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Multimodal measurement of hand function with the SensorE Exoskeleton: a validation study.

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A new wearable device, the SensorE Exoskeleton (SEE), accurately measures finger flexion and force. This objective tool offers improved sensitivity for tracking hand function during rehabilitation, especially after stroke.

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Wearable Sensors

Background:

  • Strokes frequently result in persistent upper extremity impairments.
  • Current clinical assessments for hand function lack objectivity and sensitivity.
  • Objective, multimodal measurement tools for hand function are scarce.

Purpose of the Study:

  • To design and validate the SensorE Exoskeleton (SEE), a novel wearable device.
  • To simultaneously quantify finger flexion and applied fingertip force.
  • To provide a sensitive alternative to subjective clinical assessments for hand function.

Main Methods:

  • The SEE integrates flex and force sensors into a lightweight wearable design.
  • Thirty healthy participants performed graded finger tasks guided by a GUI.
  • SEE measurements were validated against a motion capture system and a load cell.

Main Results:

  • SEE reliably distinguished between different levels of finger movement and force (p < 0.05).
  • Flex sensor data showed strong correlation with motion capture (|r| > 0.7).
  • Force sensor data correlated well with load cell measurements (|r| > 0.7) with low relative errors.

Conclusions:

  • The SEE offers accurate, objective, and sensitive tracking of finger flexion and force.
  • This multimodal wearable device has potential as a novel functional assessment tool in rehabilitation.
  • Future validation in stroke and other patient populations is warranted.