Automatically Detecting Pain Using Facial Actions.
Automatically Detecting Pain Using Facial Actions.
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使用面部动作自动检测疼痛。
DOI：
10.1109/acii.2009.5349321
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Prkachin,KennethM
中科院分区：
文献类型：
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作者：
Lucey,Patrick;Cohn,Jeffrey;Lucey,Simon;Matthews,Iain;Sridharan,Sridha;Prkachin,KennethM
疼痛通常通过患者自我报告来测量，通常通过口头交流。但是，如果患者是儿童或沟通能力有限（即，静音、精神受损或辅助呼吸的患者），自我报告可能不是可行的测量方法。此外，这些自我报告测量仅涉及序列期间经历的最大疼痛水平，因此目前无法获得逐帧测量。使用患者的图像数据与肩袖损伤，在本文中，我们描述了一个AAM为基础的自动系统，可以检测疼痛的一帧一帧的水平。我们有两种方法：直接（直接从面部特征）和间接（通过单个Au探测器的融合）。从我们的结果，我们表明，后者的方法达到了最佳的结果，因为大多数判别功能，从每个Au检测器（即形状或外观）使用。
Pain is generally measured by patient self-report, normally via verbal communication. However, if the patient is a child or has limited ability to communicate (i.e. the mute, mentally impaired, or patients having assisted breathing) self-report may not be a viable measurement. In addition, these self-report measures only relate to the maximum pain level experienced during a sequence so a frame-by-frame measure is currently not obtainable. Using image data from patients with rotator-cuff injuries, in this paper we describe an AAM-based automatic system which can detect pain on a frame-by-frame level. We do this two ways: directly (straight from the facial features); and indirectly (through the fusion of individual AU detectors). From our results, we show that the latter method achieves the optimal results as most discriminant features from each AU detector (i.e. shape or appearance) are used.