To promote occupational health management and prevent Computer Vision Syndrome among teleworkers, this paper presents a method for measuring screen-based computer work duration using a web camera. The existing method determines working states solely based on whether the PC user appears in the image, and therefore cannot accurately classify situations in which the user is taking a break while remaining at their desk. The proposed method captures an image of the user every minute and applies YOLOv8n-pose to detect the human body and facial landmarks such as the eyes and nose. Based on the size of the detected bounding box of human body and the face orientation calculated from the coordinates of the nose and eyes, a classifier determines whether the user is working or a screen break. The total work duration is calculated by counting consecutive one-minute intervals identified as “working”. To evaluate the proposed method, experiments were conducted on 21 users with a total of 3,790 webcam images. Experimental results confirmed that the proposed method was capable of accurately identifying the state of participants taking a break while remaining at their desks, and achieved a measurement error within 5 min for 12 participants with stable working postures. On the other hand, accurate classification was difficult in cases where participants adopted working postures not represented in the training data, or where only the gaze direction differed between working and on-break states. Consequently, 3 participants exhibited measurement errors exceeding 60 min.