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Quantitative assessments of finger individuation with an instrumented glove.

Brian J ConwayLéon TaquetTimothy F BoergerSarah C YoungKate B KrucoffBrian D SchmitMax O Krucoff
Published in: Journal of neuroengineering and rehabilitation (2023)
Here we provide a set of normative values for three separate finger individuation scores in healthy adults with a commercially available instrumented glove. Each score emphasizes a different aspect of finger individuation performance and may be more uniquely applicable to certain clinical scenarios. We hope for this platform to be used within and across centers wishing to share objective data in the physiological study of hand dexterity. In sum, this work represents the first healthy participant data set for this platform and may inform future translational applications into motor physiology and rehabilitation labs, orthopedic hand and neurosurgery clinics, and even operating rooms.
Keyphrases
  • electronic health record
  • high throughput
  • big data
  • primary care
  • data analysis
  • machine learning