Flexible Carbon-Based Electronics and Sensorized Neuroprosthesis

In the United States alone, there are more than 2 million people living with limb loss and prosthetic devices have long been the solution to recover their activities of daily living. However, many of the prosthetic users reported their dissatisfaction with current prostheses and some even abandoned theirs due to poor comfort and limited performance. To improve prosthetic control, advancements in surgical interfaces and sensorized neuroprosthesis are two major focus and have seen great potential. Both perspectives are presented in this work. Several reinnervated muscle surgeries have been invented to enable a better communication with muscle and nerves and a stable interface is essential to record robust muscle signals which are utilized to control a neuroprosthesis. Each muscle target may have slightly different anatomy and the current state-of-the-art implantable electrodes are complex and not easily reproducible and customizable. To address this problem, I present a simple, rapid electrode fabrication method to record muscle signals and easy-to-use electrode materials using carbon black/polydimethylsiloxane (PDMS) composite. Acute in vivo testing shows that the electrodes are highly functional and have the potential to enable large-scale muscle signal recordings with extensive data to improve the neuroprosthetic control. In addition to novel neural interfaces, sensory perception is also critical to improve the manipulation of objects with a prosthesis and enhances prosthetic performance and embodiment with feedback to the user. With recent advances in tactile sensing technology and neuromorphic stimulation interface, efficient real-time communication and functioning between them are still missing. In this work, I build and test a closed-loop system that integrates tactile sensing and neuromorphic electrical stimulation. The system functions in real time and the parameters of the sensory stimulation through transcutaneous electrical nerve stimulation (TENS) convey temporal information and dynamically change responding to real-time tactile data

Soft Biomimetic Finger with Tactile Sensing and Sensory Feedback Capabilities

The compliant nature of soft fingers allows for safe and dexterous manipulation of objects by humans in an unstructured environment. A soft prosthetic finger design with tactile sensing capabilities for texture discrimination and subsequent sensory stimulation has the potential to create a more natural experience for an amputee. In this work, a pneumatically actuated soft biomimetic finger is integrated with a textile neuromorphic tactile sensor array for a texture discrimination task. The tactile sensor outputs were converted into neuromorphic spike trains, which emulate the firing pattern of biological mechanoreceptors. Spike-based features from each taxel compressed the information and were then used as inputs for the support vector machine (SVM) classifier to differentiate the textures. Our soft biomimetic finger with neuromorphic encoding was able to achieve an average overall classification accuracy of 99.57% over sixteen independent parameters when tested on thirteen standardized textured surfaces. The sixteen parameters were the combination of four angles of flexion of the soft finger and four speeds of palpation. To aid in the perception of more natural objects and their manipulation, subjects were provided with transcutaneous electrical nerve stimulation (TENS) to convey a subset of four textures with varied textural information. Three able-bodied subjects successfully distinguished two or three textures with the applied stimuli. This work paves the way for a more human-like prosthesis through a soft biomimetic finger with texture discrimination capabilities using neuromorphic techniques that provides sensory feedback; furthermore, texture feedback has the potential to enhance the user experience when interacting with their surroundings. Additionally, this work showed that an inexpensive, soft biomimetic finger combined with a flexible tactile sensor array can potentially help users perceive their environment better

Evoked Somatosensory Feedback for Closed-Loop Control of Prosthetic Hand

Somatosensory feedback, such as tactile and proprioceptive feedback, is essential to our daily sensorimotor tasks. A lack of sensory information limits meaningful human-machine interactions. Different somatosensory feedback strategies have been developed in recent years. Non-invasive sensory substitutional approaches often evoke sensations that are unintuitive, requiring extensive sensory training. Alternatively, invasive neural stimulation can elicit intuitive percepts that are interpretable readily by prosthetic hand users; however, the invasive nature of the procedure limits wide clinical applications. To overcome these issues, we developed a multimodal sensory feedback approach that delivers tactile and proprioceptive information non-invasively. We used a skin-surface nerve stimulation array to target afferent fibers in the peripheral nerves, which can elicit intuitive tactile feedback at the fingertips. We used a vibrotactile array to deliver proprioceptive percepts encoding kinematic information of prosthetic joints. First, we evaluated whether the peripheral nerve stimulation technique could be used for the recognition of object properties. Evoked tactile sensations were modulated using forces recorded by a sensorized prosthesis not actively controlled by the users. We demonstrated that the elicited tactile sensation at the fingertips can enable recognition of object shape and surface topology. Second, we evaluated how evoked tactile feedback can be integrated into the functional utility of a prosthetic hand. We quantified the benefits of tactile feedback under different myoelectric control strategies, when participants performed an object manipulation task. We showed an improved task success rate and reduced muscle activation effort when tactile feedback was provided. Finally, we investigated whether multimodal (tactile and proprioceptive) feedback can enable the recognition of more complex object properties during active control of a prosthetics hand. We found that integrated tactile and proprioceptive feedback allowed for simultaneous recognition of multiple object properties (size and stiffness) in individuals with and without an arm amputation. Overall, this work demonstrates that artificially evoked somatosensory feedback can be utilized effectively to improve the closed-loop control of prostheses. These outcomes highlight the critical role of somatosensory feedback during human-machine interactions, which can enhance functional utility of prosthetic devices and promote user experience and confidence.Doctor of Philosoph