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Related Experiment Video

Updated: Jun 4, 2025

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes
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Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

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Using a Webcam to Assess Upper Extremity Proprioception: Experimental Validation and Application to Persons Post

Guillem Cornella-Barba1, Andria J Farrens1, Christopher A Johnson2

  • 1Department of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697, USA.

Sensors (Basel, Switzerland)
|December 17, 2024
PubMed
Summary

We developed OpenPoint, a webcam-based system to measure upper extremity (UE) proprioception. This technology accurately quantifies proprioceptive deficits, offering a new tool for clinical assessment.

Keywords:
computer visionhome-based rehabilitationpointing errorproprioception

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Computer Science

Background:

  • Proprioception deficits are common in various medical conditions.
  • Current assessment methods are often not easily deployable.
  • There is a need for accessible technologies to quantify proprioceptive impairments.

Purpose of the Study:

  • To develop and validate a novel, accessible method for quantifying upper extremity (UE) proprioception.
  • To assess the efficacy of the OpenPoint system in unimpaired individuals and post-stroke patients.

Main Methods:

  • Developed OpenPoint, a computer vision system using a webcam to automate a pointing task.
  • Quantified pointing error in the frontal plane using a deep-learning library (MediaPipe).
  • Validated the method in unimpaired adults and post-stroke participants, comparing results with a robotic assessment.

Main Results:

  • OpenPoint reliably detected increased pointing error when proprioceptive feedback was removed in unimpaired adults.
  • Post-stroke participants showed significantly increased pointing error (p < 0.001).
  • Pointing error correlated with independent robotic measures of finger proprioception (r = 0.62, p = 0.02).

Conclusions:

  • OpenPoint is a validated, novel method for assessing UE proprioception.
  • The system utilizes affordable computer technology, enabling widespread clinical and telemedicine use.
  • This technology has the potential to democratize quantitative proprioception testing.