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Updated: Sep 20, 2025

Motor Dual-Tasks for Gait Analysis and Evaluation in Post-Stroke Patients
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Establishing Accelerometer Cut-Points to Classify Walking Speed in People Post Stroke.

David Moulaee Conradsson1,2, Lucian John-Ross Bezuidenhout1,3

  • 1Division of Physiotherapy, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 83 Stockholm, Sweden.

Sensors (Basel, Switzerland)
|June 10, 2022
PubMed
Summary

New cut-points for accelerometers help differentiate walking from non-ambulation in stroke survivors. This research provides accurate classification for various walking speeds using waist- and ankle-worn devices.

Keywords:
ActiGraphROC analysisaccelerometersgait speedobjective measurementstrokewearable sensors

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Area of Science:

  • Rehabilitation Medicine
  • Biomedical Engineering
  • Kinesiology

Background:

  • Accelerometer data interpretation for gait analysis typically relies on studies with healthy individuals.
  • Validating accelerometer cut-points for post-stroke populations is crucial for accurate mobility assessment.

Purpose of the Study:

  • To develop and validate accelerometer cut-points for distinguishing non-ambulation from different walking speeds in individuals post-stroke.
  • To optimize sensor placement (waist vs. ankle) and data processing for accurate gait monitoring.

Main Methods:

  • Forty-two post-stroke participants wore waist and ankle accelerometers (ActiGraph GT3x+).
  • Activities included non-ambulation tasks and walking at self-selected and brisk speeds.
  • Receiver operating characteristic (ROC) curve analysis determined cut-points for various walking speeds and non-ambulation.

Main Results:

  • Optimal data processing involved vector magnitude at 15-second epochs for both waist and ankle placements.
  • Ankle-worn accelerometers demonstrated good-to-excellent accuracy across all speed categories.
  • Waist-worn accelerometers showed fair-to-excellent accuracy, with a slight decrease between 0.81–1.2 m/s.

Conclusions:

  • Validated cut-points enable accurate differentiation of walking behaviors in post-stroke individuals using accelerometers.
  • Ankle-worn accelerometers offer higher classification accuracy for gait speed assessment in this population.
  • These findings support the use of accelerometers in monitoring walking and its relationship to health outcomes post-stroke.