Drakopoulos, F., Vasilkov, V., Osses Vecchi, A., Wartenberg, T. & Verhulst, S. Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies. Hearing Research, 108569 (2022). https://doi.org/10.1016/j.heares.2022.108569
This repository contains the presented hearing-loss compensation strategies for cochlear synaptopathy (CS), as well as the evaluation results of our participants and the scripts that were used to record and analyse EEGs. The supporting paper can be found here and a pre-print version is available under the doc folder (https://www.biorxiv.org/content/10.1101/2022.01.10.475652v2). The hearing-enhancement algorithms were designed to compensate for the degraded AN responses of CS-affected auditory peripheries, based on simulated outcomes of a biophysically inspired auditory model (Verhulst et al. 2018, v1.2).
The algorithms folder includes the implementations of the hearing-enhancement algorithms in MATLAB. Three processing functions are included (g_70dB.m, gm_70dB.m, and gmref_70dB.m), which correspond to the implementations of the original processing strategy (Eq. 2), the modified processing strategy (Eq. 9), and the clean-envelope (reference) modified strategy, respectively, as presented in the paper. Each strategy can be applied to an input signal to improve temporal-envelope processing for 3 CS profiles: 13,0,0 (loss of LSR and MSR ANFs), 10,0,0 (loss of LSR and MSR ANFs, 23% loss of HSR ANFs) and 7,0,0 (loss of LSR and MSR ANFs, 46% loss of HSR ANFs).
The developed algorithms were evaluated in normal-hearing (NH) subjects of two age groups: Young NH (yNH) and older NH (oNH) subjects, without and with suspected age-related CS, respectively. The data folder contains the evaluation results of our participants, which include measured audiometric thresholds, envelope-following responses (EFRs), amplitude-modulation (AM) detection thresholds, and speech intelligibility in terms of speech-recognition thresholds (SRTs) and word-recognition scores (WRSs).
The EEG_recording folder contains all the necessary files to record EFRs on our BioSemi EEG setup. The run_experiment.m script is used to record EEG responses to a specific stimulus, implemented in MATLAB using Playrec. The two stimuli that were used for our experimental evaluation (SAM tone and HP-filtered speech) are provided under the stimuli folder. In the run_experiment.m script, the playback parameters (pars) need to be defined depending on the stimulus, given as an argument or adapted inside the script by uncommenting the relative sections. To generate a processed stimulus using one of the 3 CS-compensating algorithms, the corresponding number of the desired CS profile (1300, 1000 or 700) can be given as the third argument.
Additionally, the EFR_analysis folder contains the analyse_bdf.m script (along with all the supplementary functions) that was used to extract and analyse the EFRs from the recorded bdf files of the Biosemi setup.
If you use this code, please cite the corresponding paper:
Drakopoulos, F., Vasilkov, V., Osses Vecchi, A., Wartenberg, T. & Verhulst, S. Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies. Hearing Research, 108569 (2022). https://doi.org/10.1016/j.heares.2022.108569
This repository can also be cited separately:
Drakopoulos, F., Vasilkov, V., Osses Vecchi, A., Wartenberg, T. & Verhulst, S. fotisdr/CS_compensation: Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies (v1.0). Zenodo. (2022). https://github.com/fotisdr/CS_compensation.
For questions, please reach out to one of the corresponding authors:
- Fotios Drakopoulos: fotios.drakopoulos@ugent.be
- Sarah Verhulst: s.verhulst@ugent.be
This work was funded with support from the EU Horizon 2020 programme under grant agreement No 678120 (RobSpear).