Schott Julian, Gransier Robin, Moonen Marc, Wouters Jan
KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, 3001 Leuven, Belgium.
KU Leuven, Department of Neurosciences, ExpORL 3001 Leuven, Belgium.
J Neural Eng. 2025 Apr 11;22(2). doi: 10.1088/1741-2552/adc6be.
. Electrically evoked auditory steady-state responses (EASSRs) are potential neural responses for objectively determining stimulation parameters of cochlear implants (CIs). Unfortunately, they are difficult to detect in electroencephalography (EEG) recordings due to the electrical stimulation artifacts of the CI. This study investigates a novel stimulation paradigm hypothesized to improve artifact removal efficacy via system identification (SI), and therefore to improve response detection and clinical applicability.. An amplitude-modulated (AM) CI stimulation pulse train with a step-wise increase in modulation frequency is created (referred to as SWEEP stimulation). Another stimulation is created by randomly shuffling modulation frequencies of the SWEEP stimulation (referred to as Shuffled-SWEEP stimulation). AM pulse trains with fixed modulation frequency (referred to as conventional AM stimulation), which elicit EASSRs, are also created for comparison. EEG data is collected from four CI users. A supra-threshold stimulation condition is used to investigate whether the SWEEP and Shuffled-SWEEP stimulation can elicit envelope-following responses (EFRs). A sub-threshold stimulation condition allows the collection of artifact-only EEG data, which is used to compare the SI accuracy on recordings from the SWEEP and the conventional AM stimulation.. In all CI users, neural responses, following the SWEEP, Shuffled-SWEEP, and conventional AM stimulation are detected after artifact removal with SI. The validation with artifact-only EEG data shows higher1 scores when comparing recordings with SWEEP stimulation (1 = 0.9) to recordings with conventional AM stimulation (1 = 0.82).. Being able to accurately identify the response within one EEG recording enables the development of effective, online, objective fitting protocols. The increased neural response detection sensitivity with SWEEP stimulation reduces clinical recording time on average by a factor of 2.07. Detecting EFRs following complex stimulation paradigms offers a potential advancement in the systematic assessment of the temporal envelope processing in CI users.
电诱发听觉稳态反应（EASSRs）是用于客观确定人工耳蜗（CIs）刺激参数的潜在神经反应。不幸的是，由于人工耳蜗的电刺激伪迹，它们在脑电图（EEG）记录中很难被检测到。本研究调查了一种新型刺激范式，该范式假设通过系统识别（SI）提高伪迹去除效果，从而提高反应检测和临床适用性。创建了一种调制频率逐步增加的调幅（AM）人工耳蜗刺激脉冲序列（称为SWEEP刺激）。通过随机打乱SWEEP刺激的调制频率创建另一种刺激（称为随机SWEEP刺激）。还创建了具有固定调制频率的AM脉冲序列（称为传统AM刺激）以引出EASSRs进行比较。从四名人工耳蜗使用者收集脑电图数据。使用阈上刺激条件来研究SWEEP和随机SWEEP刺激是否能引出包络跟随反应（EFRs）。阈下刺激条件允许收集仅包含伪迹的脑电图数据，用于比较SWEEP和传统AM刺激记录上的系统识别准确性。在所有人工耳蜗使用者中，使用系统识别去除伪迹后，检测到了跟随SWEEP、随机SWEEP和传统AM刺激的神经反应。仅包含伪迹的脑电图数据验证表明，与传统AM刺激记录（SI = 0.82）相比，SWEEP刺激记录的SI分数更高（SI = 0.9）。能够在一次脑电图记录中准确识别反应有助于开发有效的在线客观拟合方案。SWEEP刺激提高的神经反应检测灵敏度平均将临床记录时间缩短了2.07倍。检测复杂刺激范式后的EFRs为人工耳蜗使用者颞包络处理的系统评估提供了潜在进展。
