AutoNRT™:: An automated system that measures ECAP thresholds with the Nucleus® Freedom™ cochlear implant via machine intelligence
AutoNRT™:: An automated system that measures ECAP thresholds with the Nucleus® Freedom™ cochlear implant via machine intelligence
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DOI：
10.1016/j.artmed.2006.06.003
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发表时间：
2007-05-01
影响因子：
7.5
通讯作者：
Killian, Matthijs
中科院分区：
文献类型：
--
作者：
Botros, Andrew;van Dijk, Bas;Killian, Matthijs
目的：AutoNRT((TM)) 是一种自动化系统，可通过 Nucteus((R)) Freedom((TM)) 人工耳蜗测量听觉神经的电诱发复合动作电位 (ECAP) 阈值。沿着电极阵列的 ECAP 阈值对于客观地适合个人使用的人工耳蜗系统非常有用。本文首次详细描述了 AutoNRT 算法及其专家系统，并报告了迄今为止 AutoNRT 的临床成功。方法：AutoNRT 使用两个自动识别 ECAP 的决策树专家系统，通过视觉检测确定阈值。专家系统由 5393 个神经反应测量数据集指导。该算法接近塔刺激水平的阈值，确保术后测量期间接受者的安全。术中测量使用相同的算法，但通过从更接近阈值的刺激水平开始进行得更快。在搜索 ECAP 时，AutoNRT 使用高度特异性的专家系统（训练期间特异性为 99%，测试期间特异性为 96%；训练期间敏感性为 91%，测试期间敏感性为 89%）。一旦建立 ECAP，AutoNRT 就会使用公正的专家系统来确定准确的阈值。在算法的整个执行过程中，记录参数（例如植入放大器增益）会在需要时自动优化。结果：在一项包括 29 名术中受试者和 29 名术后受试者（总共 418 个电极）的研究中，AutoNRT 在 93% 的病例中确定了阈值，其中人类专家也确定了阈值。与多个人类观察者在 77 个随机选择的电极上的中值阈值进行比较时，AutoNRT 的表现与“平均”临床医生一样准确。
Objective: AutoNRT((TM)) is an automated system that measures electrically evoked compound action potential (ECAP) thresholds from the auditory nerve with the Nucteus((R)) Freedom((TM)) cochlear implant. ECAP thresholds along the electrode array are useful in objectively fitting cochlear implant systems for individual use. This paper provides the first detailed description of the AutoNRT algorithm and its expert systems, and reports the clinical success of AutoNRT to date.Methods: AutoNRT determines thresholds by visual detection, using two decision tree expert systems that automatically recognise ECAPs. The expert systems are guided by a dataset of 5393 neural response measurements. The algorithm approaches threshold from tower stimulus levels, ensuring recipient safety during postoperative measurements. Intraoperative measurements use the same algorithm but proceed faster by beginning at stimulus levels much closer to threshold. When searching for ECAPs, AutoNRT uses a highly specific expert system (specificity of 99% during training, 96% during testing; sensitivity of 91% during training, 89% during testing). Once ECAPs are established, AutoNRT uses an unbiased expert system to determine an accurate threshold. Throughout the execution of the algorithm, recording parameters (such as implant amplifier gain) are automatically optimised when needed.Results: In a study that included 29 intraoperative and 29 postoperative subjects (a total of 418 electrodes), AutoNRT determined a threshold in 93% of cases where a human expert also determined a threshold. When compared to the median threshold of multiple human observers on 77 randomly selected electrodes, AutoNRT performed as accurately as the 'average' clinician.