Real time monitoring and analysis via the medical information bus, Part I

Because of the complexity of monitored data in modern intensive care units (ICUs), and the risk of information being overlooked if medical staff have to pay attention to a multiplicity of monitoring apparatuses and alarm signals, the data for each patient may well be best presented on a single bedside screen after digestion by expert system techniques. Such central units should be able to deal with data from any monitoring apparatus, not just a predefined set. Furthermore, relay of the information from each bed to a central control station (one per ICU) is desirable for the purposes of permanent storage and for in-depth analysis. The paper describes a comprehensive system for ICU monitoring management and patient data analysis that integrates multiple expert systems and computers. The basic difficulties in applying expert system techniques to monitoring are overcome with the shell OPS/83, which allows calls to sequential C routines and allows time-driven reasoning through appropriate design of the inference engine and rules. Flexibility as regards connectable monitoring apparatus is afforded by basing data acquisition mainly, though not exclusively, on the IEEE Medical Information Bus.     

Real-time identification and archiving of micro-embolic Doppler signals using a knowledge-based DSP system

Identification of micro-emboli in the cerebral circulation using transcranial Doppler ultrasound provides valuable clinical information, but, currently, embolic signal detection and analysis are significantly limited because they mainly rely on costly off-line analysis by human experts. In this study, a reliable, high-resolution, real-time automated system for the detection and archiving of embolic signals was designed and implemented using expert system theory and modern DSP technology. Preliminary tests were conducted to evaluate the functions and the performance of the system using data from ten carotid endarterectomy patients and two normal volunteers. Using the widely accepted 7 dB threshold for human reliability and a human expert, majority-decision gold standard, the real-time system reached sensitivity and specificity of 93.6% and 99.3%, respectively, which were close to the results obtained by three human experts under ideal laboratory conditions (90.1% and 99.8%, 98.4% and 99.9%, 98.9 and 99.9%). The new system has the potential to be used either as a bedside monitoring and signal acquisition device, or as a laboratory investigation tool.     

远程专家咨询系统

针对家庭心电图远程监护系统,我们设计并实现了心电图的远程专家咨询系统。该系统具有心电图数据的选择,自动传送和显示功能,远地专家可根据接收的数据给医院值班医生提供参考意见,本文介绍了监护中心和专家端软件设计及两机间的通讯协议。     

Derivation of rule-based knowledge from established medical outlines

The purpose of this paper is to describe the derivation of a rule base for an expert system from an existing medical auditing method called a criteria map. The criteria map represents the physician's logic in the specialty involved. The system described, EMERGE, is written in the standard Pascal programming language, operates on a microcomputer, and provides a convenient user-interface. All medical knowledge in EMERGE is contained in an independent set of production rules, which are derived from the criteria map.     

Stress and fitness monitoring embedded on a modern telematics platform

Lack of regular physical activity and high stress levels are the leading causes of several illnesses. There is thus a real need for a personal low-cost and mobile monitoring solution over extended periods to prevent health risks. Based on the above fact, this article presents a system capable of estimating and monitoring both stress and fitness levels without a physical consultation of a medical specialist. The system consists of three main subcomponents: a mobile real-time acquisition of physiological as well as subjective data, an expert model for stress and fitness estimations based on physiological signals collected from wireless vital sensors, and a secure and scalable telematics platform on which the entire system is embedded. Features and tasks performed by the telematics platform will be presented. The experimental part of the work involved a representative number of subjects. Results for 110 subjects whose fitness levels were assessed at different periods of the year and 50 individuals whose stress scores were assessed at different times of the day showed a high correlation of the estimated values with the true ones. The application of such a low-cost monitoring system will improve the quality of service in preventive medicine.     

Smart Vest: wearable multi-parameter remote physiological monitoring system

The wearable physiological monitoring system is a washable shirt, which uses an array of sensors connected to a central processing unit with firmware for continuously monitoring physiological signals. The data collected can be correlated to produce an overall picture of the wearer's health. In this paper, we discuss the wearable physiological monitoring system called ‘Smart Vest’. The Smart Vest consists of a comfortable to wear vest with sensors integrated for monitoring physiological parameters, wearable data acquisition and processing hardware and remote monitoring station. The wearable data acquisition system is designed using microcontroller and interfaced with wireless communication and global positioning system (GPS) modules. The physiological signals monitored are electrocardiogram (ECG), photoplethysmogram (PPG), body temperature, blood pressure, galvanic skin response (GSR) and heart rate. The acquired physiological signals are sampled at 250 samples/s, digitized at 12-bit resolution and transmitted wireless to a remote physiological monitoring station along with the geo-location of the wearer. The paper describes a prototype Smart Vest system used for remote monitoring of physiological parameters and the clinical validation of the data are also presented.     

基于BP神经网络的医疗诊断专家系统

设计了一种基于BP神经网络的医疗诊断专家系统,利用专家先验知识和神经网络的数值推理、自学习能力,对疾病进行分析处理,与以往医疗诊断方法相比,该系统自动化程度高,诊断可靠准确。本文介绍了系统的总体结构和关键技术。     

Development of a Kidney TeleUltrasound Consultation System

This paper presents the development of kidney TeleUltrasound consultation system. The TeleUltrasound system provides an innovative design that aids the acquisition, archiving, and dissemination of medical data and information over the internet as its backbone. The system provides data sharing to allow remote collaboration, viewing, consultation, and diagnosis of medical data. The design is layered upon a standard known as Digital Imaging and Communication in Medicine (DICOM). The DICOM standard defines protocols for exchanging medical images and their associated data. The TeleUltrasound system is an integrated solution for retrieving, processing, and archiving images and providing data storage management using Structured Query Language (SQL) database. Creating a web-based interface is an additional advantage to achieve global accessibility of experts that will widely open the opportunity of greater examination and multiple consultations. This system is equipped with a high level of data security and its performance has been tested with white, black, and gray box techniques. And the result was satisfactory. The overall system has been evaluated by several radiologists in Malaysia, United Arab Emirates, and Sudan, the result is shown within this paper.     

Expert systems in medicine: a biomedical engineering perspective

Knowledge-based expert systems for medical applications have received considerable attention in recent years. In this review, fundamental terms and notions of artificial intelligence techniques as applied to expert systems are introduced. The most well-known and influential medical expert systems are discussed in detail, and newer efforts are surveyed. A critical comparison of strengths and weaknesses of the systems is made, discussing depth and complexity of knowledge, acquisition of knowledge, user interaction and explanations, knowledge engineering tools, system evaluations, and user resistance. Long- and short-term trends are appraised.     

人工智能技术及其在医学诊断中的应用及发展

本文对人工智能技术在常规医学及其医学诊断专家系统中的发展情况作了回顾，并对人工神经网络在医学诊断系统中的应用作了概述，阐明了在医学诊断系统中，主要的困难在于多种疾病的共存现象，即许多病人有着潜伏在自身内部的其它相关性疾病，而制约医学影像专家系统发展的主要原因是高级视觉系统本身的缺陷，即从医学扫描器上获得的图像数据可能是噪声和模糊的。从而增加了专家系统的复杂性，最后对人工智能技术在医学影像诊断系统中的发展前景作了展望。     

Intelligent agents technology applied to tasks scheduling and communications management in a critical care telemonitoring system

This work presents an important part of our telemedicine system for critical care units: a distributed module based on intelligent agents technology that is dedicated to the process management of a network for medical monitoring, including distribution and control of processing tasks and bandwidth management. The system provides the real-time acquisition and analysis of physiological data, the graphical visualisation of these data, and their transmission to a central system charged with the collection and control of all the information concerning the patient, including knowledge-based systems (KBS) for medical reasoning.     

人工智能技术在医学影像专家系统中的应用及发展

本文对人工智能技术在常规医学及其医学影像专家系统中的发展情况作了回顾 ,阐明了在医学诊断系统中 ,主要困难在于多种疾病的同时并发 ,即在许多病人中存在着一种疾病的症状潜伏着多种其它疾病的症状的现象。而医学影像专家系统发展的困难在于高级视觉系统内在的不足 ,从医学扫描器上获得的数据可能是噪声和模糊的 ,从而增加了专家系统的复杂性。最后对人工智能技术在医学影像专家系统中的发展前景作了展望。     

Evaluation of atopy through an expert system: description of the database

Background In order to understand the medical decision taken during the intaial visit of a new asthmatic patient, a group experts designed an expert system which provides conclusions about severity, precipiting factors and treatment. Rules for atopy and the assesment of allergic factors have been discussed and implementedin the expert system. Conclusion about severity have been yet validated using an appropriate methodology. Objective The aim of this study was to investigate a sample of 471 patients according to conclusions regarding atopy. Methods A total of 471 cases report forms (CRf) was filled in for adult asthmatic outpatients, seen for the first time in our clinic without emergency situtations. Data of each CRF were used by the expert systemto draw conclusion. The expert systsm discerns threee patterns fir atopy, yes, possible or no. The variables known to reflect different features according to the classification of asthma as atopic or not have been studied. The Variables used in the rules for atopy, obviously linked to the conclusion, were not completed. For many medical problem no unique objectives solution esixts and this is why a group of patients with possible atomy was introduced. Results Patients with atopy had less severe asthama (P=0.01), a better FEV1 value (P=0.0007)and showed their first symptoms of asthama erlier (P=0.00001)than patients without atopy. Conclusion The Characteristics of the group studied here are consistent with the literature. This could be considered as an indirect validation of the expert system. Moreover, Patients with possible atopy show intermediate findings for these variables and it is possible to suggest a‘dose-effect’relationship.     

HIS与医保系统间基于HL7标准的接口探讨

随着国家医疗体制改革的深化,社会医疗保险事业正在全面推行,医保系统与医院信息系统(HIS系统)之间的信息交互势在必行。HL7作为医学电子数据交换的标准日益得到医学界的重视。本文首先阐述了采用HL7进行研究的必要性,接着介绍了医疗信息通讯标准HL7的一些基本概念,最后着重讨论了利用HL7标准实现HIS与医保系统之间无缝连接的基本方法和实践。     

Building a case-based diet recommendation system without a knowledge engineer

We present a new approach to the effective development of menu construction systems that allow to automatically construct a menu that is strongly tailored to the individual requirements and food preferences of a client. In hospitals and other health care institutions dietitians develop diets for clients which need to change their eating habits. Many clients have special needs in regards to their medical conditions, cultural backgrounds, or special levels of nutrient requirements for better recovery from diseases or surgery, etc. Existing computer support for this task is insufficient-many diets are not specifically tailored for the client's needs or require substantial time of a dietitian to be manually developed. Our approach is based on case-based reasoning, an artificial intelligence technique that finds increasing entry into industrial practice. Our approach goes beyond the traditional case-based reasoning (CBR) approach by allowing an incremental improvement of the system's competency during routine use of the system. The improvement of the system takes place through a direct expert user-system interaction while the expert is accomplishing their tasks of constructing a diet for a given client. Whenever the system performs unsatisfactorily, the expert will need to modify the system-produced diet 'manually', i.e. by entering the desired modifications into the system. Our implemented system, menu construction using an incremental knowledge acquisition system (MIKAS), asks the expert for simple explanations for each of the manual actions he/she takes and incorporates the explanations automatically into its knowledge base (KB) so that the system will perform these manually conducted actions automatically at the next occasion. We present MIKAS and discuss the results of our case study. While still being a prototype, the senior clinical dietitian involved in our evaluation studies judges the approach to have considerable potential to improve the daily routine of hospital dietitians as well as to improve the average quality of the dietary advice given to patients within the limited available time for dietary consultations. Our approach opens up a new avenue towards building highly specialised CBR systems in a more cost-effective way. Hence, our approach promises to allow a significantly more widespread development and practical deployment of CBR systems in a large variety of application domains including many medical applications.     

The development of a decision support system for diagnosing nasal allergy.

This paper deals with the problem of improving the capability of the medical decision support system (MDSS) for diagnosing nasal allergy by integrating the previously developed expert system with the neural network approach. Three knowledge acquisition methods were used to develop the expert system: statistical, rule-based, and the combined approach. Among the three, a combined approach showed the best prediction rate based on discriminant analysis. Using the results of a combined approach as input values, the neural network was developed using back-propagation method. Unlike the expert system, the neural network system provides the resulting allergy status in probabilistic terms. Managerial as well as legal issues were also discussed in this paper.     

Design and implementation of a web-based HL7 message generation and validation system

Health level 7 (HL7) is the standard of electronic data interchange in the health domain. We have developed a web-based message generation and validation system for testing the message format of the data exchange among hospitals and health organizations. Compared with other existing ones, this system has incorporated several novel functions that optimize medical data exchange and helps medical students in learning HL7 messages. When receiving HL7 message from another system with the hypertext transmission protocol or accepting an uploaded HL7 message file, the system shows the validation result through a web browser. In this platform, users may input and edit medical data on-line to test and generate standard HL7 messages. The system supports various data formats and is capable of transforming HL7 messages between the standard delimiter format and the extensible markup language format. This system has been successfully passed our system evaluation among 139 student users for HL7 training. Most of the users agreed that the system is helpful for medical data exchange.     

Real-time digital-filter-based data-acquisition system for the detection of neural signals

A data-acquisttion system has been built which performs real-time digital finite-impulse-response filtering to aid in the detection of neural signals. The system acts as an intelligent peripheral to a host laboratory computer, Digital filtering is done by a special-purpose LSI signal-processing chip, while the system's controller is a standard microprocessor, The system is programmable, permitting many acquisition modes to be exectuted, and can be replicated to create a multiple-channel system. A typical sampling rate is 20 kHz; maximum rates depend on the acquisition mode. Significant data compression can be achieved using the system resulting in longer permissible experimental recordings.     

Patient-directed intelligent and interactive computer medical history-gathering systems: a utility and feasibility study in the emergency department

INTRODUCTION: Patients can be used as a resource to enter their own pertinent medical information. This study will evaluate the feasibility of an intelligent computer medical history-taking device directed at patients in the emergency department (ED). METHODS: Two of the authors (MB, RE) developed an expert system that can take patient-directed medical histories. Patients interacted with the computer in the ED waiting room while it gathered a medical history based on chief complaint (CC). A survey was completed post history. A sub-study assessed the computer's ability to take an adequate history for an index CC. We compared the computer and emergency physician histories for the presence or absence of important historical elements. RESULTS: Sixty-seven patients used the interactive computer system. The mean time to complete the history was 5 min and 32s +/- 1 min and 21s. The patient response rate was 97%. Over 83% felt that the computer was very easy to use and over 92% would very much use the computer again. A total of 15 patients with abdominal pain (index CC) were evaluated for the sub-study. The computer history asked 90+/-7%, and the emergency physician asked 55+/-18%, of the important historical elements. These groups were statistically different with a p-value of <0.00001. CONCLUSION: This feasibility study has shown that the computer history-taking device is well accepted by patients and that such a system can be integrated into the normal process of patient triage without delaying patient care. Such a system can serve as an initial mode for documentation and data acquisition directly from the patient.