Using multiple high-count electrode arrays in human median and ulnar nerves to restore sensorimotor function after previous transradial amputation of the hand

Abstract

Peripheral nerve interfaces that can record from and stimulate large numbers of different nerve fibers selectively and independently may help restore intuitive and effective motor and sensory function after hand amputation. To this end, and extending previous work in two subjects, two 100-electrode Utah Slanted Electrode Arrays (USEAs) were implanted for four weeks in the residual ulnar and median nerves of a 50-year-old male whose left, dominant hand had been amputated 21 years previously. Subsequent experiments involved 1) recording from USEAs for real-time control of a virtual prosthetic hand; 2) stimulation to evoke somatosensory percepts; and 3) closed-loop sensorimotor control. Overall, partial motor control and sensation were achieved using USEAs. 1) Isolated action potentials recorded from nerve motor fibers, although sparse at these distal implant sites, were activated during fictive movements of the phantom hand. Unlike in our previous two subjects, electromyographic (EMG) activity contributed to most online recordings and decodes, but was reduced in offline analyses using common average referencing. Online and offline Kalman-filter decodes of thresholded neural or EMG spikes independently controlled different digits of the virtual hand with one or two degrees of freedom. 2) Microstimulation through individual electrodes of the two USEAs evoked up to 106 different percepts, covering much of the phantom hand. The subject discriminated among five perceived stimulus locations, and between two somatosensory submodalities at a single location. 3) USEA-evoked percepts, mimicking contact with either a near or distal virtual target, were used to terminate movements of the virtual hand controlled with USEA recordings comprised wholly or mostly of EMG. These results further indicate that USEAs can help restore sensory and motor function after hand loss.

Simulating tactile signals from the whole hand with millisecond precision

“…57). Also, the model will be valuable in neuroprosthetic applications that aim to restore the sense of touch through peripheral nerve interfaces (58)(59)(60). Indeed, the output of sensors on the prosthesis during object contact can be used as input to the simulated afferents, which then provide an accurate representation of how the nerve from an intact hand would respond to object contact.…”

Pursuing prosthetic electronic skin

“…Intracortical electrode 101,102 Epidural electrode 97,104 Optical fibre [113][114][115] Micro-light-emitting diode 118,120 Magnetic generator for transcranial magnetic stimulation 13,100 Interface with peripheral nervous system Surface electrode 105 Extra-fascicular electrode 106,107 Intra-fascicular electrode 108,109 Surface light pulse 116 Optical nerve cuff 117 Although the number of sensory signals that can be injected into the nervous system is currently limited, even a small number of sensors can substantially improve the utility of prosthetic devices 90,110 . To recover the ability to sense more complex stimuli such as surface textures and object shape, a large number of receptors is necessary.…”

Key considerations in designing a somatosensory neuroprosthesis

“…The other family of approaches consists of activating, using electrical stimulation, the neuronal populations that would be activated if the limb and nervous system were intact. For amputees, somatosensory restoration involves interfacing with the nerve using chronically implanted multi-electrode arrays (Clark et al, 2014;Dhillon and Horch, 2005;Raspopovic et al, 2014;Tan et al, 2014). For tetraplegic patients, somatosensory feedback is conveyed by directly stimulating the brain, somewhere along the neuraxis from the brain stem through the somatosensory cortex (Bensmaia and Miller, 2014;Cushing, 1909;Dadarlat et al, 2015;Davis et al, 1998;Fitzsimmons et al, 2007;Kim et al, 2015;O'Doherty et al, 2009;O'Doherty et al, 2011;O'Doherty et al, 2012;Penfield and Boldrey, 1937;Richardson et al, 2016;Romo et al, 1998;Tabot et al, 2013).…”