This review demonstrates optimization frameworks for improving neuroprosthetic interfaces, highlighting clinical implications.
The electrical stimulation of the nervous system has shown great clinical potential in injury and pathology, yet experimentally driven practice makes it challenging to identify effective design choices and personalized stimulation protocols. This review outlines emerging model-based optimization frameworks that address these challenges by leveraging biophysical digital twins of neural interfaces. Enabling acceleration strategies and complementary data-driven approaches are also highlighted, along with key factors that currently limit clinical translation.
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Verardo et al. (2026) studied this question.
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