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Open Access Publications from the University of California

Minimally Intrusive Gaze Detection in Clinical Environments

Abstract

Motivated by the Electronic Health Record (EHR) system's demand of capturing patients' multimodal activities and the wide application of gaze detection, we develop a minimally intrusive gaze detection system with Microsoft Kinect sensor and test its performance in a simulated clinical environment. Traditional methods require either a close distance between the camera and the user or a fixed head pose which may severely interrupt the clinical workflow and the interaction between the physician and the patient. Compared with the traditional methods, our system allows a wider range of detection, while achieving an accuracy around 70%

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