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Personalised profiling to identify clinically relevant changes in tremor due to multiple sclerosis.

David G Western1,2, Simon A Neild3, Rosemary Jones4

  • 1Department of Mechanical Engineering, University of Bristol, University Walk, Bristol, BS8 1TR, UK. david.western@uwe.ac.uk.

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New tremor metrics improve sensor-based assessment for multiple sclerosis. These customized metrics better detect clinically relevant changes than traditional methods, aiding personalized treatment and clinical trials.

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Area of Science:

  • Neurology
  • Biomedical Engineering
  • Movement Disorders

Background:

  • Growing interest in sensor-based upper limb tremor assessment for multiple sclerosis and movement disorders.
  • Previous sensor-based methods lacked improvement over clinical observation due to poor test-retest repeatability.
  • A key barrier to sensor-based tremor assessment is distinguishing random variability from clinically relevant symptom changes.

Purpose of the Study:

  • To overcome the barrier of poor repeatability in sensor-based tremor assessment.
  • To develop customized tremor change metrics to differentiate random variability from clinically relevant symptom changes.
  • To compare newly proposed metrics against conventional clinical and sensor-based metrics in individuals with multiple sclerosis tremor.

Main Methods:

  • Developed novel 'change in scale' tremor change metrics, customized to individual tremor characteristics.
  • Compared proposed metrics against conventional clinical and sensor-based metrics in 24 individuals with multiple sclerosis tremor.
  • Evaluated metrics using Spearman rank correlation with Fahn-Tolosa-Marin Tremor Rating Scale (FTMTRS) subscales for functional disability (FTMTRS B) and self-assessed impact (FTMTRS C).

Main Results:

  • Newly proposed 'change in scale' metrics showed statistically significant correlations with changes in self-assessed tremor impact (max R²>0.5, p<0.05).
  • Proposed metrics outperformed conventional metrics in correlations with changes in task-based functional performance (R²=0.25 vs. R²=0.15).
  • The new metrics demonstrated improved sensitivity to change compared to conventional clinical observation.

Conclusions:

  • The proposed metrics enhance sensor-based tremor assessment sensitivity, surpassing conventional visual observation.
  • These findings suggest the main barrier to translational impact in sensor-based tremor assessment can be overcome.
  • Refined sensor-based tremor assessments could improve personalized treatment selection and clinical trial efficiency through standardization and sensitivity.