Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC 3216, Australia.
Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC 3216, Australia.
Comput Methods Programs Biomed. 2022 Jan;213:106541. doi: 10.1016/j.cmpb.2021.106541. Epub 2021 Nov 17.
Wearable technologies have added completely new and fast emerging tools to the popular field of personal gadgets. Aside from being fashionable and equipped with advanced hardware technologies such as communication modules and networking, wearable devices have the potential to fuel artificial intelligence (AI) methods with a wide range of valuable data.
Various AI techniques such as supervised, unsupervised, semi-supervised and reinforcement learning (RL) have already been used to carry out various tasks. This paper reviews the recent applications of wearables that have leveraged AI to achieve their objectives.
Particular example applications of supervised and unsupervised learning for medical diagnosis are reviewed. Moreover, examples combining the internet of things, wearables, and RL are reviewed. Application examples of wearables will be also presented for specific domains such as medical, industrial, and sport. Medical applications include fitness, movement disorder, mental health, etc. Industrial applications include employee performance improvement with the aid of wearables. Sport applications are all about providing better user experience during workout sessions or professional gameplays.
The most important challenges regarding design and development of wearable devices and the computation burden of using AI methods are presented. Finally, future challenges and opportunities for wearable devices are presented.
可穿戴技术为个人小工具这一热门领域增添了全新且快速发展的工具。除了时尚并配备了先进的硬件技术(如通信模块和网络)外,可穿戴设备还具有利用各种有价值的数据为人工智能(AI)方法提供动力的潜力。
各种 AI 技术,如监督式、非监督式、半监督式和强化学习(RL),已经被用于执行各种任务。本文回顾了利用 AI 实现目标的可穿戴设备的最新应用。
回顾了监督式和非监督式学习在医疗诊断中的特定应用示例。此外,还回顾了将物联网、可穿戴设备和 RL 相结合的示例。还将为特定领域(如医疗、工业和运动)展示可穿戴设备的应用示例。医疗应用包括健身、运动障碍、心理健康等。工业应用包括借助可穿戴设备来提高员工绩效。运动应用则专注于在锻炼或专业比赛期间提供更好的用户体验。
提出了设计和开发可穿戴设备以及使用 AI 方法的计算负担方面的最重要挑战。最后,提出了可穿戴设备的未来挑战和机遇。