Searchfield Grant D, Sanders Philip J, Doborjeh Zohreh, Doborjeh Maryam, Boldu Roger, Sun Kevin, Barde Amit
Section of Audiology, The University of Auckland, Auckland, New Zealand.
Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand.
Front Digit Health. 2021 Aug 10;3:724370. doi: 10.3389/fdgth.2021.724370. eCollection 2021.
Digital processing has enabled the development of several generations of technology for tinnitus therapy. The first digital generation was comprised of digital Hearing Aids (HAs) and personal digital music players implementing already established sound-based therapies, as well as text based information on the internet. In the second generation Smart-phone applications (apps) alone or in conjunction with HAs resulted in more therapy options for users to select from. The 3rd generation of digital tinnitus technologies began with the emergence of many novel, largely neurophysiologically-inspired, treatment theories that drove development of processing; enabled through HAs, apps, the internet and stand-alone devices. We are now of the cusp of a 4th generation that will incorporate physiological sensors, multiple transducers and AI to personalize therapies. To review technologies that will enable the next generations of digital therapies for tinnitus. A "state-of-the-art" review was undertaken to answer the question: what digital technology could be applied to tinnitus therapy in the next 10 years? Google Scholar and PubMed were searched for the 10-year period 2011-2021. The search strategy used the following key words: "tinnitus" and ["HA," "personalized therapy," "AI" (and "methods" or "applications"), "Virtual reality," "Games," "Sensors" and "Transducers"], and "Hearables." Snowballing was used to expand the search from the identified papers. The results of the review were cataloged and organized into themes. This paper identified digital technologies and research on the development of smart therapies for tinnitus. AI methods that could have tinnitus applications are identified and discussed. The potential of personalized treatments and the benefits of being able to gather data in ecologically valid settings are outlined. There is a huge scope for the application of digital technology to tinnitus therapy, but the uncertain mechanisms underpinning tinnitus present a challenge and many posited therapeutic approaches may not be successful. Personalized AI modeling based on biometric measures obtained through various sensor types, and assessments of individual psychology and lifestyles should result in the development of smart therapy platforms for tinnitus.
数字处理推动了几代耳鸣治疗技术的发展。第一代数字技术包括数字助听器（HA）和个人数字音乐播放器，它们实施已有的基于声音的疗法，以及互联网上基于文本的信息。第二代则是智能手机应用程序（app）单独使用或与助听器结合，为用户提供了更多的治疗选择。第三代数字耳鸣技术始于许多新颖的、主要受神经生理学启发的治疗理论的出现，这些理论推动了治疗技术的发展；通过助听器、应用程序、互联网和独立设备得以实现。我们现在正处于第四代技术的开端，这一代技术将整合生理传感器、多个换能器和人工智能，实现个性化治疗。为了回顾能够推动下一代耳鸣数字疗法的技术，开展了一项“最新技术”综述，以回答以下问题：未来10年可应用于耳鸣治疗的数字技术有哪些？在谷歌学术和PubMed上搜索了2011年至2021年这10年的文献。搜索策略使用了以下关键词：“耳鸣”以及["助听器", "个性化治疗", "人工智能"（以及"方法"或"应用"）, "虚拟现实", "游戏", "传感器"和"换能器"]，还有“可穿戴设备”。通过滚雪球的方式从已识别的论文中扩大搜索范围。综述结果被分类整理成不同主题。本文确定了耳鸣智能疗法发展中的数字技术和相关研究。识别并讨论了可能应用于耳鸣治疗的人工智能方法。概述了个性化治疗的潜力以及在生态有效环境中收集数据的益处。数字技术在耳鸣治疗中的应用前景广阔，但耳鸣背后不确定的机制带来了挑战，许多假定的治疗方法可能并不成功。基于通过各种传感器类型获得的生物特征测量以及对个体心理和生活方式的评估进行个性化人工智能建模，应能推动耳鸣智能治疗平台的发展。
