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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - BIREHAB (Increasing the robustness and neural integration of bidirectional prostheses for rehabilitation withrobust and real time Independent Component Analysis)

Teaser

Summary

Hand loss is a highly disabling condition that adversely affects the quality of life, independence and mobility. Prostheses are only as useful as the richness of the sensation (i.e., â€œnaturalâ€ - or as close to natural as possible - sensory feedback) and dexterity (ease of control and capabilities close to the intact human hand) that they provide. Most of the effort must be therefore directed towards the achievement of both natural prosthesis control and sensory feedback integration to overcome the barriers to effective usability of hand prostheses by patients and enable the personalization of rehabilitation protocols. BIREHAB has been developed in this framework with the aims of (i) determining the cognitive cortical mechanisms underlying tactile stimuli perception and (ii) simultaneously achieving robust myoelectric control of prostheses.

Work performed

To determine the cognitive cortical mechanisms underlying tactile stimuli perception I have characterized the brain activity (Somatosensory Evoked Potentials â€“ SEPs) of four amputees while undergoing neuromorphic electrical stimulation, which produced somatotopic sensations of tingling on the phantom hand. Furthermore I recruited 10 healthy subjects at the Campus Biotech facilities and performed a similar experiment both to validate the findings on amputees and compare somatotopic (referred) and non-somatotopic (local) stimulation. Finally I characterized the neural correlates of actual tactile sensations delivered by gratings slid beneath a finger on healthy subjects in a controlled way. The results show that only somatotopic stimulation evokes SEPs compatible with their generation by dipoles located in the somatosensory cortex, and whose scalp distribution resembles that generated by real tactile stimulation on healthy subjects.

Regarding the second objective of the proposal, I have carried out several methodological activities to optimize the processing of electromyographic (EMG) and electroencephalographic (EEG) data by means of Blind Source Separation techniques, which I applied, along with novel signal processing methodologies, in several fields, namely to find the electrophysiological correlates of syntax, to determine the selectivity of visual cortical activation produced by optic nerve intraneural stimulation, to implement a data-driven bodyâ€“machine interface for the accurate control of drones. The results show that it is possible to combine reliable myoelectric control of prostheses and somatotopic stimulation to increase the robustness and neural integration of bidirectional prostheses.

Regarding dissemination and exploitation I have co-authored 11 journal papers (3 more in preparation), 5 papers at peer-reviewed conferences, I have participated to the Hannover Messe fair with a Startup project and I am in the process of preparing 3 patents. I have given 6 invited talks at conferences and workshops, taught lessons in 4 courses, regularly performed lab representation duties, supervised 15 students and regularly served as reviewer for various journals.

Final results

By studying the neural correlates of tactile stimulation both by mechanical (gratings) and electrical (median and ulnar nerve somatotopic stimulation) it was possible to determine consistent bilateral somatosensory evoked potentials, sensitive to the stimulation modality, whose study can be used to benchmark and optimize tactile sensory substitution capabilities of upper limb prostheses. Furthermore, thanks to the development and application of robust independent component analysis techniques and a platform for the unified and synchronized real time collection and analysis of multiple data sources, it was possible to demonstrate the possibility of achieving robust myoelectric control of prostheses and increase the robustness of multivariate data analyses also in several different domains.

These results are especially relevant for society and especially amputees. Currently prostheses are often rejected by patients, chiefly due to their lack of sensory feedback and cognitive workload required for their use. The results brought forward by the project have the potential to successfully address these issues and improve the long term efficacy and quality of hand prostheses, enabling in the future near-natural replacement of missing hands, as well as help devising new upper limb rehabilitation strategies.