Improving audio training for Cochlear Implant users

Abstract

A Cochlear Implant(CI) is an implant that replaces the functionality of the inner ear with an electronic prosthesis. The prosthesis stimulates the auditory nerves within the cochlea so that people with auditory disabilities regain hearing. While the medical process of inserting the implant is relatively straightforward, learning how to use the implant may be difficult. This thesis proposes a digital training platform that can aid with the learning process for CI users and lighten the transition into the audible realm. Providing efficient training tools available at home without assistance from third parties can increase independence for CI users, as it becomes easier to conduct audio training. The results from a questionnaire performed during the thesis with CI users as participants found that participants spent, on average, one hour traveling to and from training centers or audio therapists. Introducing home-based training tools tailored toward post-lingually deafened CI users can help free up patients' time and alleviate the learning process. Therefore, a digital training platform was developed, tailored towards the needs of post-lingually deafened CI users. CI users were involved via questionnaires and semi-structured interviews throughout the development process, and their feedback was gathered to inform the design and increase usability and effectiveness. The participants' feedback and the findings from a literature review based on related research crafted the requirements specification for the proposed digital training platform. Throughout the thesis, the main goal was to create something that could be deployed and maintained, accessible and reachable for those who may use it. Therefore, a cost analysis of different cloud computing services was carried out to find the cheapest deployment options to avoid adding a monetary barrier to entry. Linode Kubernetes Engine (LKE) was an affordable and efficient option. Along with LKE, the efficacy of deployment through single board computers was investigated. The data gathered through performance testing done during the thesis indicates that the current generation of the Raspberry Pi platform could be used to provide a cheap alternative to deployment if the number of expected users is relatively low. However, a side effect of using single-board computers is that it puts the responsibility to provide the availability and reliability requirements on the developer. As a result, you can not rely on the monetary incentives of a cloud provider. Since the availability and reliability requirements of the proposed digital training platform could not be ensured when utilizing single-board computers, the final deployment utilizes LKE and is accessible through: www.lyttetrening.no