Without any doubt, research in biomedical engineering and anesthesiology achieved diverse ground-breaking successes for the sake of patient safety and for optimization of medical treatment in the last decades. Particularly anesthesia has become increasingly comfortable and safer due to new monitoring devices and further techniques. However, assessment of pain still relies on self-reporting of the patient using a Numeric Rating Scale ranging from 0 to 10. Obviously, this method suffers from severe restraints when unconscious, anesthetized or uncooperative subjects or children are involved as patients. Furthermore, no continuous monitoring is available so that features like alerting telemetry are lacking. Several scientific groups and companies searched intensively for procedures to measure pain objectively. Skin conductance, heart rate variability and peripheral perfusion, among others, were used to develop new algorithms and devices. Up to date, none of these devices succeeded to enter in clinical routine. In this project, we used infrared thermography (IRT) to analyze facial expressions and further thermal-associated phenomena that are visible in recorded IRT sequences such as lacrimation and perspiration. By means of clinical observations, a number of IRT features were predefined that were expected to correlate with pain. The combination of those features led to the so-called "Thermal-Associated Pain Intensity" (TAPI) after normalization and transformation. The TAPI correlates significantly with the NRS and achieves a sensitivity of above 0.75 to detect pain.