Human-Machine Interaction Design for a Self-service Forearm Thrombus Detection System Based on Jetson Nano

To alleviate the workload of medical personnel and enhance the convenience of rapid thrombus detection for patients, this study designs and implements a self-service thrombus detection system based on the Jetson Nano platform. The system utilizes near-infrared light and an industrial camera to detect blood vessels in human forearm during disease diagnosis. This paper focuses on the human-computer interaction design of this system, enabling users to autonomously operate the detection system through scripting, allowing for tasks such as patient information collection and medical image acquisition via a single button. The research findings demonstrate that the system is stable, reliable, and user-friendly, meeting the demand for patient-initiated detection.