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Related Experiment Video

Updated: Apr 30, 2026

Quantitative Static and Dynamic Assessment of Balance Control in Stroke Patients
09:17

Quantitative Static and Dynamic Assessment of Balance Control in Stroke Patients

Published on: May 17, 2020

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Balance ability test dataset for stroke patients based on flexible array pressure sensors.

Shun Wang1, Jian Guo2, Yue Zhang3

  • 1University of Science and Technology of China, Anhui, China.

Data in Brief
|April 29, 2026
PubMed
Summary

This study introduces a new dataset for balance assessment using flexible array pressure sensors. The data aims to improve the detection and analysis of balance impairments in stroke patients.

Keywords:
Array pressure acquisition systemBalance ability evaluationBiomedical signal processingGait behaviour recognitionHome-based rapid screening

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Science
  • Data Science

Background:

  • Flexible array pressure sensors offer high sensitivity and multi-point measurement for balance assessment.
  • Existing datasets for balance assessment in stroke patients are scarce, limiting research and technological advancement.

Purpose of the Study:

  • To introduce a publicly available dataset for balance assessment in stroke patients.
  • To facilitate the detection and analysis of balance impairments using flexible array pressure sensor data.
  • To address the need for large-scale, high-quality data in stroke rehabilitation research.

Main Methods:

  • Data collected from 53 volunteers (36 healthy, 17 stroke patients) at Jiangbin Hospital.
  • Utilized an array pressure acquisition system to record sensor data during five specific movements.
  • Included diverse participant demographics (age, height, weight) and balance tasks (sit-to-stand, stepping, static balance with/without eyes closed).

Main Results:

  • A comprehensive dataset comprising sensor data from various balance tasks and participant groups was successfully compiled.
  • The dataset captures detailed pressure distribution and temporal dynamics during specific movements.
  • The data provides a valuable resource for developing and validating balance assessment algorithms for stroke patients.

Conclusions:

  • The release of this dataset addresses a critical gap in resources for balance assessment research in stroke.
  • This resource is expected to accelerate the development of advanced technologies for detecting and analyzing balance impairments.
  • Promotes further research in quantitative balance assessment and personalized rehabilitation strategies for stroke survivors.