least one limb. One or more boxes generated from the box fitting algorithm are sliced into a plurality of 2D point clouds to measure and record the circumference of each 2D point cloud to obtain limb range of motion parameters. The limb range of motion parameters are a maximum and a minimum size of the at least one limb as a function of soft tissue expansion and contraction of the limb while under pressure, force, and/or motion.