Generating tactile afferent stimulation patterns for slip and touch feedback in neural prosthetics

Abstract

Current prosthetic limbs are limited by a lack of tactile feedback. Slip feedback is particularly important to inform grip. Object slip is marked by both a change in the normal grip force applied and a change in force tangential to the fingertips. In this study, we demonstrate that a new multi-axial tactile sensor composed of gold nanoparticle strain gauges is able to record slip and reconstruct the X, Y, and Z forces incident on the sensor's surface due to a slipping object. We entered the X, Y, and Z force components generated by the slip event into a noisy leaky integrate and fire model to simulate the firing responses of SA1 and FA1 afferents. We also recorded a uniaxial normal force input representative of tactile contact. A single set of SA1 model and FA1 model parameters generated realistic firing patterns for both the slip and normal force recordings. These results suggest that canonical SA1 and FA1 afferent models could be used to generate biomimetic electrical stimulation patterns for both slip and touch stimuli. When used to activate the tactile afferents of an amputee, these electrical stimulation patterns could create natural and distinguishable slip and touch percepts for closed loop control of an upper limb neural prosthesis.

Tapping Into the Language of Touch: Using Non-invasive Stimulation to Specify Tactile Afferent Firing Patterns

“…The strength of such an approach is that potentially useful information, whose encoding we do not yet understand, is not discarded. This approach is behind one technique we have employed (Rager et al, 2013) to preserve spike firing patterns related to environmental features down to sub-millisecond precision. We built a library of virtual tactile afferent neurons by training noisy integrate-and-fire neurons (Paninski et al, 2004) on data derived from real afferents while driving them through artificial sensors given the same set of mechanical stimuli.…”

Implantable Neural Interfaces and Wearable Tactile Systems for Bidirectional Neuroprosthetics Systems

“…This biomimetic system is also used to identify shape and movement of objects, detect braille characters and, when connected to efferent nerves of a cockroach, it demonstrated a hybrid bioelectronic reflex arc and control biological muscles. This promising study can be included in the general framework of neuromorphic technology in neuroprosthetics with potential future applications in neurorobotics.…”

“…Comparison among different strategies of stimulation of PNS to evoke tactile percepts. Parameters that have been considered are: i) number of subjects (S) and implant duration; ii) type of implanted electrode, number of channels, nerve target; iii) impedance measurement; iv) type of stimulation pattern; v) threshold charge/current over time; vi) …”

Tactile afferents encode grip safety before slip for different frictions

“…Further advances in the control of sophisticated robotic manipulators and smart prostheses will not be possible without inspiring innovations in the design of tactile sensors and associated signal analyses algorithms. An understanding of the encoding of tactile stimuli which are relevant to object manipulation could lead to the development of improved biomimetic artificial sensors which might also be able to replace (in whole or in part) lost sensory information for amputees, improving sensorimotor control of prosthetic limbs [9].…”