Gnadlinger Florian, Werminghaus Maika, Selmanagić André, Filla Tim, Richter Jutta G, Kriglstein Simone, Klenzner Thomas
Faculty of Informatics, Masaryk University, Brno, Czech Republic.
University of Applied Sciences Berlin, Berlin, Germany.
JMIR Serious Games. 2024 Dec 3;12:e55231. doi: 10.2196/55231.
Cochlear implants are implanted hearing devices; instead of amplifying sounds like common hearing aids, this technology delivers preprocessed sound information directly to the hearing (ie, auditory) nerves. After surgery and the first cochlear implant 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 computer-based auditory training.
In general, self-directed, computer-based auditory training tasks have already shown advantages. However, compliance of cochlear implant recipients is still a major factor, especially for self-directed training at home. Hence, we aimed to explore the combination of 2 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).
Following the suggestions of the evidence-centered design framework, a domain analysis of hearing therapy was conducted, allowing us to partially describe 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 was based on 7 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 cochlear implant recipients used the system during a feasibility study for 4 weeks.
The 23 adult participants (20 women; 3 men) fulfilled 2259 tasks. In total, 2004 (90.5%) tasks were solved correctly, and 255 (9.5%) tasks were solved incorrectly. A generalized additive model analysis of these tasks indicated that the system adapted to the estimated competency levels of the cochlear implant recipients more quickly in the beginning than at the end. Compared with a uniform distribution of all task types, the recommended task types differed (χ²=86.713; P<.001), indicating that the system selected specific task types for each patient. This is underlined by the identified categories for the error proportions of the task types.
This contribution demonstrates the feasibility of combining an intelligent tutoring system with a serious game in cochlear implant rehabilitation therapies. The findings presented here could lead to further advances in cochlear implant care and aural rehabilitation in general.
German Clinical Trials Register (DRKS) DRKS00022860; https://drks.de/search/en/trial/DRKS00022860.
人工耳蜗是植入式听力设备；与普通助听器放大声音不同，这项技术将预处理后的声音信息直接传递至听觉神经。手术及首次人工耳蜗激活后，患者必须练习解读新的听觉感受，尤其是对于语言理解。这一康复过程伴随着通过与治疗师面对面训练、自主训练以及基于计算机的听觉训练进行的听力治疗。
总体而言，自主的、基于计算机的听觉训练任务已显示出优势。然而，人工耳蜗接受者的依从性仍是一个主要因素，尤其是对于在家中的自主训练。因此，我们旨在探索两种技术的结合，以在这种情况下提高学习者的积极性：适应性学习（以智能辅导系统的形式）和基于游戏的学习（以严肃游戏的形式）。
遵循以证据为中心的设计框架的建议，对听力治疗进行了领域分析，使我们能够将人类听力技能部分描述为概率能力模型（贝叶斯网络）。我们开发了一种算法，该算法使用这样的模型来估计患者当前的能力水平并创建训练建议。对于训练，我们开发的任务系统基于7种语言理解任务类型，这些类型作为自动生成不同难度任务的蓝图。为此，创建了1053个带有元信息标签的音频资产。我们将自适应任务系统嵌入到类似漫画的移动严肃游戏中。说德语的人工耳蜗接受者在一项为期4周的可行性研究中使用了该系统。
23名成年参与者（20名女性；3名男性）完成了2259项任务。总共2004项（90.5%）任务被正确解决，255项（9.5%）任务被错误解决。对这些任务的广义相加模型分析表明，该系统在开始时比结束时更快地适应人工耳蜗接受者的估计能力水平。与所有任务类型的均匀分布相比，推荐的任务类型有所不同（χ²=86.713；P<.001），表明该系统为每个患者选择了特定的任务类型。任务类型错误比例的已识别类别也证实了这一点。
本研究证明了在人工耳蜗康复治疗中将智能辅导系统与严肃游戏相结合的可行性。此处呈现的研究结果可能会推动人工耳蜗护理及总体听觉康复的进一步发展。
德国临床试验注册中心（DRKS）DRKS00022860；https://drks.de/search/en/trial/DRKS00022860 。
