Towards Intelligent Pain Monitoring Systems: A Survey of Recent Technologies and Methods

Area of Science:

• Pain management and medical technology.
• Biomedical engineering and human-computer interaction.

Background:

• Pain assessment is challenging, especially for non-communicative individuals.
• Existing methods for pain monitoring have limitations.
• Technological advancements are needed for objective pain assessment.

Purpose of the Study:

• To provide a comprehensive overview of current technologies for automatic pain monitoring.
• To present a taxonomy of technologies used in automatic pain monitoring.
• To identify challenges and future research directions in the field.

Main Methods:

• Survey of existing literature on automatic pain monitoring technologies.
• Categorization of technologies based on Internet of Things (IoT), computer vision, and multimodal approaches.
• Analysis of various data modalities including physiological signals, facial expressions, vocalizations, and behavioral patterns.

Main Results:

• Overview of technologies utilizing IoT, computer vision, and multimodal techniques for pain detection.
• Discussion of the advantages and limitations of different data modalities for pain assessment.
• Identification of current research trends, including machine learning algorithms and wearable devices.

Conclusions:

• Automatic pain monitoring technology is advancing rapidly, offering new possibilities for patient care.
• Further research is needed to overcome challenges in developing accurate and reliable pain monitoring systems.
• A keyword map is provided to guide future research and identify emerging trends.