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

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.