Collaborative research projects in
Pain Intensity Detection
funded by the german research foundation (DFG)
The AI-based pain detection at NIT consists of two DFG funded research projects. These two projects focus on developing and testing AI-based methods to reliably detect pain in humans. Thus, the first project aims at using the knowlegde from our previous projects, which resulted in the creation of the pain databases BioVid and X-ITE, to develop a reliable, robust and effective pain detection system based on all available modalities. These modalities range from physiological bio-signals such as ECG, Skin activity, and muscle activiy to video based methods of the face or the body.
The second research project focuses then on transfering the developed solutions from the laboratory enviornments of BioVid and X-ITE to real world settings. For this purpose, the project aims to create a new dataset from real patient after abdominal surgery in the intermediate care unit of the university hospital Ulm. This dataset allows to verify and transfer the AI models to real world settings.
The projects are supported by the DFG with the grants Pain analysis Nr. AL 638/20-1 and AL 638/19-1 until 2027.
X-ITE PAIN Challenge 2025
May 15, 2025
Towards a reliable multimodal AI monitoring system for pain detection and quantification
February 25, 2025
Recording Start in Ulm
October 01, 2024
An Intelligent Approach for Continuous Pain Intensity Prediction
May 27, 2024
Automated Electrodermal Activity and Facial Expression Analysis for Continuous Pain Intensity Monitoring on the X-ITE Pain Database
August 29, 2023
Classification networks for continuous automatic pain intensity monitoring in video using facial expression on the X-ITE Pain Database
March 01, 2023
