KELVASA2015 - Azimuthal localization in cochlear-implant listeners

Usage:

[results] = kelvasa2015(insig,fs,varargin);

Input parameters:

`insig`	Can be either [N x 2] two channel audio signal or results structure of preProcessed data
`fs`	sampling rate (Hz)
`varargin`	structure with all parameters required for model. If this is not included, default paramters are loaded.

Output parameters:

results

A structure containing the processed electrodograms, AN spike times, and model predicted azimuthal locations

Description:

KELVASA2015(insig,fs) implements the ACE signal processing strategy upon the two channel input signal to produce bilateral electrodograms. This is further processed through an electrode nerve interface to generate spike times of a population of AN neurons. A chosen localization model from Kelvasa and Dietz 2015 is then used to map the two channel (right and left) outputs to a predicted azimuthal position.

The output structure results has the following fields:

`'electrodogramCHAN1'`
	[NxM] matrix of CI electrode current output in mA(???) with N = number of CI electrodes and M = time
`'APvecCHAN1'`	[Nx2] matrix of [Nx1] indices of spiking AN fibers [Nx2] spike times in seconds
`'electrodogramCHAN2'`
	same but for second channel
`'APvecCHAN2'`	same but for second channel
`'SpkSumPerBin'`	[NxM] matrix of Right and Left Spike Rate differences in spikes per second with N = number of AN frequency bands and M = time bins
`'SpkDiffPerBin'`	same but for Right and Left spike rate differences
`'ANbinPredictions'`	[NxM] matrix of azimuthal angle bin predictions in degrees with N= number of AN frequency bands and M = time bins
`'weightedPredictions'`
	[1xM] matrix of bin weighted azimuthal angle bin predictions in degrees with M = time bins
`'mappingData'`	Structure containing data used to calibrate and implement the chosen localization model as detailed in kelvasa2015calibratemodels.m

The steps of the binaural model to calculate the result are the following :

1 Process two channel input signal through a CI strategy as detailed in (Hamacher, 2003) and (Fredelake and Hohmann, 2012) to produce bilateral electrodograms.

2 Process electrodogram through an electrode nerve interface and auditory nerve model as detailed in (Fredelake and Hohmann, 2012)

3 Compute bilateral spike rate differences over chosen AN frequency bands and time windows as detailed in (Kelvasa and Dietz, 2015)

4 Calibrate the chosen localization model with a chosen calibration signal. This step can take several hours so preprocessed calibration is loaded for "Speech Shaped Noise" at 55dB as detailed in (Kelvasa and Dietz, 2015)

5 Map the spike rate differences for each AN frequency band to a predicted azimuthal angle using the chosen localization model as detailed in (Kelvasa and Dietz, 2015)

WARNING: If Octave is used, the plots will differ from the original ones, because spectrogram is not available in Octave. Instead, sgram from LTFAT is used.

References:

S. Fredelake and V. Hohmann. Factors affecting predicted speech intelligibility with cochlear implants in an auditory model for electrical stimulation. Hearing Research, 287(1):76 -- 90, 2012. [ DOI | http ]

V. Hamacher. Signalverarbeitungsmodelle des elektrisch stimulierten Gehörs; 1. Aufl. PhD thesis, RWTH Aachen, Aachen, 2004. Zugl.: Aachen, Techn. Hochsch., Diss., 2003. [ http ]