AutoNRT™: An automated system that measures ECAP thresholds with the Nucleus ® Freedom™ cochlear implant via machine intelligence

• Published in: Artificial intelligence in medicine Vol. 40; no. 1; pp. 15 - 28
• Main Authors: Botros, Andrew, van Dijk, Bas, Killian, Matthijs
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2007
• Subjects: Automated systems; Cochlear implants; Decision trees; Electrically evoked compound action potential; Internal Medicine; Machine learning; Neural response telemetry; Other; Pattern recognition; Threshold estimation; Cochlear implants; Electrically evoked compound action potential; Machine learning; Pattern recognition; Decision trees; Automated systems; Neural response telemetry; Threshold estimation
• ISSN: 0933-3657; 1873-2860
• DOI: 10.1016/j.artmed.2006.06.003

AutoNRT™ is an automated system that measures electrically evoked compound action potential (ECAP) thresholds from the auditory nerve with the Nucleus ® Freedom™ 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. 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 lower 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. 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. AutoNRT has demonstrated a high success rate and a level of performance that is comparable with human experts. It has been used in many clinics worldwide throughout the clinical trial and commercial launch of Nucleus Custom Sound™ Suite, significantly streamlining the clinical procedures associated with cochlear implant use.