JMIR Publications

ABSTRACT

Background:

Cochlear Implants (CIs) are implanted hearing devices. Instead of amplifying sounds like common hearing aids, this technology delivers preprocessed sound information directly to the hearing (auditory) nerves. After surgery and the first CI(s) activation, patients must practice interpreting the new auditory sensations, especially for language comprehension. This rehabilitation process is accompanied by hearing therapy through face-to-face training with a therapist, self-directed training, and/or computer-based auditory training.

Objective:

In general, self-directed computer-based auditory training tasks have already shown advantages. However, compliance of CI recipients is still a major factor, especially for self-directed training at home. Hence, our aim is to explore the combination of two techniques to enhance learner motivation in this context: adaptive learning (in the form of an intelligent tutoring system) and game-based learning (in the form of a serious game).

Methods:

Following the suggestions of the Evidence-Centered Design Framework, a domain analysis of hearing therapy took place, allowing us to partially describe the human hearing skill as a probabilistic competence model (Bayesian Network). We developed an algorithm that uses such a model to estimate the current competence level of a patient and create training recommendations. For training, our developed task system is based on seven language comprehension task types that act as a blueprint for generating tasks of diverse difficulty automatically. To achieve this, 1053 audio assets with meta-information labels were created. We embedded the adaptive task system into a graphic novel-like mobile serious game. German-speaking CI patients used the system during a feasibility study for four weeks.

Results:

The 23 adult participants (20f;3m) fulfilled 2259 tasks. A generalized additive model analysis of these tasks indicates that the system adapts to the actual competency levels of the CI recipients quicker in the beginning compared to the end. Compared to a uniform distribution of all task types, the recommended task types differed (X²= 86.713, df = 6, p-value < 2.2e-16), indicating that the system selected specific task types for each patient. This is underlined by the significantly found categories for the error ratios of the task types.

Conclusions:

This contribution demonstrates the feasibility of combining an intelligent tutoring system with a serious game in CI rehabilitation therapies. The findings presented here hopefully lead to further advances in CI care and aural rehabilitation in general. Clinical Trial: DRKS - German Clinical Trials Register ID: DRKS00022860 Title: “ProWear Cochlea” - Development, testing, and evaluation of a hearing training program for cochlear implant patients