Wheelchair Operator Posture Classification Image Dataset

In the medical industry, recognizing the posture of wheelchair operators is key to enhancing patient autonomy. However, current technologies face challenges with diverse postures and complex environments, leading to insufficient accuracy in existing recognition systems. By constructing this dataset, we aim to improve the accuracy of posture classification to meet the needs of medical assistance and rehabilitation training. The dataset contains 5000 images collected using high-quality camera equipment under different lighting and angles to ensure data diversity and representativeness. We use multiple rounds of annotation and expert review to enhance data quality, ensuring consistency and accuracy in annotations. The data will be stored in JPG format, with each image accompanied by detailed annotation information organized by file structure.