Determining electrically evoked compound action potential thresholds: A comparison of computer versus human analysis methods

E. Katelyn Glassman, Michelle L. Hughes

    Research output: Contribution to journalArticlepeer-review

    7 Scopus citations


    Objectives: Current cochlear implants (CIs) have telemetry capabilities for measuring the electrically evoked compound action potential (ECAP). Neural Response TelemetryTM (Cochlear) and Neural Response Imaging (Advanced Bionics [AB]) can measure ECAP responses across a range of stimulus levels to obtain an amplitude growth function. Software-specific algorithms automatically mark the leading negative peak, N1, and the following positive peak/plateau, P2, and apply linear regression to estimate ECAP threshold. Alternatively, clinicians may apply expert judgments to modify the peak markers placed by the software algorithms, or use visual detection to identify the lowest level yielding a measurable ECAP response. The goals of this study were to: (1) assess the variability between human and computer decisions for (a) marking N1 and P2 and (b) determining linear-regression threshold (LRT) and visual-detection threshold (VDT); and (2) compare LRT and VDT methods within and across human- and computer-decision methods. Design: ECAP amplitude-growth functions were measured for three electrodes in each of 20 ears (10 Cochlear Nucleus® 24RE/CI512, and 10 AB CII/90K). LRT, defined as the current level yielding an ECAP with zero amplitude, was calculated for both computer- (C-LRT) and human-picked peaks (H-LRT). VDT, defined as the lowest level resulting in a measurable ECAP response, was also calculated for both computer- (C-VDT) and human-picked peaks (H-VDT). Because Neural Response Imaging assigns peak markers to all waveforms but does not include waveforms with amplitudes less than 20 μV in its regression calculation, C-VDT for AB subjects was defined as the lowest current level yielding an amplitude of 20 μV or more. Results: Overall, there were significant correlations between human and computer decisions for peak-marker placement, LRT, and VDT for both manufacturers (r = 0.78-1.00, p < 0.001). For Cochlear devices, LRT and VDT correlated equally well for both computer- and human-picked peaks (r = 0.98-0.99, p < 0.001), which likely reflects the well-defined Neural Response Telemetry algorithm and the lower noise floor in the 24RE and CI512 devices. For AB devices, correlations between LRT and VDT for both peak-picker methods were weaker than for Cochlear devices (r = 0.69-0.85, p < 0.001), which likely reflect the higher noise floor of the system. Disagreement between computer and human decisions regarding the presence of an ECAP response occurred for 5 % of traces for Cochlear devices and 2.1 % of traces for AB devices. Conclusions: Results indicate that human and computer peak-picking methods can be used with similar accuracy for both Cochlear and AB devices. Either C-VDT or C-LRT can be used with equal confidence for Cochlear 24RE and CI512 recipients because both methods are strongly correlated with human decisions. However, for AB devices, greater variability exists between different threshold-determination methods. This finding should be considered in the context of using ECAP measures to assist with programming CIs.

    Original languageEnglish (US)
    Pages (from-to)96-109
    Number of pages14
    JournalEar and hearing
    Issue number1
    StatePublished - 2013

    ASJC Scopus subject areas

    • Otorhinolaryngology
    • Speech and Hearing


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