Experience of adults with upper-limb difference and their views on sensory feedback for prostheses: a mixed methods study.

BACKGROUND: Upper-limb prostheses are regularly abandoned, in part due to the mismatch between user needs and prostheses performance. Sensory feedback is among several technological advances that have been proposed to reduce device abandonment rates. While it has already been introduced in some high-end commercial prostheses, limited data is available about user expectations in relation to sensory feedback. The aim of this study is thus to use a mixed methods approach to provide a detailed insight of users' perceptions and expectations of sensory feedback technology, to ensure the addition of sensory feedback is as acceptable, engaging and ultimately as useful as possible for users and, in turn, reduce the reliance on compensatory movements that lead to overuse syndrome. METHODS: The study involved an online survey (N = 37) and video call interviews (N = 15) where adults with upper-limb differences were asked about their experience with limb difference and prosthesis use (if applicable) and their expectations about sensory feedback to prostheses. The survey data were analysed quantitatively and descriptively to establish the range of sensory feedback needs and their variations across the different demographics. Reflexive thematic analysis was performed on the interview data, and data triangulation was used to understand key behavioural issues to generate actionable guiding principles for the development of sensory feedback systems. RESULTS: The survey provided a list of practical examples and suggestions that did not vary with the different causes of limb difference or prosthesis use. The interviews showed that although sensory feedback is a desired feature, it must prove to have more benefits than drawbacks. The key benefit mentioned by participants was increasing trust, which requires a highly reliable system that provides input from several areas of the hand rather than just the fingertips. The feedback system should also complement existing implicit feedback sources without causing confusion or discomfort. Further, the effect sensory feedback has on the users' psychological wellbeing was highlighted as an important consideration that varies between individuals and should therefore be discussed. The results obtained were used to develop guiding principles for the design and implementation of sensory feedback systems. CONCLUSIONS: This study provides a mixed-methods research on the sensory feedback needs of adults with upper-limb differences, enabling a deeper understanding of their expectations and worries. Guiding principles were developed based on the results of a survey and interviews to inform the development and assessment of sensory feedback for upper-limb prostheses.

Pig Ulnar Nerve Recording with Sinusoidal and Temporal Interference Stimulation.

Temporal interference stimulation has been suggested as a method to reach deep targets during transcutaneous electrical stimulation. Despite its growing use in transcutaneous stimulation therapies, the mechanism of its operation is not fully understood. Recent efforts to fill that gap have focused on computational modelling, in vitro and in vivo experiments relying on physical observations - e.g., sensation or movement. This paper expands the current range of experimental methods by demonstrating in vivo extraneural recordings from the ulnar nerve of a pig while applying temporal interference stimulation at a location targeting a distal part of the nerve. The main aim of the experiment was to compare neural activation using sinusoidal stimulation (100 Hz, 2 kHz, 4 kHz) and temporal interference stimulation (2 kHz and 4 kHz). The recordings showed a significant increase in the magnitude of stimulation artefacts at higher frequencies. While those artefacts could be removed and provided an indication of the depth of modulation, they resulted in the saturation of the amplifiers, limiting the stimulation currents and amplifier gains used. The results of the 100 Hz sine wave stimulation showed clear neural activity correlated to the stimulation waveform. However, this was not observed with temporal interference stimulation. The results suggest that, despite its greater penetration, higher currents might be required to observe a neural response with temporal interference stimulation, and more complex artefact rejection techniques may be required to validate the method.

Tutorial: a guide to techniques for analysing recordings from the peripheral nervous system.

The nervous system, through a combination of conscious and automatic processes, enables the regulation of the body and its interactions with the environment. The peripheral nervous system is an excellent target for technologies that seek to modulate, restore or enhance these abilities as it carries sensory and motor information that most directly relates to a target organ or function. However, many applications require a combination of both an effective peripheral nerve interface (PNI) and effective signal processing techniques to provide selective and stable recordings. While there are many reviews on the design of PNIs, reviews of data analysis techniques and translational considerations are limited. Thus, this tutorial aims to support new and existing researchers in the understanding of the general guiding principles, and introduces a taxonomy for electrode configurations, techniques and translational models to consider.

Sensory Feedback for Upper-Limb Prostheses: Opportunities and Barriers.

The addition of sensory feedback to upper-limb prostheses has been shown to improve control, increase embodiment, and reduce phantom limb pain. However, most commercial prostheses do not incorporate sensory feedback due to several factors. This paper focuses on the major challenges of a lack of deep understanding of user needs, the unavailability of tailored, realistic outcome measures and the segregation between research on control and sensory feedback. The use of methods such as the Person-Based Approach and co-creation can improve the design and testing process. Stronger collaboration between researchers can integrate different prostheses research areas to accelerate the translation process.

Array processing of neural signals recorded from the peripheral nervous system for the classification of action potentials.

BACKGROUND: Recording from the peripheral nervous system is key in the development of implantable neural interfaces. Despite a long history of using implantable electrodes for neuro-stimulation, it is difficult to make recordings from the nerves as signal amplitudes are often too small to be detected. Methods exist that are suitable for recording evoked potentials, but these require artificial stimulation of the nerve and thus have limited use in implanted neural interfaces. NEW METHOD: In order to address these issues new methods are developed to analyse spontaneously occurring action potentials by extending an approach called velocity selective recording, which uses longitudinally spaced electrodes to record action potentials as they propagate. The new methods using image processing techniques to automatically identify and classify action potentials without any prior knowledge of their morphology. RESULTS: Simulations are developed to test the methods, and a detailed experimental validation is performed using in-vivo recordings from the L5 dorsal rootlet of rat. Results show that this new approach can discriminate action potentials from both simulated and real recordings and the experimental validation demonstrates an ability to detect dermal stimulation by changes in the firing patterns of different axons. COMPARISON TO EXISTING METHODS: This framework, unlike existing methods, is intrinsically suitable for recordings of spontaneous neural activity. Further it improves upon both the computational complexity and the overall performance of existing methods. CONCLUSION: It is possible to perform on-line discrimination and identification of action potentials without any prior knowledge of their morphology using new image processing inspired methods.

A New Method for Neural Spike Alignment: The Centroid Filter.

Recordings made directly from the nervous system are a key tool in experimental electrophysiology and the development of bioelectronic medicines. Analysis of these recordings involves the identification of signals from individual neurons, a process known as spike sorting. A critical and limiting feature of spike sorting is the need to align individual spikes in time. However, electrophysiological recordings are made in extremely noisy environments that seriously limit the performance of the spike-alignment process. We present a new centroid-based method and demonstrate its effectiveness using deterministic models of nerve signals. We show that spike alignment in the presence of noise is possible with a 30 dB reduction in minimum SNR compared with the conventional methods. We present a mathematical analysis of the centroid method, characterizing its fundamental operation and performance. Furthermore, we show that the centroid method lends itself particularly well to hardware realization, and we present results from a low-power implementation that operates on an FPGA, consuming ten times less power than conventional techniques - an important property for implanted devices. Our centroid method enables the accurate alignment of spikes in sub-0 dB SNR recordings and has the potential to enable the analysis of spikes in a wider range of environments than has been previously possible. Our method thus has the potential to influence significantly the design of electrophysiological recording systems in the future.