## 1 Introduction  
The human hand is a masterpiece of working capabilities, and so researchers have been struggling to replace the lost functionalities of arm (and/or forearm) amputees by means of more and more sophisticated sensorized prostheses [1; 2; 3]. Allowing even a partial recovery of full functionalities can significantly increase the quality of amputees' lives. Accordingly, current upper-limb prostheses, particularly those including hand segments, can be articulated by interpreting myoelectric signals gathered on the amputated limb [4; 5; 6; 7], allowing some form of grasping and manipulation.  
However, in general, the higher the degree of functionality of the prosthesis, the greater the training time and efforts required for the amputee to be confident with the electromechanical arm [8; 9]. In particular, three main aspects can be underlined: the user's need to become familiar with an \"unnatural appendix\", also from a psychological point of view, the dull and annoying training time needed from the user; and the correct recognition of the user's intentions to correctly drive the prosthetic hand. Accordingly, a key rule can be played by preventive training activities to be carried out in safe environments, which virtual environments can act as [10; 11; 12; 13], allowing the identification of possible functional customisations before the actual physical prosthesis is completed and mounted onto the amputated limb.  
Within this frame and scientific background, the use of virtual reality and the building of digital twins can be very helpful tools for improving training, even for the use of complex and advanced prostheses. On the other hand, as far as we know, examples of their full integration are still missing. For this reason, we propose a new, ad hoc-developed, interactive training methodology for amputees to become confident with a sensorized upper-limb prosthesis, based on the advantages offered by virtual reality environmentsand simulation numerical models, by combining computer graphics, multibody simulation, computer vision, sensors, and virtual reality.  
The main goal is to integrate different computer-aided methodologies to build a comprehensive digital twin to be integrated into a virtual reality environment. This environment will contain a series of standardized exercises aimed at reducing the training time required to use a sensorized prosthesis. Although the procedure is developed and tested specifically for the iHannes prosthesis, made by the INAIL Italian Centre for Prosthetics and the Italian Institute of Technology (IIT) [14; 15], the proposed algorithms are generally applicable to any type of sensorized upper-limb prosthesis.  
The main novelty of this investigation is the integration of different methodologies into a self-contained approach and an immersive virtual environment (a fully functional digital twin). The combined use of advanced simulation models; a sequential impulse solver; and digital twins with real-time gesture classification, object interaction, realistic deformation of the skin, and quantitative virtual training exercises is suitable for a comprehensive virtual training environment. We believe that, apart from this specific implementation, this approach can be used for other prosthesis training procedures.  
This work can be split into three main parts: the sensorized upper-limb prosthesis with myoelectric inputs; the digital replica of the complex system (namely, the digital twin) of the prosthesis, focusing on the algorithms, numerical models, and implementation procedures; and the training tests and usability concerns. The specific background and state of the art of each integrated methodology are included in Section 3 and split into each digital-twin component.