A study of patient's pain assessment based on facial expression: issues and challenges

Abstract EN

Pain is considered as an emotional experience and a restless feeling associated with tissue damage.

When the interpretation begins in the brain, the sensation of pain occurs; a signal transmitted to the brain through the nerve fiber.

Pain helps the body to stop further damage to the tissues.

Since there are numerous ways to convey and feel pain, the perception of pain is special to all.

Technology that promotes pain assessment is an urgent need to reduce restless feelings and suffering.

This paper aims to demonstrate the issues and challenges facing the patient's pain assessment based on facial expression.

The design and implementation of an automatic pain recognition system and explain the various concepts relevant to it, such as the type of modalities, the procedure of collection and processing data sequentially to reach the classifier.

Then presenting clarification for various signals as input data (facial expressions, body movement, and vocalization).

This survey would positively help researchers to supplement their efforts towards the expansion of patients' pain assessment based on facial Pain is considered as an emotional experience and a restless feeling associated with tissue damage.

When the interpretation begins in the brain, the sensation of pain occurs; a signal transmitted to the brain through the nerve fiber.

Pain helps the body to stop further damage to the tissues.

Since there are numerous ways to convey and feel pain, the perception of pain is special to all.

Technology that promotes pain assessment is an urgent need to reduce restless feelings and suffering.

This paper aims to demonstrate the issues and challenges facing the patient's pain assessment based on facial expression.

The design and implementation of an automatic pain recognition system and explain the various concepts relevant to it, such as the type of modalities, the procedure of collection and processing data sequentially to reach the classifier.

Then presenting clarification for various signals as input data (facial expressions, body movement, and vocalization).

This survey would positively help researchers to supplement their efforts towards the expansion of patients' pain assessment based on facial expression.