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Design and Analysis for Fall Detection System Simplification
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Discriminating Between Fallers and Non-Fallers Using Kinematic Data from the Heel2Toe™ Wearable Sensor.

Nancy E Mayo1,2,3, Ahmed Abou-Sharkh3, Helen Dawes3,4

  • 1Department of Medicine, McGill University, Montreal, QC H3A 0G4, Canada.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

Ankle angular velocity (AV) during walking can predict fall risk. This study found specific AV metrics at heel strike effectively differentiate individuals who have fallen from those who have not.

Keywords:
digitalfallsgaitkinematicssensorwearable

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Area of Science:

  • Biomechanics
  • Gerontology
  • Wearable Technology

Background:

  • Falls are a major health concern, often occurring during walking.
  • Gait quality, particularly kinematic parameters, is a key factor in fall risk.
  • Ankle kinematics are closely linked to common fall-related incidents like trips and slips.

Purpose of the Study:

  • To determine the association between ankle angular velocity (AV) during walking and fall history.
  • To develop a predictive model for fall risk based on ankle AV metrics.

Main Methods:

  • A comparative study analyzing ankle AV metrics in individuals with and without a history of falls.
  • Utilized data from the Heel2Toe™ sensor across various settings.
  • Employed logistic regression with natural cubic splines to identify discriminating AV parameters.

Main Results:

  • Ankle angular velocity at heel strike was identified as a significant discriminator between fallers and non-fallers.
  • A novel algorithm was developed using logistic regression parameters to estimate fall risk.
  • The algorithm produced fall risk probabilities ranging from 0.0480 to 0.7245, influenced by participant age.

Conclusions:

  • Measures of ankle angular velocity during walking show significant potential for fall risk assessment.
  • The developed algorithm offers a promising tool for estimating fall risk, warranting further validation.
  • Ankle kinematics represent a valuable therapeutic and diagnostic target for fall prevention strategies.