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Quantifying directional variability during sit-to-stand for post-stroke fall risk stratification: a pilot study.
Hyun Haeng Lee1, Doyoung Yuk1, Jongmin Lee1
1Department of Rehabilitation Medicine, Konkuk University Medical Center and Konkuk University School of Medicine, Seoul, Korea.
Topics in Stroke Rehabilitation
|March 30, 2026
Summary
Quantifying sit-to-stand (STS) directional variability with pressure sensors improves fall risk prediction in stroke survivors beyond the Berg Balance Scale (BBS). This method offers more precise fall prediction for better rehabilitation strategies.
Area of Science:
- Neurology
- Rehabilitation Medicine
- Biomechanics
Background:
- The Berg Balance Scale (BBS) has limitations in predicting falls due to its ordinal scoring and granularity issues.
- Sensor-based sit-to-stand (STS) assessments offer continuous data, overcoming ordinal scale limitations.
- STS directional variability may indicate impaired motor control and increased fall risk in stroke survivors.
Purpose of the Study:
- To assess if quantifying STS directional variability with pressure sensors adds predictive value for post-stroke falls compared to the BBS alone.
Main Methods:
- A prospective observational cohort study included stroke patients and healthy controls.
- Berg Balance Scale (BBS) and STS directional variability using a pressure sensor mat were assessed.
- Falls were tracked for 3 months post-discharge.
Main Results:
- Stroke patients with higher STS directional variability experienced more falls.
- Adding STS Direction Range to a model with Age and BBS improved fall prediction accuracy (AUC from 0.574 to 0.768).
Conclusions:
- Quantifying STS directional variability enhances fall risk stratification in stroke survivors beyond the BBS.
- This sensor-based approach provides valuable insights for stroke rehabilitation and fall prevention.
