Encoding algorithms for somatotopic restoration of somatic sensations in the upper-limb: a systematic review.

Abstract

Objective.Sensory feedback restoration represents a fundamental need for upper limb prosthesis users because it permits to feel somatic sensations during interactions with the environment. Considering the artificial sensory transduction, neuroprotheses should take advantage of effective encoding algorithms, which have the essential role, in the sensory feedback process, of coding the intended perception to the individual with the amputation. This paper presents a literature systematic review of the encoding algorithms employed for somatotopically restoring somatic sensations in upper limb of individuals with the intact arm or with an amputation.Approach.The methodologies adopted for the development of the encoding algorithms were deeply analyzed to describe what is the current state of the art on this topic. Encoding algorithms validated in literature on upper limb were grouped into three main categories (Function-based,Bio-inspiredandHybrid) and then compared and described.Main results.Function-based Algorithmsprovide the user with high sensitivity, whereas if the verisimilitude to natural sensation and complexity are the most desirable features for sensory feedback, aBio-inspiredstrategy would be the most suitable to implement. However,Hybridsolutions both evoked realistic sensations and enhanced discrimination capabilities.Significance.The conducted analysis represents a guide for understanding which type of encoding to choose, making a compromise between the characteristics of the elicited sensations and the achieved performance. This critical analysis will give the reader important information for understanding the potentiality of the encoding strategies to elicit different sensations for a specific application and for developing novel sensory restoration approaches.