Table 1 Key points for clinical translation of projects involving computational modeling in neurorehabilitation

• Identify your ultimate clinical endpoint, even if translation is far in the future

• Distinguish between hypothesis-driven and data-driven models

• Be precise about hypothesized biological processes and levels of abstraction

• Understand and contextualize outcome measures

• Clinical and computational collaboration are necessary to move neurorehabilitation devices into the clinic

• Modeling rehabilitation data “in the wild” will introduce new sources of variability but is essential for clinical translation

• Increasing clinical touchpoints (data collection, device testing, brainstorming and discussion) is a good research investment