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Development of a Drawing Application to Evaluate Hand and Wrist Function: A Pilot Study.

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Summary

A new digital drawing app objectively measures hand function by analyzing drawing features. This technique differentiates patients from controls and correlates with patient-reported outcomes, offering a novel assessment tool.

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Area of Science:

  • Biomedical Engineering
  • Digital Health
  • Rehabilitation Technology

Background:

  • Assessing hand function is crucial for diagnosing and managing various conditions.
  • Traditional methods can be subjective or time-consuming.
  • Objective, digital tools are needed for precise hand function evaluation.

Purpose of the Study:

  • To validate a custom digital drawing application for assessing hand function.
  • To identify drawing features indicative of hand function.
  • To correlate drawing features with established patient-reported outcome measures (PROMs).

Main Methods:

  • Participants drew shapes on an iPad using a custom digital pen application.
  • Kinematic, geometric, and pressure-based features were extracted from 142 hand drawings.
  • Random forest models classified patients versus controls and assessed correlations with PROMs.

Main Results:

  • Numerous drawing features differed significantly between patients and controls (P < 0.05).
  • Circle drawings and pressure features proved most informative.
  • Classification models demonstrated good performance (AUC 0.82-0.84, F1 0.78-0.81).
  • Drawing features strongly correlated with validated PROMs (P < 0.001).

Conclusions:

  • A novel digital drawing technique objectively measures hand function.
  • This method effectively differentiates patients from healthy controls.
  • Drawing-based assessment shows promise as a reliable tool for hand function evaluation.