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.