近日,著名期刊Applied Physics Reviews发表了来自新加坡国立大学的综述文章,详细介绍了在面向下一代人机接口的技术方面的研究进展
背景 随着 5 G通信和物联网人工智能(AIoT)的显著进步,具有传感技术的可穿戴电子是最近快速发展的研究领域之一,特别是智能家居和医疗保健领域。 从虚拟现实和增强现实 (VR/AR) 概念开始,整个社区在使用智能人机接口(HMI)和云中进一步数据分析方面揭示了海量数据收集的新技术需求。具体来说,HMI 是实现人类与数字化世界和谐共存、高效协作,以使我们的生活更美好的标的。几十年来,人类机器交互不可避免地依赖于不同的控制器,包括触摸板、操纵杆、键盘和鼠标。基本来说,人们对多种传感机制进行了深入的探索和研究,从传统高灵敏度的压阻和电容传感器到能够进行零功耗传感的压电和摩擦电的传感器。基于这些传感器,我们能够检测各种物理参数,以感知外部刺激,实现瞬时和连续操作,如惯性、法线和剪切力、应变和振动,以获得相应的信息或将控制命令传递到机器中。但是,随着进行多功能无缝交互的需求上升,非可穿戴 HMI 暴露了一些棘手的问题,例如体积大、直观和控制精度,尤其是用于监视人类运动或传输复杂命令。视控和声控接口的出现通过解决上述一些问题提高了操作效率。然而,包括隐私在内的其他问题对未来的实施提出了挑战。 摘要 在可预见的未来,智能社会的前景是,在数字世界中,人类与电子产品的联系日益紧密,这将极大地改善我们的生活和生产力。近几十年来,人机界面(HMI)的进步已经从触觉传感器,如触摸板和操纵杆,到现在包括在更加多样化和复杂的设备中精确检测灵巧的身体动作。高度自适应机器学习技术、神经接口和神经形态感知的进步,为下一代应用带来了经济可行的解决方案,如具有亲密和多向感知能力的可穿戴HMIs。这篇综述提供了从触觉传感器及其压阻、电容、压电和摩擦电传感机制开始的人机界面技术的一般知识。进一步的讨论给出了如何机器学习,神经接口,和神经形态电子可用于增强下一代HMIs在即将到来的5 G基础设施和进步的物联网和人工智能的东西在不久的将来。通过触觉传感器与神经电子技术的融合,与人体的运动和生理信号进行有效的交互作用,将会给高级操作和医疗康复带来一场革命。 With the prospect of a smart society in the foreseeable future, humans are experiencing an increased link to electronics in the digital world, which can benefit our life and productivity drastically. In recent decades, advances in the Human Machine Interface (HMI) have improved from tactile sensors, such as touchpads and joysticks, to now include the accurate detection of dexterous body movements in more diversified and sophisticated devices. Advancements in highly adaptive machine learning techniques, neural interfaces, and neuromorphic sensing have generated the potential for an economic and feasible solution for next-generation applications such as wearable HMIs with intimate and multi-directional sensing capabilities. This review offers a general knowledge of HMI technologies beginning with tactile sensors and their piezoresistive, capacitive, piezoelectric, and triboelectric sensing mechanisms. A further discussion is given on how machine learning, neural interfaces, and neuromorphic electronics can be used to enhance next-generation HMIs in an upcoming 5 G infrastructure and advancements in the internet of things and artificial intelligence of things in the near future. The efficient interactions with kinetic and physiological signals from human body through the fusion of tactile sensor and neural electronics will bring a revolution to both the advanced manipulation and medical rehabilitation. |