连续血液净化系统中血压实时监测模块的研究

连续血液净化系统中血压值是确定患者病情的重要参数,因此设计了一种非侵入式的血压实时监测模块。该监测模块采用气压传感器作为检测血压的测量元件,低功耗的单片机MSP430F449作为处理核心,高精度的AD7714作为模数转换模块,实现了对循环管路中血压的非侵入式实时测量。实验结果表明,该血压实时监测模块能实现0.12%精度,输入、输出具有较好的线性关系,能准确反映血压的实时变化。     

物联网在竞技运动监测中的应用研究

物联网技术因其巨大的应用前景而受到各国政府、学术界和工业界的广泛重视。介绍了物联网在竞技运动中的意义,分析了竞技运动中物联网的体系结构,设计了一个可以应用于日常训练中的物联网系统。通过便携式传感器采集运动员的心率、脉搏和血压等生理参数,使用基于RFID技术对不同运动员进行标识,使得教练员可以实时获取运动员的生理参数,制定有针对性的训练计划,以促进竞技运动的发展。     

无线通信远程监护

在分析传统的有线远程监护的基础上,提出了一种更方便、更实用的无线远程监护方法,可以实时监测病人的各种重要生理参数,如心电(ECG)、脑电(EGG)、血压、体温、呼吸率、血氧饱和度(SPO2)等。本文详细论述了无线通信网络的选择和GPRS通信原理。     

Linux平台下远程多生理参数监护系统的实现

利用新一代通信网络GPRS(General Packet Radio Service)与IP网络的无缝接入设计了一种人体多生理参数远程监护系统.系统采用CSN808传感器模块,基于嵌入式Linux平台,实现心电波、血压、体温、脉搏和血氧饱和度等5大生理参数实时监测,具有参数异常报警功能.测试表明:系统能够稳定、准确、实时监测显示各项生理参数,适用于家庭护理、医院等场合.     

透射式血氧饱和度检测方法研究

血氧饱和度是人体的重要参数,临床上许多场合都要对血氧饱和度进行检测。透射式血氧饱和度检测法已经成为一种比较成熟的检测手段,它可以实时、连续和无创伤地进行血氧饱和度检测。本文首先对透射式血氧饱和度检测法的原理进行了详细分析,接着对透射式血压饱和度检测系统的设计进行了阐述,最后指出了目前透射式血氧饱和度检测中仍存在的不足之处以及未来的发展趋势。     

一种实现系统PID参数实时整定与仿真的方法

工业现场PID控制器应用广泛,PID参数的整定直接影响控制器效果,如何整定PID参数变得尤为重要,应用OPC技术、利用Matlab进行实时仿真,使系统PID参数更能适应系统的生产过程。OPC技术作为一种开放式接口标准,其支持ActiveX技术,通过Matlab调用ActiveX控件,可以实现Matlab与OPC服务器进行动态数据交换,通过这种方法可以实现Matlab对工业现场生产实时数据获取。构造半实物仿真的系统。进行PID参数的实时整定,实现分段自适应,获得较好的鲁棒性。     

便携式家庭健康监护仪的研究与设计

文涉及一种家庭健康监护仪的研究与设计。采用模块化的设计方法以PSo C4系列处理器芯片为核心,简单的外围检测电路为辅助完成对人体心电、脉搏血氧和血压三个重要生理参数采集及测量,并通过蓝牙模块实时传输测量数据至手机或PC端,可监测家庭中每个成员的身体状况。通过监护系统硬件电路和软件部分的设计完成监护仪的研发,并进行实验且测试结果表明该监护仪能长时间实时地监测到这三个生理参数。     

基于FastICA算法的脉搏波信号特征参数提取方法研究

经过大量临床证实,脉搏波能反映许多心血管方面的生理信息,脉搏波特征变化可以反映出人体生理系统的状态。为了能够在脉搏波信号中提取更多的生理参数,必须对脉搏波信号的各种特性进行深入的分析。利用光电容积脉搏波描记法(PPG),人们只需要将手指轻微的贴着摄像头就可以采集到手指图像,对图像进行独立成分分析(ICA),找到最接近人体的脉搏波信号。这对基于智能终端分析脉搏波信号的特征,进行呼吸、血压、心率测量的便捷性有很大的提高,为在家居环境下对人体生理参数的实时监测提供了一定的参考。     

基于树莓派的对于圆周运动物体的摄像测量系统

摄像测量技术是信息科学行业比较热门的一个行业,通过摄像头捕获成像并对图像参数进行分析处理便可获得较多的实时信息。本项目设计一款基于树莓派(Raspberry?Pi)的摄像测量系统,主要对圆周运动的物体进行相关参数的测量。该设计可以在摄像头成像范围内对运动的物体进行实时定位,以此来获得长度角度等重要参数的信息。此外,本设计还可以将从正交的两个方向实时显示物体的运动画面,并通过交换机将这两个运动画面传输到终端。针对以上功能,该系统可以用于远程的非接触式测量,如工业中实时监测工件的运行情况,检测零件损坏程度等。     

群体运动生理参数监测手环设计

进行了群体运动生理参数监测手环设计，旨在监测运动者的心率、血氧饱和度以及血压异常情况，通过此系统监测数据，合理评估运动者的健康状态，确保运动安全。本系统下位机主要由STM32F103RCT6控制板、电源模块、HC-12无线传输模块、生理参数检测模块、蜂鸣器以及LED警示灯组成。通过下位机可以获取运动者的心率、血氧饱和度和血压的数据，在显示模块进行生理参数显示，同时可以设置各生理参数的阈值，如检测到生理参数数据在安全阈值之外的情况，给出声光报警提示，警示运动者及时作出缓解调整。     

基于手机热点传输的微型光谱仪系统研究

为满足光谱探测系统微型化及实时现场检测需求,研制了一种基于手机热点传输和Android平台的微型光谱仪系统.系统通过光谱仪端对被测物体的光谱信号进行采集,并利用CCD探测器记录光谱图像,光谱仪端的Open WRT模块作为无线终端连接热点手机,将光谱图像传到手机端,通过Android平台实现光谱图像的处理与图形化显示.测...     

应用于移动互联网的入侵检测系统的研究

随着移动互联网的迅猛发展,智能手机越来越普及,其安全问题也随之而来。入侵检测技术能收集信息并进行分析,通过与规则库比较,发现是否含有入侵攻击。由于目前移动互联网监测能力不足,大量木马入侵手机,严重影响了手机用户的生活。提出了一套应用于移动互联网的入侵检测系统,能有效检测到入侵攻击,并及时响应,保证手机安全。     

Self ‐Powered Insole Plantar Pressure Mapping System

Sensitive monitoring and real‐time foot pressure mapping have important applications for medical treatment/diagnostics, sports training, and even security. In this work, a facile plantar pressure mapping system with a large pressure detection range using piezoelectric nanogenerators serving as the sensor array to acquire pressure signals, and a self‐designed data acquisition (DAQ) circuit board to process and wirelessly send the signals to a mobile terminal, such as a smart phone, are developed. Working with an application program developed in Android, the whole system can accurately monitor and visually display the real‐time pressure distribution during walking. More importantly, by combining a hybridized triboelectric–electromagnetic nanogenerator, a self‐powered, continuous, and real‐time pressure distribution monitoring system is developed, which provides a feasible solution for sport/exercise biomechanics information acquisition, injury prevention, and ulceration prediction in the feet.     

Bidirectional Artificial Neural Networks for Mobile‐Phone Fraud Detection

We propose a system for mobile‐phone fraud detection based on a bidirectional artificial neural network (bi‐ANN). The key advantage of such a system is the ability to detect fraud not only by offline processing of call detail records (CDR), but also in real time. The core of the system is a bi‐ANN that predicts the behavior of individual mobile‐phone users. We determined that the bi‐ANN is capable of predicting complex time series (Call_Duration parameter) that are stored in the CDR.     

Novel methods of faster cardiovascular diagnosis in wireless telecardiology

With the rapid development wireless technologies, mobile phones are gaining acceptance to become an effective tool for cardiovascular monitoring. However, existing technologies have limitations in terms of efficient transmission of compressed ECG over text messaging communications like SMS and MMS. In this paper, we first propose an ECG compression algorithm which allows lossless transmission of compressed ECG over bandwidth constrained wireless link. Then, we propose several algorithms for cardiovascular abnormality detection directly from the compressed ECG maintaining end to end security, patient privacy while offering the benefits of faster diagnosis. Next, we show that our mobile phone based cardiovascular monitoring solution is capable of harnessing up to 6.72 times faster diagnosis compared to existing technologies. As the decompression time on a doctor?s mobile phone could be significant, our method will be highly advantageous in patient wellness monitoring system where a doctor has to read and diagnose from compressed ECGs of several patients assigned to him. Finally, we successfully implemented the prototype system by establishing mobile phone based cardiovascular patient monitoring.     

单片机的智伴系统的设计

本项目主要针对社会上的弱势群体和身体健康需要细心照顾的人群,如空巢老人的健康安全问题。智伴系统采用51单片机为嵌入式核心板,搭载体温、脉搏、血压等检测传感器,将采集到的数据显示在显示屏上,定时将老人的身体数据通过GSM模块发送到的监护人手机上,一旦老人身体出现异常则开启报警功能,并能及时向监护人发送报警信息。     

A mobile care system with alert mechanism.

Hypertension and arrhythmia are chronic diseases, which can be effectively prevented and controlled only if the physiological parameters of the patient are constantly monitored, along with the full support of the health education and professional medical care. In this paper, a role-based intelligent mobile care system with alert mechanism in chronic care environment is proposed and implemented. The roles in our system include patients, physicians, nurses, and healthcare providers. Each of the roles represents a person that uses a mobile device such as a mobile phone to communicate with the server setup in the care center such that he or she can go around without restrictions. For commercial mobile phones with Bluetooth communication capability attached to chronic patients, we have developed physiological signal recognition algorithms that were implemented and built-in in the mobile phone without affecting its original communication functions. It is thus possible to integrate several front-end mobile care devices with Bluetooth communication capability to extract patients' various physiological parameters [such as blood pressure, pulse, saturation of haemoglobin (SpO2), and electrocardiogram (ECG)], to monitor multiple physiological signals without space limit, and to upload important or abnormal physiological information to healthcare center for storage and analysis or transmit the information to physicians and healthcare providers for further processing. Thus, the physiological signal extraction devices only have to deal with signal extraction and wireless transmission. Since they do not have to do signal processing, their form factor can be further reduced to reach the goal of microminiaturization and power saving. An alert management mechanism has been included in back-end healthcare center to initiate various strategies for automatic emergency alerts after receiving emergency messages or after automatically recognizing emergency messages. Within the time intervals in system setting, according to the medical history of a specific patient, our prototype system can inform various healthcare providers in sequence to provide healthcare service with their reply to ensure the accuracy of alert information and the completeness of early warning notification to further improve the healthcare quality. In the end, with the testing results and performance evaluation of our implemented system prototype, we conclude that it is possible to set up a complete intelligent healt care chain with mobile monitoring and healthcare service via the assistance of our system.     

基于Android的手机恶意代码检测与防护技术

随着通信技术以及移动终端的发展,Android系统由于其本身的开源性,滋生了大量的恶意代码。为了满足Android手机用户的安全需求,文中基于Android,采用SVM机器学习思想,构建了恶意代码检测模型,并开发了一套手机恶意代码检测与防护系统,可以对其进行快速检测和深度检测。系统经Android手机测试结果表明,其具有较好的检测精度以及较低的恶意代码漏报率。     

阵列式无线压力传感器系统设计与迟滞补偿研究

为提高传统硅压阻式压力传感器的测量精度,针对性地设计与实现了一种带有迟滞误差校正功能的阵列式无线压力传感器系统。该系统采用了硅压阻式传感器阵列和高精度模数转换器AD7794,以STM32微处理器作为数据采集和信号处理的核心部件,并通过无线蓝牙传输模块将测量数据发送至手机接收端,以手机APP显示测量结果有利于用户对压力实现无线监测。针对硅压阻压力传感器的迟滞非线性,基于最小二乘法与函数校正法对压力传感器阵列的输出信号进行了非线性和迟滞误差补偿,结果表明：迟滞误差从原来的±0.152%降为±0.077%,,有效地提高了系统的测量精度。     

Minimizing queuing delays and number of messages in mobile phone location

The mobility of phones in a cellular or Personal Communication Services (PCS) environment introduces the problem of efficiently locating the called phone. In this paper, we present an analysis of the delay and number of messages transmitted in different sequential and parallel search strategies, considering for the first time the issue of queuing on radio paging channels. Our analysis shows that parallel search may not reduce the time to find a mobile phone if the parameters of the system are unfavorable. We also develop an efficient algorithm for searching with minimum expected number of message when the location of the phone is given by a probability vector.