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基于霍尔传感器阵列和OpenGL技术的三维恒定磁源定位系统

3-D Tracking System for the Micro Medical Devices in the Human Body Based on the Hall Effect Sensor Array and OpenGL Technology

【作者】 吴旭东

【导师】 彭承琳;

【作者基本信息】 重庆大学 , 生物医学工程, 2008, 博士

【摘要】 目前,无创、微创诊疗正是医疗领域重要的发展方向,药丸式无线内窥镜,药丸式施药装置作为最近发展起来的诊疗技术,其无创、快速的优势被采用在临床及药物研发领域当中,这其中有些技术已经得到市场化的检验,比如M2A,重庆金山公司的胶囊内窥镜等等,同时,越来越多的研发人员正不断推动该技术往着低成本,主动式,更加准确等方向发展。在药丸式微型诊疗设备的应用过程中,如何对进入人体的设备进行有效的检测,能实时知道进入人体的微型装置到底在什么位置及其运行轨迹,医疗人员或科技工作者才能实现对微型装置有效的控制,因此,对于进入人体的微型装置的定位方法便成为药丸式微型诊疗应用过程中的关键环节。传统上,对于进入人体的诊疗装置的定位方式主要为X-光设备,超声定位,ECT定位,基于Squid对磁标记定位等,X光定位和ECT定位方式存在辐射问题,患者长期处于辐射照射下势必会有害健康,同时X光定位也存在三维信息不明显,定位不直观的缺点。超声定位中温度、湿度、气流以及发射器的尺寸都影响了定位精度。Squid设备由于其昂贵的成本,使普通消费者望而却步。因此,采用一种无创,实时,简便,成本低廉的定位方式成为人们研究重点。基于霍尔原理的磁定位方式具有非接触、快速、应用简便的特点,霍尔传感器也被广泛的应用在位置检测、电流等领域当中,本系统采用了基于霍尔原理的磁场检测方法,在微型医疗装置内布置了恒定磁源,检测进入人体后微型装置的磁场信息,为了在空间内有效检测,研发了三维空间磁场检测的传感器模块,该模块采用了背靠背式的传感器布置,并布置了传感器模块阵列,覆盖了人体腹部区域以便准确检查。传感器模块检测空间磁场信息之后,便由USB接口的多通道数据采集卡进行数据采集,数据被采集进入计算机后,进行滤波处理,并采用基于磁偶极子模型的定位算法对磁场信息中包含的位置信息进行计算,并得出结果。为了更加直观的对定位结果进行观测,开发了基于OpenGL技术的三维操作界面,对整个定位过程进行控制,显示并记录结果,该操作软件还提供了中间数据和结果数据的读写功能,以便对定位过程进行回放,便于技术的改进。在该技术的实施过程中,地磁场由于与恒定磁源具有相同的磁场性质,对于地磁场的消除我们尝试了独立分量分析(ICA)算法和地磁场标定算法进行分离,从实际检测结果可以看出,地磁场标定算法具有简单,高效,准确滤除地磁场干扰的特点,因此在实际中得到应用。对于定位准确性,论文讨论了磁偶极子理想化模型在定位过程中的适用范围,该理想化模型中磁源距离传感器模块较近的情况下便会引起磁偶极子模型的失真,这也是误差产生的重要原因。目前,已经开发了基于霍传感器阵列和OpenGL技术实验室样机,并进行了模拟肠道实验和初步的人体试验,通过模拟肠道实验,可以看到该系统能反映微型装置的走向,在定位精度上存在一定误差,在人体试验中,由于人体肠道复杂的分布,实验结果密集程度反映了人体肠道的分布情况,但是如何对人体肠道中的微型装置位置直观有效的表达出来,仍需要进一步的研究。

【Abstract】 As a significant trend of the medical diagnosis, the noninvasive technology has been revolutionized by the modern engineering technologies. Recently, a new non-invasive technique, the MEMS Medical Capsule has been developed which shows brilliant potential in the application of disease area observation, local drug release and wireless monitoring of the gastrointestinal parameters. Up to now, many MEMS Medical Capsules are available commercially, such as M2A, ESO-PILL NORIKA3 to name but a few. In clinical use, when the capsule is swallowed, it is critical for the doctor to precisely track the movement and location of the capsule in order to organize an effective diagnosis scheme. Thus how to wirelessly track the capsule inside human body has become an area of interest.So far, some methods have been implemented to wirelessly track a MEMS Medical Capsule, such as Magnetic Marker Monitoring (MMM), ECT, Digital X-ray Gastrointestinal Tract. However, the MMM technology is based on the DC-SQUID which is hampered by the high cost of practical use. The harmful radiation exposure is the weakness of both the X-ray imaging and ECT. Moreover, the low trace observability of X-Ray sets anther obstacle for easy application of capsule tracking. To provide a low-cost, harmless and easy-to-operate method, the magnetic tracking technique was early developed by Donald G. Polvani et al (1998), whose patent presented the sketch of magnetic positioning system including the foundation of algorithms on paper. V.Schlageter, et al (2001,2002) described a magnetic sensing technique with the Hall Sensor array. They introduced a real-time sensing hardware, which is, however, not wearable. Based on the research aforementioned, we develop a wearable tracking system based on the Hall Effect and Quiescent Magnetic field. This system is composed of a wearable vest and the software interface. The Hall Effect sensing modules detect the magnetic field signals of a tiny magnet assembled in the capsule, then the signals are collected by a USB data collecting card and transferred to a workstation where data procession and calculation are accomplished, finally the location of the capsule is presented in the three-dimension software interface.To accomplish the real-time data collection and reduce the noise, some effective multi-channel data collecting and processing solutions are implemented. Several trial tests have been performed with relatively accurate expectation to justify the precision of the system. The results of the volunteer experiments compared with the X-ray image of the small intestine demonstrate that this system can effectively trace the motion of the capsule inside the twisted intestine.To limit the electromagnetic interference, the classic low passing circuit and a digital signal filter have been developed which restrain the electromagnetic noise effectively. However, the earth itself is a huge magnet with the same distributional characteristic of magnetic filed as our tiny magnet inside the capsule which can not be reduced by the methods implemented for the electromagnetic noise reduction. To eliminate the earth magnetic interference in a low cost and effective way, a method designated by the Magnetic Interference Level Labeling is developed.The Ideal Magnetic Dipole Model also leads to the detecting error; we discussed the limitation of the model when the magnetic source locates not far from the detection sensor.From the results of the experiments, we can see the trace reported by the system precisely reflects the actual traveling path of the capsule. The relative locating error of the system was approximately around 10%. Thus conclusively, the results of this trial test demonstrate that the system is qualified to locate the trace of the capsule. The volunteer experiments have been tested for clinic use, the results of which indicate that the trace basically represents the distribution of the small intestine even though it highly twists. Meanwhile, the results also reflect this system effectively reduces the interference from the earth magnetic field which eases the practical use considerably.To improve the system accuracy and the observation quality, we focus on the efforts to decrease the systematic error, reduce the noise and make the mathematical model more accurate.The mathematical model of the tracking algorithm was simply based on the magnetic dipole when the magnetic source located far from the sensing module. However, in reality the magnetic dipole model is limited when the capsule moves close to the sensing module which leads to the low precision. Therefore the optimization of the mathematical model of the tracking algorithm is the main focus for further study.

  • 【网络出版投稿人】 重庆大学
  • 【网络出版年期】2009年 06期
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