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Design and Analysis for Fall Detection System Simplification
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Identifying falls remotely in people with multiple sclerosis.

Valerie J Block1, Erica A Pitsch2, Arpita Gopal2

  • 1Department of Neurology, UCSF Weill Institute for Neurosciences, University of California San Francisco, 1651 4th Street, Box 3126, San Francisco, CA, 94143, USA. Valerie.Block@ucsf.edu.

Journal of Neurology
|August 18, 2021
PubMed
Summary

Falling is a common and under-treated issue in multiple sclerosis (MS). The MS Walking Scale (MSWS-12) is a key predictor of falls, highlighting the need for better screening and intervention.

Keywords:
FallFallingMultiple sclerosisOutcome measurementQuality improvementRemote monitoring

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Area of Science:

  • Neurology
  • Rehabilitation Medicine
  • Clinical Research

Background:

  • Falling is prevalent in multiple sclerosis (MS) but often overlooked in clinical practice.
  • Under-ascertainment and under-treatment of falls in MS patients are significant concerns.

Purpose of the Study:

  • To evaluate fall risk factors in individuals with multiple sclerosis (MS).
  • To identify predictors of falling in the MS population.

Main Methods:

  • Recruited 94 individuals with MS (Expanded Disability Status Scale ≤ 6.5).
  • Collected clinic-based measures, patient-reported outcomes (including fall surveys and MS Walking Scale-12), and daily step counts via accelerometers over 12 months.

Main Results:

  • 53.2% of participants reported at least one fall, with only 56% documented in medical records.
  • Fallers exhibited greater disability (EDSS), were more likely to have progressive MS, and took fewer daily steps compared to non-fallers.
  • The MS Walking Scale-12 emerged as a significant predictor of future falls.

Conclusions:

  • Falling is common, under-reported, and under-diagnosed in MS patients.
  • Multimodal fall screening, both in-clinic and remotely, is recommended to identify high-risk individuals.
  • Timely intervention and referral to specialized physical rehabilitation can improve patient care.