The versatility of the hands is revealed in its movements, but often not noticed before trauma occurs. Joint range of motion is used as a measure to follow the progress of diseases. A digital workflow for 3D data in medical appliances is envisioned for years. The aim of this research is to develop a method that reliably and reproducability determine the range of motion of the digits. In current practice, the angles are measured using a goniometer. This method is very imprecise. Three methods to determine the location of joints in 3D hand scans can be distinguished: using heuristics, computer vision, and deep learning. Of those, deep learning is the most flexible, modern and accurate method and is therefore applied. The end result is a matrix containing the range of motion per joint and is applied to anatomically correctly manipulate a 3D model. For ease of manipulation, a physical manipulator is proposed. The results of this novel method show lower interrater differences than measurements with a goniometer.

In 2010, an estimated 15 million infants were born prematurely, which makes up 10% of all childbirths that year. Just in the Netherlands there were 11,530 preterm births in 2018. Since these children should be spending additional months inside of the uterus, they are delicate and need to grow until near regular gestational age inside of an incubator in the neonatal intensive care unit (NICU), which provides these children with clean, humid, and warm air. One important part of the care of these infants is keeping track of their development, in order to adjust nourishment, as well as spot possible complications early. A regular part of these measurements is the head circumference (HC) measurement. This measurement is performed by two nurses, one holding the infant still while another winds a tape measure around the delicate head, in order to take the measurement. Unfortunately, this process causes the infant to stress, which is correlated to an increased chance in reduced neurological development of the infant. Therefore, Vectory3, a company specialized in 3D scanning for healthcare, commissioned a project to create an alternative way to take this measurement, which would cause the infant less stress than the current method. During this project, this alternative has been conceived and developed into a functional prototype: MONITOR3D. MONITOR3D makes use of 3 hybrid photogrammetry cameras in order to take a contactless 3D capture of the infant’s head, allowing NICU staff to measure the 3D model after acquisition, instead of measuring the child directly. MONITOR3D’s cameras are housed in an unobtrusive shell which is placed on top of the incubator hood, staying outside of the hygienic zone of the child during use. Though the hardware for MONITOR3D is already in a functional state, providing higher accuracy than the current tape measure-based measurements, the software still consists of unmodified open-source software, for which a simple but relatively time consuming (compared to tape measuring) workflow has been developed. The current prototype of MONITOR3D is thus not ready to be used by regular in a NICU setting. However, it can possibly be used for research purposes in its current state. Future developments should focus mainly on the software part of the product, automating as many of the mesh processing steps as possible, in order to make the device usable in a live NICU environment as alternative to the current tape measure.