Adaptive Neural Interface to Control Prosthetic Devices: Design, Fabrication, Performance, and Evaluation

<p dir="ltr">In the face of technological leaps and bounds, numerous challenges persist, particularly those linked to physical disability resulting from accidents, congenital conditions, or health-related issues. One such profound challenge is the loss of a limb, an issue that, despite considerable advancements in the field of prosthetics, remains considerable in its impact. Crucially, the development of portable technologies, specifically neural interfaces, that are robust enough for every day, outside-the-laboratory use poses a significant obstacle.</p><p dir="ltr">As such, we find ourselves still reliant on harnesses and pulley systems that have seen limited evolution over the last century. These often lead to changes in the residual limb's volume, subsequent muscle atrophy, and chronic pain. This thesis shifts its focus to the increasing field of neural interfaces. Over time, these interfaces have experienced a trajectory of consistent evolution and improvement, a pathway we hope will capture the interest of research groups globally, instigating further enhancement in devices used for recording and providing feedback to the peripheral nervous system.</p><p dir="ltr">This dissertation will delve into a comprehensive discussion of various aspects critical to the advancement of these interfaces. This includes an exploration of the requisite electrical specifications for their development, the mechanical challenges they pose, as well as the physiological response of the organism and the biological reactions following device implementation. Additionally, the materials used in the construction of these interfaces will be examined, alongside the evaluation of outcomes presented by various research groups.</p><p dir="ltr">A significant contribution of this research lies in the exploration of edge functionalized graphene (EFG) used in tandem with other polymers in the development of neural interfaces and associated devices. The development of fabrication methodologies for these materials can subsequently be extended to the manufacturing of other devices.</p><p dir="ltr">This research also demonstrates that neural cuffs can be effectively evaluated using testing techniques commonly applied within the realm of soft robotics, such as finite element analysis. This approach provides a mechanism to predict the mechanical behaviour of the interface accurately. As such, this study holds potential to function as a comprehensive guide for the in-vitro testing of similar devices, facilitating other researchers in following the established protocols and furthering the field's collective knowledge.</p>