Pain is a complex and subjective experience that poses significant challenges in both clinical and research settings. Accurate and objective pain assessment plays a crucial role in diagnosing and treating various medical conditions, as well as monitoring patient progress and response to interventions. Traditional pain assessment methods heavily rely on self-reporting or observations made by individuals, which can be influenced by various factors such as cultural differences, cognitive impairments, or personal biases. This subjectivity and potential inaccuracies in traditional pain scores highlight the need for accurate and objective approaches to pain assessment. In recent years, the advent of sensor technologies, such as wearable devices, biosensors, or imaging technologies, and advancements in artificial intelligence (AI) have opened new possibilities for objective pain detection and quantification. Combining sensor capabilities and AI analysis unveils new possibilities for advancing pain assessment and management.

The goal of this Research Topic is to showcase the latest advancements and research in the integration of sensor technologies and AI for objective pain detection and quantification. By bringing together innovative approaches and methodologies, this Research Topic aims to unveil new possibilities and insights how the combination of sensors and AI can improve pain assessment, offering accurate, reliable, and real-time methods for detecting and quantifying pain. We aim to stimulate interdisciplinary discussions, foster collaboration, and inspire further research in the exciting intersection of sensors and AI for objective pain assessment.

We welcome the submission of manuscripts including, but not limited to, the following topics:
1. Novel sensor technologies for pain assessment
2. Machine learning algorithms for pain detection and classification
3. Deep learning approaches for pain quantification
4. Real-time monitoring systems for objective pain assessment
5. Wearable devices and biosensors in pain measurement
6. Imaging technologies for objective pain detection
7. Data fusion techniques for integrating multiple sensor modalities in pain assessment
8. Ethical considerations and privacy issues in sensor-based pain assessment
9. Clinical applications of sensor-based pain detection and quantification
10. User experience and acceptance of sensor-based pain assessment technologies
11. Long-term monitoring and tracking of pain using sensor technologies
12. Integration of sensor data with electronic health records for comprehensive pain management.

We encourage the exploration of different sensing modalities, such as neural (electroencephalogram, functional near-infrared spectroscopy), physiological (electrodermal activity, photoplethysmogram, electrocardiogram, electromyogram, etc.), behavioral (facial expressions, voice, movement, etc.), and their combinations.

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Frontiers in Pain Research

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