OBJECTIVE: AutoNRT is the completely automatic electrically evoked compound action potential (ECAP) measuring algorithm in the recently released Nucleus Freedom cochlear implant system. AutoNRT allows clinicians to automatically record T-NRT profiles that in turn can be used as a guide for initial fitting. The algorithm consists of a pattern recognition part that judges if the traces contain an ECAP and an intelligent flow that optimizes the measurement parameters and finds the ECAP threshold (T-NRT). The objective of this study was to determine how accurate, reliable, and fast the automatic measurements are. DESIGN: Data on more than 400 electrodes were collected as part of the multicenter clinical trial of the Nucleus Freedom cochlear implant system. T-NRT values determined by the algorithm were compared with T-NRT determinations on the same data by different human observers. Also, the time the measurements took was analyzed. RESULTS: In 90% of the cases, the absolute difference between the AutoNRT and the human observer determined T-NRT was less than 9 CL; the median absolute difference was 3 CL. A second experiment, in which a group of human observers were asked to analyze NRT data, showed high variability in T-NRT; in some cases, two experienced clinicians disagreed by more than 30 current levels. Compared with the group, AutoNRT performed as well as the "average" clinician, with the advantage that the AutoNRT threshold determinations are objective. Analysis of the timing data showed an average intraoperative measurement time of less than 20 sec per electrode with a standard deviation of 5 sec, suggesting that the total array of 22 electrodes can be measured intraoperatively in about 7 minutes on average. CONCLUSIONS: AutoNRT provides comparable accuracy to an average clinician but with the added benefit of significant time savings over manual recordings. This makes it a valuable tool for clinical measurement of ECAP threshold in cochlear implant recipients.
OBJECTIVE: AutoNRT is the completely automatic electrically evoked compound action potential (ECAP) measuring algorithm in the recently released Nucleus Freedom cochlear implant system. AutoNRT allows clinicians to automatically record T-NRT profiles that in turn can be used as a guide for initial fitting. The algorithm consists of a pattern recognition part that judges if the traces contain an ECAP and an intelligent flow that optimizes the measurement parameters and finds the ECAP threshold (T-NRT). The objective of this study was to determine how accurate, reliable, and fast the automatic measurements are. DESIGN: Data on more than 400 electrodes were collected as part of the multicenter clinical trial of the Nucleus Freedom cochlear implant system. T-NRT values determined by the algorithm were compared with T-NRT determinations on the same data by different human observers. Also, the time the measurements took was analyzed. RESULTS: In 90% of the cases, the absolute difference between the AutoNRT and the human observer determined T-NRT was less than 9 CL; the median absolute difference was 3 CL. A second experiment, in which a group of human observers were asked to analyze NRT data, showed high variability in T-NRT; in some cases, two experienced clinicians disagreed by more than 30 current levels. Compared with the group, AutoNRT performed as well as the "average" clinician, with the advantage that the AutoNRT threshold determinations are objective. Analysis of the timing data showed an average intraoperative measurement time of less than 20 sec per electrode with a standard deviation of 5 sec, suggesting that the total array of 22 electrodes can be measured intraoperatively in about 7 minutes on average. CONCLUSIONS: AutoNRT provides comparable accuracy to an average clinician but with the added benefit of significant time savings over manual recordings. This makes it a valuable tool for clinical measurement of ECAP threshold in cochlear implant recipients.
Authors: Michelle L Hughes; Jenny L Goehring; Jacquelyn L Baudhuin; Gina R Diaz; Todd Sanford; Roger Harpster; Daniel L Valente Journal: J Speech Lang Hear Res Date: 2012-01-09 Impact factor: 2.297