Using lightweight electroencephalography (EEG) to exploit the fringe P3 response

长期以来，警方素描艺术家一直被用来建立嫌疑人的侧写。他们利用证人证词和受害者报告，但是，这种确定嫌疑人的方法可能不可靠，因为证人可能隐瞒信息或在陈述中不诚实。近年来，随着电子面部识别技术（E-FIT）的广泛使用，以及最近引入人工智能来帮助创建这些E-FIT配置文件，已经取得了长足的进步。这些方法仍然受到证人偏见和反措施技术的影响，因为它们需要证人的证词来建立。有时，这些E-FIT因其滑稽的外观而受到新闻和社交媒体的关注，这可能会对调查产生不利影响[6-8]。尽管如此，E-FIT被全球30多个国家使用，成功率在40-55%之间，这就提出了如何使这些图像防篡改以实现更高的准确性和更快速的图像生成的问题[5]。VisionMetric Ltd目前对提高E-FIT精度的研究使用快速串行视觉呈现（RSVP）来测量大脑对与嫌疑人相似的图像的反应。RSVP和其他基于脑电图（EEG）的隐藏信息测试，与Fringe-P3方法相结合，已被证明是一种有前途的法医应用方法。例如，Frings-P3方法已被用于在地址流中正确检测受试者的电子邮件地址，从而将个人的在线身份与自己联系起来[1]。它通过在屏幕上向受试者显示一系列图像或类似刺激来实现这一点，这些图像或刺激的速度足够快，以至于受试者没有足够的时间有意识地思考他们所显示的信息，但大脑确实识别熟悉性。研究人员能够检测到P3反应时，主题显示了一个熟悉的项目，以这种方式，你可以绕过对策技术，一个主题可能会尝试和部署。在2014年，研究人员能够使用这种RSVP方法来证明您可以成功绕过对策技术[3]。在这个例子中，研究人员在屏幕上显示了受试者的名字，一些受试者被告知在显示熟悉的样本时尝试抑制反应的技术，一些受试者被告知尝试提高对控制刺激的反应。这项研究表明，通过使用这种方法，您可以绕过用于欺骗测谎仪等系统的对策技术，这是执法机构几十年来的一个问题。虽然这些方法显示出希望，但主要缺点是需要EEG设备来进行测试。在研究环境中，传统的设备是合适的，但是存在长的准备时间，需要基于每个受试者进行训练，并且设备对于佩戴者来说是笨重的和不舒服的，通常需要将许多电极放置在受试者的头皮上，因此在现实世界的场景中不容易部署。为了解决这个问题，研究人员开发了一种名为SKINTRONICS的新EEG。该设备是无线的，重量轻，电磁干扰少得多，已被证明具有与传统台式EEG系统相同（如果不是更好）的准确性[4]。虽然该系统已被证明是有效的，但它从未被应用于检测P3波。如果我们能开发出一种方法来精确地将这些方法联合收割机结合起来，并证明你可以根据大脑的P3反应生成越来越精确的图像，这将是一项有价值的研究，并将有助于地球仪各地的执法机构。

For a long time, police sketch artists have been used to build a profile of a suspect. They have utilized witness statements and victim reports, however, this method for identifying suspects can be unreliable since the witnesses can hold information back or not be truthful in their statements. Strides have been made in recent years with the more widespread use of the electronic facial identification technique (E-FIT) and even more recently the introduction of artificial intelligence to aid the creation of these E-FIT profiles. These methods still suffer from witness bias and countermeasure techniques since they require a testimony from the witness to create. Sometimes these E-FITs get attention from the news and social media for their comical appearance which can adversely affect the investigation [6-8]. Despite this, E-FITs are used by over 30 countries around the world and have success rates between 40-55% which raises the question of how these images can be made tamper-proof to enable better accuracy and more rapid image generation [5].Current research into improving the precision of the E-FITs by VisionMetric Ltd uses rapid serial visual presentation (RSVP) to measure the brains responses to images that bear resemblance to the suspect. RSVP and other electroencephalography (EEG) based concealed information tests, in combination with the Fringe-P3 method, have proven to be a promising method for forensic applications. For example, the Frings-P3 method has been used to detect subject's email addresses correctly in a stream of addresses thus linking an individual's online identity to themselves [1]. It does this by showing the subject a series of images or similar stimuli on a screen fast enough that the subject does not get enough time to consciously think about the information they have been shown, but the brain does recognise familiarity. Researchers were able to detect a P3 response when the subject was shown a familiar item, in this way you can bypass countermeasure techniques that a subject may try and deploy. In 2014, researchers were able to use this RSVP method to show that you can successfully bypass countermeasure techniques [3]. In this example, the researchers showed the subjects names on the screen and some of the subjects were told techniques to try and dampen the response when a familiar sample was shown, and some subjects were told to try and elevate the response measured to the control stimulus. This research demonstrates that by using this method you are able to bypass countermeasure techniques employed to trick systems like lie detectors which has been a problem for law enforcement agencies for decades.Although these methods show promise, the major drawback is the EEG equipment needed in order to carry out the tests. In a research environment, the traditional equipment is suitable however there is a long preparation time, requires training on a per subject basis and the equipment is bulky and uncomfortable for the wearer, often requiring many electrodes to be placed on the scalp of the subject, therefore not easily deployable in a real-world scenario. To address this issue, researchers have developed a new EEG called SKINTRONICS. This device, which is wireless, lightweight and suffers from a lot less electromagnetic interference has been shown to have the same if not better accuracy than traditional benchtop EEG systems [4]. Although the system has proven to work, it has never been applied to detecting P3 waves. If we could develop a method to accurately combine these methods and prove you can generate increasingly more accurate images based on the brains P3 response it would be an valuable piece of research and would aid law enforcement agencys around the globe.