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Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia
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Head tremor in cervical dystonia: Quantifying severity with computer vision.

Jeanne P Vu1, Elizabeth Cisneros1, Ha Yeon Lee1

  • 1Institute for Neural Computation, University of California, San Diego, La Jolla, CA, USA.

Journal of the Neurological Sciences
|February 1, 2022
PubMed
Summary

A new computer vision system, CMOR, objectively measures head tremor (HT) severity in cervical dystonia (CD) using video recordings. This automated method shows strong agreement with clinical ratings, offering a more precise way to assess HT.

Keywords:
Computer visionHead tremorSeverity ratingTWSTRSVideo

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Area of Science:

  • Neurology
  • Biomedical Engineering
  • Medical Technology

Background:

  • Head tremor (HT) is a prevalent symptom in cervical dystonia (CD), often assessed subjectively.
  • Objective and automated methods for quantifying HT severity are needed.

Purpose of the Study:

  • Develop Computational Motor Objective Rater (CMOR), a computer vision system, to objectively quantify head tremor.
  • Assess oscillatory and directional aspects of HT from video recordings.
  • Validate CMOR's convergent validity with established clinical rating scales.

Main Methods:

  • Analyzed video recordings of 93 participants with isolated CD and HT.
  • Used CMOR to evaluate peak power, frequency, and directional dominance of head tremor.
  • Employed Spearman's correlation to compare CMOR measures with clinical ratings.

Main Results:

  • CMOR quantified head tremor power and peak frequency (1.95 Hz).
  • Pitch was the dominant tremor axis for 50% of participants, with significant contributions from secondary and tertiary axes.
  • CMOR's HT severity measure showed a significant positive correlation with the Toronto Western Spasmodic Torticollis Rating Scale-2 (rho=0.54, p<0.001).

Conclusions:

  • A novel, objective method for measuring head tremor severity in cervical dystonia has been developed.
  • CMOR utilizes conventional video recordings to quantify complex HT characteristics.
  • The system demonstrates convergent validity with clinical assessments, supporting its utility in research and practice.