An assistive lower limb exoskeleton for people with neurological gait disorders.

Lower limb exoskeletons have already proven the capability to give back mobility to people suffering from spinal cord injury (SCI). Other important populations such as people with multiple sclerosis or muscular dystrophy, frail elderly and stroke victims, suffer from severe gait impairments and could benefit from similar technology. The work presented in the current paper describes a novel design of a 6-actuated degrees of freedom (DOFs) assistive lower limb exoskeleton for people with moderate mobility impairments. The electrical actuators are all remotely located on the back of the user for a more compact design with high dynamics. Cable driven solutions are used to transmit the flexion/extension of the hip and knee joints, while a powerful ballscrew carries out the hip adduction/abduction. The design of this exoskeleton, named AUTONOMYO, follows the key specifications of being highly back-drivable and able to perform dynamic motions at low energy consumption. AUTONOMYO is capable to assist the user's balance by providing complementary torques at the hip and the knee. Results show that the projected level of assistance for sit-to-stand transition varies from 50% to 100% in function of the user's bodyweight and height while higher level of assistance are reached for walking and stairs climbing activities.

Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.

OBJECTIVE: The authors consider the problem of exact string pattern matching using algorithms that do not require any preprocessing. To choose the most appropriate algorithm, distinctive features of the medical language must be taken into account. The characteristics of medical language are emphasized in this regard, the best algorithm of those reviewed is proposed, and detailed evaluations of time complexity for processing medical texts are provided. DESIGN: The authors first illustrate and discuss the techniques of various string pattern-matching algorithms. Next, the source code and the behavior of representative exact string pattern-matching algorithms are presented in a comprehensive manner to promote their implementation. Detailed explanations of the use of various techniques to improve performance are given. MEASUREMENTS: Real-time measures of time complexity with English medical texts are presented. They lead to results distinct from those found in the computer science literature, which are typically computed with normally distributed texts. RESULTS: The Boyer-Moore-Horspool algorithm achieves the best overall results when used with medical texts. This algorithm usually performs at least twice as fast as the other algorithms tested. CONCLUSION: The time performance of exact string pattern matching can be greatly improved if an efficient algorithm is used. Considering the growing amount of text handled in the electronic patient record, it is worth implementing this efficient algorithm.

Evaluation of a command-line parser-based order entry pathway for the Department of Veterans Affairs electronic patient record.

OBJECTIVE: To improve and simplify electronic order entry in an existing electronic patient record, the authors developed an alternative system for entering orders, which is based on a command- interface using robust and simple natural-language techniques. DESIGN: The authors conducted a randomized evaluation of the new entry pathway, measuring time to complete a standard set of orders, and users' satisfaction measured by questionnaire. A group of 16 physician volunteers from the staff of the Department of Veterans Affairs Puget Sound Health Care System-Seattle Division participated in the evaluation. RESULTS: Thirteen of the 16 physicians (81%) were able to enter medical orders more quickly using the natural-language-based entry system than the standard graphical user interface that uses menus and dialogs (mean time spared, 16.06 +/- 4.52 minutes; P=0.029). Compared with the graphical user interface, the command--based pathway was perceived as easier to learn (P<0.01), was considered easier to use and faster (P<0.01), and was rated better overall (P<0.05). CONCLUSION: Physicians found the command- interface easier to learn and faster to use than the usual menu-driven system. The major advantage of the system is that it combines an intuitive graphical user interface with the power and speed of a natural-language analyzer.

Medical dictionaries for patient encoding systems: a methodology.

Medical language is highly compositional and makes extensive use of common roots, especially Latino-Greek roots. Besides words devoted to common sense, medical language presents some typical characteristics, especially on morphological and semantic aspects of word formation. Morphological decomposition and identification precedes semantic analysis. It is only when these two prerequisites are fulfilled that an attempt to grasp the meaning of a whole expression is made possible. The main aim of the proposed approach is that of coping with 'the lack of coverage of the medical lexical knowledge', in order to help physicians find the correct international classification for diseases (ICD) codes for a written diagnosis. The proposed methodology allows the development of a powerful dynamic dictionary dedicated to natural language processing in the field of diagnoses and narrative procedures. It describes the design of an analyser that can profit from a dictionary. The methods used have proved to be efficient for various classifications, s well as for multiple languages, as the system presently supports French, German, English and Dutch for ICD-9 and ICD-10 classifications.

Natural language processing and semantical representation of medical texts.

For medical records, the challenge for the present decade is Natural Language Processing (NLP) of texts, and the construction of an adequate Knowledge Representation. This article describes the components of an NLP system, which is currently being developed in the Geneva Hospital, and within the European Community's AIM programme. They are: a Natural Language Analyser, a Conceptual Graphs Builder, a Data Base Storage component, a Query Processor, a Natural Language Generator and, in addition, a Translator, a Diagnosis Encoding System and a Literature Indexing System. Taking advantage of a closed domain of knowledge, defined around a medical specialty, a method called proximity processing has been developed. In this situation no parser of the initial text is needed, and the system is based on semantical information of near words in sentences. The benefits are: easy implementation, portability between languages, robustness towards badly-formed sentences, and a sound representation using conceptual graphs.

Alternative ways for knowledge collection, indexing and robust language retrieval.

Definitions are provided of the key entities in knowledge representation for Natural Language Processing (NLP). Starting from the words, which are the natural components of any sentence, both the role of expressions and the decomposition of words into their parts are emphasized. This leads to the notion of concepts, which are either primitive or composite depending on the model where they are created. The problem of finding the most adequate degree of granularity for a concept is studied. From this reflection on basic Natural Language Processing components, four categories of linguistic knowledge are recognized, that are considered to be the building blocks of a Medical Linguistic Knowledge Base (MLKB). Following on the tracks of a recent experience in building a natural language-based patient encoding browser, a robust method for conceptual indexing and query of medical texts is presented with particular attention to the scheme of knowledge representation.

Modeling concepts in medicine for medical language understanding.

Over the past two decades, the construction of models for medical concept representation and for understanding of the deep meaning of medical narrative texts have been challenging areas of medical informatics research. This review highlights how these two inter-related domains have evolved, emphasizing aspects of medical modeling as a tool for medical language understanding. A representation schema, which balances partially but accurately with complete but complex representations of domain-specific knowledge, must be developed to facilitate language understanding. Representative examples are drawn from two major independent efforts undertaken by the authors: the elaboration and the subsequent adjustment of the RECIT multilingual analyzer to include a robust medical concept model, and the recasting of a frame-based interlingua system, originally developed to map equivalent concepts between controlled clinical vocabularies, to invoke a similar concept model.

Representing clinical narratives using conceptual graphs.

The analysis of medical narratives and the generation of natural language expressions are strongly dependent on the existence of an adequate representation language. Such a language has to be expressive enough in order to handle the complexity of human reasoning in the domain. Sowa's Conceptual Graphs (CG) are an answer, and this paper presents a multilingual implementation, using French, English and German. Current developments demonstrate the feasibility of an approach to natural Language Understanding where semantic aspects are dominant, in contrast to syntax driven methods. The basic idea is to aggregate blocks of words according to semantic compatibility rules, following a method called Proximity Processing. The CG representation is gradually built, starting from single words in a semantic lexicon, to finally give a complete representation of the sentence under the form of a single CG. The process is dependent on specific rules of the medical domain, and for this reason is largely controlled by the declarative knowledge of the medical Linguistic Knowledge Base.

A humanist's legacy in medical informatics: visions and accomplishments of Professor Jean-Raoul Scherrer.

OBJECTIVE: To report about the work of Prof. Jean-Raoul Scherrer, and show how his humanist vision, his medical skills and his scientific background have enabled and shaped the development of medical informatics over the last 30 years. RESULTS: Starting with the mainframe-based patient-centered hospital information system DIOGENE in the 70s, Prof. Scherrer developed, implemented and evolved innovative concepts of man-machine interfaces, distributed and federated environments, leading the way with information systems that obstinately focused on the support of care providers and patients. Through a rigorous design of terminologies and ontologies, the DIOGENE data would then serve as a basis for the development of clinical research, data mining, and lead to innovative natural language processing techniques. In parallel, Prof. Scherrer supported the development of medical image management, ranging from a distributed picture archiving and communication systems (PACS) to molecular imaging of protein electrophoreses. Recognizing the need for improving the quality and trustworthiness of medical information on the Web, Prof. Scherrer created the Health-On-the-Net (HON) foundation. CONCLUSIONS: These achievements, made possible thanks to his visionary mind, deep humanism, creativity, generosity and determination, have made of Prof. Scherrer a true pioneer and leader of the human-centered, patient-oriented application of information technology for improving healthcare.

Reconciling users' needs and formal requirements: issues in developing a reusable ontology for medicine.

A common language, or terminology, for representing what clinicians have said and done is an important requirement for individual clinical systems, and it is a pre-requisite for integrating disparate applications in a distributed telematic healthcare environment. Formal representations based on description logics or closely related formalisms are increasingly used for representing medical terminologies. GALEN's experience in using one such formalism raises two major issues, as follows: how to make ontologies based on description logics easy to use and understand for both clinicians and applications developers; what features are required of the ontology and description logic if they are to achieve their aims. Based on our experience we put forward four contentions: two relating to each of these two issues, as follows: that natural language generation is essential to make a description logic based ontology accessible to users; that the description logic based ontology should be treated as an "assembly language" and accessed via "intermediate representations" oriented to users and "perspectives" adapting it to specific applications; that independence and reuse are best supported by partitioning the subsumption hierarchy of elementary concepts into orthogonal taxonomies, each of which forms a pure tree in which the branches at each level are disjoint but nonexhaustive subconcepts of the parent concept; that the expressivity of the description logic must include support for transitive relations despite the computational cost, and that this computational cost is acceptable in practice. The authors argue that these features will be necessary, though by no means sufficient, for the development of any large reusable ontology for medicine.

Present and future trends with NLP.

This paper reflects some desiderata on the role of Natural Language Processing (NLP) in the coming years as foreseen in the medical domain. During the Medical Informatics Europe (MIE) conference in 1997, the NLP track was composed by numerous papers on natural language, knowledge representation, nomenclatures and classifications. Indeed, the medical community is looking for solutions for the future which are going to emerge from more powerful desktop and for which the successful softwares of tomorrow are not yet identified. Presently this same community's needs remains unsatisfied with healthcare professionals writing at best their patient medical records in a text processing system. We stand today closer to the typewriter than to any modern solution which could radically transform the treatment of information related to patients. What kind of hurdles are there still in front of us before we reach this new territory?

Evaluating and reducing the effect of data corruption when applying bag of words approaches to medical records.

Unlike journal corpora, which are supposed to be carefully reviewed before being published, the quality of documents in a patient record are often corrupted by mispelled words and conventional graphies or abbreviations. After a survey of the domain, the paper focuses on evaluating the effect of such corruption on an information retrieval (IR) engine. The IR system uses a classical bag of words approach, with stems as representation items and term frequency-inverse document frequency (tf-idf) as weighting schema; we pay special attention to the normalization factor. First results shows that even low corruption levels (3%) do affect retrieval effectiveness (4-7%), whereas higher corruption levels can affect retrieval effectiveness by 25%. Then, we show that the use of an improved automatic spelling correction system, applied on the corrupted collection, can almost restore the retrieval effectiveness of the engine.

Power of expression in the electronic patient record: structured data or narrative text?

This paper presents the authors' experience with the development and use of a document-centered electronic patient record (EPR) in a large teaching hospital. The development of the document-centered EPR began with the formulation of a set of critical hypotheses to facilitate both the continuation of the best medical practice and the implementation and use of the EPR. An alternate and more conventional approach - the data-centered EPR - is compared with the document-centered EPR. Various benefits and pitfalls are discussed. Finally, the choice was to offer both solutions in a tightly linked system. The need for an EPR which combines the document and data centered approaches is a reflection of the more general discussion of what the medical record will be in the future. All too often, the need for structured data conflicts with the need for free texts and the power of expression. It is not easy to evaluate the consequences of this initial decision. However, changing the foundations of the EPR after its implementation is difficult and expensive. Therefore, the selection of the correct orientation in a given hospital requires a broad-based discussion.

Happy birthday DIOGENE: a hospital information system born 20 years ago.

Since its birth in 1978, DIOGENE, the hospital information system of Geneva University Hospital has been constantly evolving, with a major change in 1995, when migrating from a centralized to an open distributed architecture. For a few years, the hospital had to face health policy revolution with both economical constraints and opening of the healthcare network. The hospital information system DIOGENE plays a significant role by integrating four axes of knowledge: medico-economical context for better understanding and influencing resources consumption; the whole set of patient reports and documents (reports, encoded summaries, clinical findings, images, lab data, etc.), patient-dependent knowledge, in a vision integrating time and space; external knowledge bases such as Medline (patient-independent knowledge); integration of these patient-dependent and independent knowledge in a case-based reasoning format, providing on the physician desktop all relevant information for helping him to take the most appropriate adequate decision.

Natural language generation of surgical procedures.

A number of compositional Medical Concept Representation systems are being developed. Although these provide for a detailed conceptual representation of the underlying information, they have to be translated back to natural language for used by end-users and applications. The GALEN programme has been developing one such representation and we report here on a tool developed to generate natural language phrases from the GALEN conceptual representations. This tool can be adapted to different source modelling schemes and to different destination languages or sublanguages of a domain. It is based on a multilingual approach to natural language generation, realised through a clean separation of the domain model from the linguistic model and their link by well defined structures. Specific knowledge structures and operations have been developed for bridging between the modelling 'style' of the conceptual representation and natural language. Using the example of the scheme developed for modelling surgical operative procedures within the GALEN-IN-USE project, we show how the generator is adapted to such a scheme. The basic characteristics of the surgical procedures scheme are presented together with the basic principles of the generation tool. Using worked examples, we discuss the transformation operations which change the initial source representation into a form which can more directly be translated to a given natural language. In particular, the linguistic knowledge which has to be introduced--such as definitions of concepts and relationships is described. We explain the overall generator strategy and how particular transformation operations are triggered by language-dependent and conceptual parameters. Results are shown for generated French phrases corresponding to surgical procedures from the urology domain.

GALEN: a third generation terminology tool to support a multipurpose national coding system for surgical procedures.

Generalised architecture for languages, encyclopedia and nomenclatures in medicine (GALEN) has developed a new generation of terminology tools based on a language independent model describing the semantics and allowing computer processing and multiple reuses as well as natural language understanding systems applications to facilitate the sharing and maintaining of consistent medical knowledge. During the European Union 4 Th. framework program project GALEN-IN-USE and later on within two contracts with the national health authorities we applied the modelling and the tools to the development of a new multipurpose coding system for surgical procedures named CCAM in a minority language country, France. On one hand, we contributed to a language independent knowledge repository and multilingual semantic dictionaries for multicultural Europe. On the other hand, we support the traditional process for creating a new coding system in medicine which is very much labour consuming by artificial intelligence tools using a medically oriented recursive ontology and natural language processing. We used an integrated software named CLAW (for classification workbench) to process French professional medical language rubrics produced by the national colleges of surgeons domain experts into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation, on one hand, we generate with the LNAT natural language generator controlled French natural language to support the finalization of the linguistic labels (first generation) in relation with the meanings of the conceptual system structure. On the other hand, the Claw classification manager proves to be very powerful to retrieve the initial domain experts rubrics list with different categories of concepts (second generation) within a semantic structured representation (third generation) bridge to the electronic patient record detailed terminology.

Natural language processing of medical texts within the HELIOS environment.

A large number of hospital applications are potentially interested in natural language processing since they currently heavily depend on an efficient use of a huge amount of textual information. The need for systems that are able to accept multiple European languages is of paramount interest, as language barriers can be a strong impediment for large-scale communication in Europe, in particular regarding telemedicine. In the context of the AIM project HELIOS, the Natural Language Processing (NLP) component offers a large variety of medical services according to natural language free input. It allows the multilingual analysis of medical texts (currently in English, French and German) and the storage of the meaning of these texts under a deep knowledge representation that can be queried whenever it is needed. In addition, it provides facilities to handle knowledge source embedded into the conceptual typologies and into the dictionaries. This article aims at describing all these functionalities and their integration into the environment of the HELIOS project.

The HELIOS medical software engineering environment.

The aim of the HELIOS project is to create an integrated Software Engineering Environment (SEE) to facilitate the development and maintenance of medical applications. HELIOS is made of a set of software components, communicating through a software bus called the HELIOS Unification Bus. The object oriented paradigm is used both as the basic structure for building the software components and as the methodology for modelling, storing and retrieving the entities and procedures used in an application. Development standards include UNIX as operating system and X Window/MOTIF as windowing environment. One of the target applications for the HELIOS prototype is the development of a multimedia medical workstation as a front end to a hospital information system.

The component-based architecture of the HELIOS medical software engineering environment.

The constitution of highly integrated health information networks and the growth of multimedia technologies raise new challenges for the development of medical applications. We describe in this paper the general architecture of the HELIOS medical software engineering environment devoted to the development and maintenance of multimedia distributed medical applications. HELIOS is made of a set of software components, federated by a communication channel called the HELIOS Unification Bus. The HELIOS kernel includes three main components, the Analysis-Design and Environment, the Object Information System and the Interface Manager. HELIOS services consist in a collection of toolkits providing the necessary facilities to medical application developers. They include Image Related services, a Natural Language Processor, a Decision Support System and Connection services. The project gives special attention to both object-oriented approaches and software re-usability that are considered crucial steps towards the development of more reliable, coherent and integrated applications.

Internet integrated in the daily medical practice within an electronic patient record.

Healthcare enters the information age and professionals are finding an ever-growing role for computers in the daily practice of medicine. However, a number of problematic issues are associated with electronic publications, especially through Internet. Whilst access to any information has been improved, access to specific information has become more and more difficult [1], due to the lack of a general meta-knowledge allowing to structure Internet resources. Physicians have to learn and adapt themselves to computers and Internet, but Internet has to meet the specific requirements of Healthcare. Important issues must therefore be addressed to allow a real and daily use of Internet in the medical practice. The paper discusses most of these issues and proposes a solution developed at the University Hospital of Geneva that integrates an Electronic Patient Record with Internet, without compromises on security or on performances and that runs on standard PCs'.