Vision analysis in detecting abnormal breathing activity in application to diagnosis of obstructive sleep apnoea

<p>Recognizing abnormal breathing activity frombody movement is a challenging task in machine vision. In this paper, we present a non-intrusive automatic video monitoring technique for detecting abnormal breathing activities and assisting in diagnosis of obstructive sleep apnoea. The proposed technique utilizes infrared video information and avoids imposing geometric or positional constraints on the patient. The technique also deals with fully or partially obscured patients’ body. A continuously updated breathing activity template is builtfor distinguishing general body movement from breathingbehavior.</p>