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tags:
  - status classification
  - image recognition
  - rehabilitation therapy
  - auxiliary equipment monitoring
  - elderly care
license: cc-by-nc-sa-4.0
task_categories:
  - image-classification
language:
  - en
pretty_name: Electric Wheelchair Status Classification Image Dataset
size_categories:
  - 1B<n<10B

Electric Wheelchair Status Classification Image Dataset

With the advent of an aging society, the use of electric wheelchairs is becoming increasingly common. However, in practical application, users face challenges in status monitoring and are unable to understand the wheelchair's usage status in real-time. Existing solutions often rely on manual inspections, which are inefficient and prone to errors. This dataset aims to automatically identify the status of electric wheelchairs through image classification technology, meeting the medical industry's demand for intelligent monitoring. The dataset contains 5000 status images of electric wheelchairs, collected using high-definition cameras in various environments to ensure coverage of multiple usage scenarios. Quality control measures including multiple rounds of annotation and expert review ensure the accuracy and consistency of data labeling. The data is stored in JPG format, organized by status classification for convenient subsequent training and application.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
wheelchair_condition string The current state of the wheelchair, such as moving, stopped, etc.
obstacle_presence boolean A boolean indicator of whether there are obstacles affecting wheelchair movement in the image.

Compliance Statement

Authorization Type CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization No PII, no real company names, simulated scenarios follow industry standards
Compliance System Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com