Development of novel, highly integrated multisensory interfaces for upper limb prosthetic system control

This work explores new ways to improve upper-limb prostheses so they can become more natural, versatile, and adaptive for the users. Three main technical and scientific challenges are addressed: how to make the prosthesis more dexterous, how to better capture the user’s intention via electromyographic signals, and how to enhance the coadaptation between the prosthesis and the user. After presenting motivation and research context (Chapter 1), we provide a comprehensive background of the current state of the art of upper limb prosthetic developments and control strategies (Chapter 2). Building from the prosthetic hand system Hannes with the purpose of augmenting its versatility in daily tasks, we present new mechatronic modules (Chapter 3). This includes a two-degrees of freedom wrist and additional in-hand mechanisms for thumb and tridigital grasps, fully integrated in a functional prosthetic system for daily use. These mechanisms have been validated against able-bodied kinematic and dynamic performances and tested on an amputee subject using a low-density EMG Machine Learning control strategy. We then introduce two novel HD-EMG systems and intention detection strategies (Chapter 4), tailored to the requirements of a realistic prosthesis. Having a richer set of input signals promote natural and more accurate control of a wider range of movements, combining with conventional and Deep Learning approaches. Despite these advancements, these strategies fail to compensate for variability over time of EMG signals. Therefore, we explore real-time interactive incremental learning frameworks (Chapter 5), enabling users to improve the intention detection model in a simple and intuitive way with a minimum amount of data. By embedding incremental learning into the prosthesis hardware and control, the model adapts as needed to the natural variability of muscle signals, to better align with user’s intention over time. Together, these advances show some promising paths to bring upper-limb prostheses closer to user needs.