一种实时的无线高速视频眼震追踪系统
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摘要
针对良性阵发性位置性眩晕(BPPV)诊断中视频眼震记录仪存在的分辨率低、帧率低、抗干扰能力不足的问题,提出了一种实时的无线高速视频眼震追踪系统。基于ARM Cortex-A7构架和最新5 G WiFi模块设计了高速无线传输的核心控制板,使用MIPI相机接口保证了视频的高速采集,采用H. 265高性能编码技术实现视频的无损压缩,通过RTSP实时网络传输协议完成无线传输网络构建,终端通过无线网络接收眼震视频,进行基于暗瞳的实时眼震追踪算法分析获取眼震信息。在视频分辨率、帧率对系统精度的影响与不同传输方式的抗干扰能力,实验结果表明:提出的高速视频眼震分析系统精度高、抗干扰能力强,能准确获取眼震轨迹,为疾病的诊断奠定了基础。
Aiming at the problem of low resolution,low frame rate,and lack of anti-jamming capability of videonystagmography in benign positional parsmal vertigo(BPPV) diagnosis,a real-time wireless high-speed videonystagmography tracking system is proposed. The system constructs the core control board which can realize highspeed wireless transmission based on ARM Cortex-A7 architecture and 5 G WiFi module,use MIPI camera interface to ensure high-speed video acquisition,using H. 265 high-performance coding technology to achieve video lossless compression,completing the construction of the wireless transmission network through the real-time RTSP network transmission protocol,the terminal receives the nystagmus video through the wireless network,and performs the real-time nystagmus tracking algorithm analysis based on the dark pupil to acquire the nystagmus information. The effect of video resolution and frame rate on system precision and anti-jamming ability of different transmission modes are tested. The experimental results show that the proposed high-speed video-nystagmography tracking system has high precision and strong anti-interference ability,and can accurately obtain nystagmus trajectory,which lay the foundation for the diagnosis of the disease.
Aiming at the problem of low resolution,low frame rate,and lack of anti-jamming capability of videonystagmography in benign positional parsmal vertigo(BPPV) diagnosis,a real-time wireless high-speed videonystagmography tracking system is proposed. The system constructs the core control board which can realize highspeed wireless transmission based on ARM Cortex-A7 architecture and 5 G WiFi module,use MIPI camera interface to ensure high-speed video acquisition,using H. 265 high-performance coding technology to achieve video lossless compression,completing the construction of the wireless transmission network through the real-time RTSP network transmission protocol,the terminal receives the nystagmus video through the wireless network,and performs the real-time nystagmus tracking algorithm analysis based on the dark pupil to acquire the nystagmus information. The effect of video resolution and frame rate on system precision and anti-jamming ability of different transmission modes are tested. The experimental results show that the proposed high-speed video-nystagmography tracking system has high precision and strong anti-interference ability,and can accurately obtain nystagmus trajectory,which lay the foundation for the diagnosis of the disease.
引文
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[2]VON BREVERN M,BERTHOLOR P,BRANDT T,等.良性阵发性位置性眩晕诊断标准[J].中国全科医学,2017,20(11):1275-1281.
[3]王长元,史学颖.基于视频眼震图的瞳孔中心定位方法研究[J].计算机与数字工程,2011,39(3):128-130.
[4]王锦榕.眼动跟踪系统设计与实现[D].大连:大连理工大学,2011.
[5]刘紫燕,冯亮,祁佳.一种基于FPGA的实时视频跟踪系统硬件平台设计[J].传感器与微系统,2014,33(7):98-102.
[6]周建萍,刘洪英,皮喜田,等.基于Wi Fi技术的便携式耳鼻喉内视镜系统设计[J].传感器与微系统,2018,37(1):99-101.
[7]潘银松,张威,张文普,等.基于USB 2.0的X射线图像传感器数据采集系统[J].传感器与微系统,2009,28(3):92-94.
[8]郭政.5 G Wi Fi标准---802.11ac解析及应用展望[J].科技传播,2012,4(15):217-218.
[9]陈学军,杨永明,何为.红外眼震视频瞳孔寻迹[J].生物医学工程学杂志,2012,29(2):347-351.
[10]WU J H,OU W L,FAN C P.NIR-based gaze tracking with fast pupil ellipse fitting for real-time wearable eye trackers[C]∥2017IEEE Conference on Dependable and Secure Computing,IEEE,2017:93-97.
[11]ZHAO Y,QU Z,HAN H,et al.An effective and rapid localization algorithm of pupil center based on Starburst model[C]∥Advanced Information Management,Communicates,Electronic and Automation Control Conference,IEEE,2017:988-991.
[12]FITZGIBBON A W,PILU M,FISHER R B.Direct least squares fitting of ellipses[C]∥International Conference on Pattern Recognition,IEEE,2002:253-257.
[13]HOLMQVIST K,NYSTRM M,MULVEY F.Eye tracker data quality:What it is and how to measure it[C]∥Symposium on Eye Tracking Research and Applications,ACM,2012:45-52.
[14]张李娜,史学锋,赵堪兴.视频眼动仪系统测量的精确度及不同红外照明强度的影响[J].中华实验眼科杂志,2015,33(12):1118-1121.