Pain detection system in real time healthcare environment

Pain detection system in real time healthcare environment

Computer Science

The negative feeling of pain is often involuntarily expressed through facial expressions. Facial expression therefore is an important non-verbal cue to determine if a person is in pain. This property can be applied for diagnosis of pain especially among patients who are differently challenged and lack the ability of expressing their issue. In spite of the developments made so far, this field still lags behind in finding pain expressing faces in an uncontrolled environment through unprocessed real time images and videos. To bridge this gap, the study proposed a
hybrid or fusion model that could adequately detect a face expressing pain. The model was executed with inputs taken from pre-recorded or stored videos and live streamed videos. It involved the combination of Patch Based Model (PBM), Constrained Local Model (CLM), and Active Appearance Model (AAM) in concurrence with image algebra.

Dutta, Pranti - 1445003

CHRIST (Deemed to be University)

English

PhD