Tengteng Lei;Runxiao Shi;Zong Liu;Yushen Hu;Man Wong
{"title":"用于沉浸式显示器的神经形态传感器感知系统","authors":"Tengteng Lei;Runxiao Shi;Zong Liu;Yushen Hu;Man Wong","doi":"10.1109/OJID.2023.3343309","DOIUrl":null,"url":null,"abstract":"An immersive display implementing enhanced virtual and augmented reality demands a higher level of human-machine interaction and requires input from a variety of sensors that monitor human activities. However, the processing of a large volume of sensory data challenges the classical von Neumann computing architecture in terms of latency and energy efficiency. Made possible by the sharing of a common metal-oxide (MO) thin-film transistor (TFT) technology, the monolithic integration of a sensor array and a neuromorphic signal processor has been reported as an approach to meeting such requirement. Reviewed presently is the realization of an analog front-end human-machine interfacing system and its application to the acquisition of bio-potential signals. Active-matrix chemical and tactile sensor arrays integrated with biomimetic artificial neural networks based on dual-gate MO TFTs for neuromorphic signal processing are described. Finally, the challenges and prospects of enhanced neuromorphic sensor-perception systems for immersive displays are discussed.","PeriodicalId":100634,"journal":{"name":"IEEE Open Journal on Immersive Displays","volume":"1 ","pages":"20-27"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10360208","citationCount":"0","resultStr":"{\"title\":\"Neuromorphic Sensor-Perception Systems for Immersive Displays\",\"authors\":\"Tengteng Lei;Runxiao Shi;Zong Liu;Yushen Hu;Man Wong\",\"doi\":\"10.1109/OJID.2023.3343309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An immersive display implementing enhanced virtual and augmented reality demands a higher level of human-machine interaction and requires input from a variety of sensors that monitor human activities. However, the processing of a large volume of sensory data challenges the classical von Neumann computing architecture in terms of latency and energy efficiency. Made possible by the sharing of a common metal-oxide (MO) thin-film transistor (TFT) technology, the monolithic integration of a sensor array and a neuromorphic signal processor has been reported as an approach to meeting such requirement. Reviewed presently is the realization of an analog front-end human-machine interfacing system and its application to the acquisition of bio-potential signals. Active-matrix chemical and tactile sensor arrays integrated with biomimetic artificial neural networks based on dual-gate MO TFTs for neuromorphic signal processing are described. Finally, the challenges and prospects of enhanced neuromorphic sensor-perception systems for immersive displays are discussed.\",\"PeriodicalId\":100634,\"journal\":{\"name\":\"IEEE Open Journal on Immersive Displays\",\"volume\":\"1 \",\"pages\":\"20-27\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10360208\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Journal on Immersive Displays\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10360208/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal on Immersive Displays","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10360208/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
实现增强型虚拟现实和增强现实技术的沉浸式显示器要求更高水平的人机交互,并需要来自各种监测人类活动的传感器的输入。然而,大量感知数据的处理在延迟和能效方面对传统的冯-诺依曼计算架构提出了挑战。通过共享通用金属氧化物(MO)薄膜晶体管(TFT)技术,传感器阵列和神经形态信号处理器的单片集成已被报道为满足此类要求的一种方法。目前介绍的是模拟前端人机接口系统的实现及其在生物电位信号采集中的应用。此外,还介绍了基于双栅 MO TFT 的有源矩阵化学和触觉传感器阵列与仿生物人工神经网络的集成,用于神经形态信号处理。最后,讨论了用于沉浸式显示器的增强型神经形态传感器感知系统所面临的挑战和前景。
Neuromorphic Sensor-Perception Systems for Immersive Displays
An immersive display implementing enhanced virtual and augmented reality demands a higher level of human-machine interaction and requires input from a variety of sensors that monitor human activities. However, the processing of a large volume of sensory data challenges the classical von Neumann computing architecture in terms of latency and energy efficiency. Made possible by the sharing of a common metal-oxide (MO) thin-film transistor (TFT) technology, the monolithic integration of a sensor array and a neuromorphic signal processor has been reported as an approach to meeting such requirement. Reviewed presently is the realization of an analog front-end human-machine interfacing system and its application to the acquisition of bio-potential signals. Active-matrix chemical and tactile sensor arrays integrated with biomimetic artificial neural networks based on dual-gate MO TFTs for neuromorphic signal processing are described. Finally, the challenges and prospects of enhanced neuromorphic sensor-perception systems for immersive displays are discussed.