An Audibility Model of the Bone Conduction Device during Headband Trial in Single-sided Deaf Subjects.

Code of the study 
Available in GitHub 

Related Data 
zenodo.7295445 

Abstract
Objective
Modelling the head-shadow-effect compensation and speech intelligibility outcomes, we studied the benefits of fitting a bone conduction device (BCD) during the headband trial in single-sided deafened (SSD) subjects.

Design
The participants’ BCD settings were retrospectively used for measurements on the skull simulator. The sensation levels of the Bone-Conduction and Air-Conduction sound paths were compared, modelling three spatial conditions with the speech in quiet. When the difference between sensation levels was equivalent or greater than zero, this was scored as full head-shadow-effect compensation. We calculated the phoneme score using the Speech Intelligibility Index for the three conditions in quiet and seven in noise.

Study sample
Data from eighty-five SSD adults fitted with a BCD during the headband trial.

Results
According to our model, most subjects did not achieve a full head-shadow-effect compensation with the signal at the BCD side and in front. The modelled speech intelligibility in the quiet condition did not improve with the transcutaneous BCD compared with the unaided condition. In noise, we found a slight improvement in some specific conditions and minimal worsening in others.

Conclusions
Based on an audibility model, this study challenges the fundamentals of a trial period with a transcutaneous BCD in SSD subjects.

About this release 
The code is provided in 2 different flavors: .ipynb and .html. If you want just to consult the code, it is best to use the html format. The html files provide also results, tables, and graphs. If you want to run the code, you have to use the ipynb files in the jupyter notebook (https://jupyter.org). Beside python and R, you will need different libraries. See the list "Code_packages_version". For this purpose, you may consider the installation of the anaconda platform (https://www.anaconda.com). To get the code working properly, you have to set the input and output file paths according to your operating system and map tree. The code is written for use with xslx files. If you like to use csv files, you have to adapt the code. 

Software & Libraries Version
The code works fine with the following versions: Python 3.8.12, Matplotlib 3.5.1, Numpy 1.20.3, Pandas 1.4.1, Pillow (PIL) 9.0.1, Scipy 1.7.3, Seeborn 0.11.2, R 3.6.3.