Czaplik M, Hochhausen N, Dohmeier H, Pereira C Barbosa, Rossaint R
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:3831-3834. doi: 10.1109/EMBC.2017.8037692.
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.
毫无疑问，在过去几十年里，生物医学工程和麻醉学领域的研究为了患者安全和优化医疗治疗取得了各种开创性的成功。特别是由于新的监测设备和进一步的技术，麻醉变得越来越舒适和安全。然而，疼痛评估仍然依赖于患者使用从0到10的数字评分量表进行自我报告。显然，当涉及无意识、麻醉或不合作的受试者或儿童患者时，这种方法存在严重局限性。此外，没有连续监测，因此缺乏诸如警报遥测等功能。几个科学团体和公司深入研究了客观测量疼痛的程序。皮肤电导、心率变异性和外周灌注等被用于开发新的算法和设备。到目前为止，这些设备都没有成功进入临床常规应用。在这个项目中，我们使用红外热成像（IRT）来分析面部表情以及在记录的IRT序列中可见的其他与热相关的现象，如流泪和出汗。通过临床观察，预先定义了一些预期与疼痛相关的IRT特征。这些特征的组合在归一化和转换后产生了所谓的“热相关疼痛强度”（TAPI）。TAPI与数字评分量表（NRS）显著相关，检测疼痛的灵敏度超过0.75。
