Researchers interested in the exact stimulation presented by a cochlear implant (CI) require an experimental setup that can measure clinical CI processor output. This work describes such a setup and aims to provide all the information and code needed to recreate a similar one. Additionally, the setup allows precise adaptation of realistic personalized stimulation tables retrieved from ecological sound stimuli, to be used in experiments with a research interface.

Since the coding from acoustic signal to stimulation tables is highly complex in modern processors, it can be difficult for researchers to understand what signals are being presented to the CI recipient listening to complex stimuli such as speech. Computational models for relating sound input to processor output exist, such as BEPS+ by Advanced Bionics, and the Nucleus Matlab Toolbox (NMT) by Cochlear. However, these models can prove insufficient in several ways: (1) they are not updated as often as clinical processors, (2) apply simplifications to decrease computational time, (3) lack a brand-neutrality needed to compare between processing of different manufacturers, and (4) make it difficult to recreate inputs that incorporate the multiple directional microphones of modern processors. The experimental setup described here overcomes these difficulties by allowing a researcher to measure the output of a clinical CI processor with all its bells and whistles.

The setup is a chain of devices which starts and ends at a laptop running Python. Inside a sound treated room, a loudspeaker plays stimuli to the CI processor, which is set up in an ecological fashion by attaching it to the ear of a KEMAR dummy. An implant-in-a-box retrieves CI signals from the processor and, through a load board, transmits the voltage signals of each channel to two synchronized oscilloscopes.

An example experiment is used to illustrate the use of the system. Here, the voice pitch (F0) of recorded Dutch spoken syllables was adapted, and the availability of F0 pitch cues in the CI output was studied using the experimental setup.

The voltage output was processed to infer pulse timing and current information. From here, analyses were done to retrieve information related to pitch, such as spectral centroid, amplitude modulation, and salience. This output was compared to the outputs generated by BEPS+ and NMT.