Development of an Adaptable 3D Rigged Model for the Design of Bespoke Devices for Upper Limb Rehabilitation

The human hand is a versatile and complex body part. It permits difficult movements with various degrees of precision and force. Several causes can lead to upper limb damage, including musculoskeletal disorders and diseases like stroke. The impairment can affect daily living activities. Patients usually undergo rehabilitation therapy with medical personnel for a long time after the traumatic event. In most cases, they use off-the-shelf medical devices. However, the shape of the upper limbs can differ a lot among people. A bespoke rehabilitative device could provide better comfort and usability, but the design process can be challenging. This work aims to present a digital workflow to generate a 3D virtual reconstruction of the patient’s upper limb structure, to be used in the device design. Starting from a 3D scan acquisition of the patient’s upper limb, the algorithm allows the creation of a polygonal mesh of the arm and the hand by a semi-automatic procedure. The algorithm uses neural networks’ capability to automatically detect the upper limb’s landmarks to localize the joints’ coordinates. The joints’ positions can be used to build a virtual skeleton for a 3D model of a human arm. The mesh of the model is subsequently wrapped around the scan of the real arm. The output consists in the 3D rigged model of the patient’s upper limb with a manifold mesh that can be deformed using its virtual skeleton. The results have been assessed with patients who had sports injuries or strokes. The 3D deviations between the scan acquisition of the arm and the resulting model have been evaluated.