Intelligent Assistance Systems Research Articles

Intelligent wireless tele-FES walking assistant system for foot drop patients

Online detection and removal of eye blink (EB) artifacts from electroencephalogram (EEG) would be very useful in medical diagnosis and brain computer interface (BCI). In this work, approaches that combine unsupervised eyeblink artifact detection with empirical mode decomposition (EMD), and canonical correlation analysis (CCA), are proposed to automatically identify eyeblink artifacts and remove them in an online manner. First eyeblink artifact regions are automatically identified and an eyeblink artifact template is extracted via EMD, which incorporates an alternate interpolation technique, the Akima spline interpolation. The removal of eyeblink artifact components relies on the elimination of EEG canonical components obtained through CCA, based on cross correlation with the extracted eyeblink artifact template. The proposed algorithm is evaluated and analyzed with respect to its ability in removing eyeblink artifacts and retaining neural information of the EEG signals. Analysis proved that the proposed algorithm, FastEMD–CCA, is efficacious in eyeblink artifact removal with an average accuracy, sensitivity, specificity and error rate of 97.9%, 97.65%, 99.22% and 2.1% respectively. The algorithm is able to clean and remove eyeblink artifacts from a 14-channel EEG of length 1 s, at an average time of 63 ms. This makes it a feasible solution for applications requiring online removal of eyeblink artifacts.

A fuzzy-rough approach for the maintenance of distributed case-based reasoning systems

Case-based reasoning (CBR) means reasoning from prior examples and it has considerable potential for building intelligent assistant system for the World Wide Web. In order to develop successful Web-based CBR systems, we need to select a set of representative cases for the client side case-base such that this thin client is competence in problem solving. This paper proposes a fuzzy-rough method of selecting cases for such a distributed CBR system, i.e., a thin client system (a smaller case-base with rules) connected to a comparatively more powerful server system (the entire original case-base). The methodology is mainly based on the idea that an original case-base can be transformed into a smaller case-base together with a group of fuzzy adaptation rules, which could be generated using our fuzzy-rough approach. As a result, the smaller case-base with a group of fuzzy rules will almost have the same problem coverage as the entire original case-base. The method proposed in this paper, consists of four steps. First of all, an approach of learning feature weights automatically is used to evaluate the importance of different features in a given case-base. Secondly, clustering of cases is carried out to identify different concepts in the case-base using the acquired feature weights. Thirdly, fuzzy adaptation rules are mined for each concept using a fuzzy-rough method. Finally, a selection strategy which based on the concepts of case coverage and reachability is used to select representative cases. The effectiveness of our method is demonstrated experimentally using some testing data in the travel domain.

Focusing on context in human-centered computing

The author has developed a context-based paradigm for intelligent assistant systems from our experience in real-world applications. He concentrates on a system for traffic control (SART, Systeme d'Aide a la Regulation du Trafic). It supports operators who monitor a subway line and solve problems when they occur.

Smart Cars

This article focuses on features and benefits of intelligent driver assistance systems. A combination of radar and vision systems helps a driver to better sense his/her crash envelope. Using a highway simulation model, research teams have found motorists tending to overcompensate for slowing traffic ahead. The model indicated that 10 percent of the cars fitted with driver assistance would reduce the problem by eliminating excessive braking. Twenty percent of vehicles using such systems would eliminate traffic jams altogether. Delphi aims its roll control system specifically at topple-prone SUVs. Active controls eliminate body roll in corners and during evasive maneuvers. A semi-active version removes the performance compromises that afflict dual-purpose, on-/off-road vehicles. Assist Ware Technology Inc., Wexford, PA, builds an alertness aid that combines lane position monitoring with a road-departure warning. A small video camera watches the road ahead from the dashboard. Any weaving or drifting off track triggers the alarm.

Operational Knowledge Representation for Practical Decision-Making

For the design of an intelligent assistant system aimed at supporting operators' decision in subway control, we modeled operators' activity and know-how. As a result, we introduce the notion of a...

Usability criteria for intelligent driver assistance systems

Increasing numbers of intelligent driver assistance systems are now being installed in motor vehicles to support drivers. In order to ensure that the stress reduction benefits obtained from these systems are not nullified or even outweighed by new stresses at the vehicle's man-machine interfaces, the systems' control concepts must be designed to high ergonomic standards. This review seeks to identify design weaknesses in assistance systems by presenting criteria that must, on the one hand, be observed when designing the control concept of a new assistance system and, on the other hand, be applied when assessing the man-machine interfaces of assistance systems already installed in a vehicle. Currently available and future driver assistance systems are evaluated against recognized usability criteria, and their weak points are discussed.

The development of driver assistance systems following usability criteria

Increasing numbers of intelligent driver assistance systems are now being installed in motor vehicles to support drivers. In order to ensure that the stress reduction benefits obtained from these systems are not nullified or even outweighed by new stresses at the vehicle's man-machine interfaces, the systems' control concepts must be designed to high ergonomic standards. This paper seeks to identify design weaknesses in assistance systems by presenting criteria that must, on the one hand, be observed when designing the control concept of a new assistance system and, on the other hand, be applied when assessing the man-machine interfaces of assistance systems already installed in a vehicle.

Web search using a genetic algorithm

Webnaut is an intelligent agent system that uses a genetic algorithm to collect and recommend Web pages. A feedback mechanism adapts to user interests as they evolve. The authors first describe intelligent assistant systems in general and then present the Webnaut architecture, its learning agent, and the genetic algorithm. They conclude with results from two preliminary experiments that tested the accuracy and adaptability of the learning agent.

Towards Human-Centred Intelligent Systems — The Intelligent Assistant

In this paper, we describe some abstract features of human/machine interaction systems that are required for the production of intelligent behaviour. We introduce a subset of intelligent systems called human-centered intelligent systems (HCIS) and argue that such systems must be autonomous, robust and adaptive in order to be intelligent. We also propose soft computing as a promising new technique that can be used to build HCIS, and present examples where this is already being done. The paper defines flexibility to be a combination of the often-conflicting requirements of robustness and adaptability, and based on this we claim that the right balance between these two features is necessary to achieve intelligent behaviour.We describe the intelligent assistant (IA) system and its various components which automatically perform helpful tasks for its user, so as to enable the user to improve productivity. These tasks include time, information and communication management. Time management involves planning and scheduling, decision making and learning user habits. Information management involves information seeking and filtering, information fusion, decision making and learning user preferences. Communication management involves recognising user behaviour and learning user priorities. All these tasks depend on many factors including the type of activity, its originator, the mood of the user, past experience, and the priority of the task. The IA uses a multimodal interface with conventional interfaces such as keyboard and mouse enhanced to include vision, speech and natural language processing. The inclusion of such extra modalities extends the capabilities of existing systems at the cost of introducing extra complexity. The IA is 'smart' because it has the knowledge about tasks and the capability to learn and adapt to new interactions with its user and with other systems.

USCSH: An Active Intelligent Assistance System

This paper describes the knowledge sources and methods of knowledge acquisition for USCSH (University of South Carolina SHell). USCSH is an active intelligent assistance system for Unix. The system operates in two modes, the active mode and the intelligent mode. In the active mode USCSH monitors the user's interactions with the system, and at appropriate times makes suggestions on how the user may better utilize the system to perform tasks. In the intelligent mode the system accepts questions in natural language and responds to them, taking into consideration the ability of the user and the context of the question.

The role of explanations in an intelligent assistant system

This paper sets out to illustrate the importance of transparency within software support systems and in particular for those intelligent assistant systems performing complex industrial design tasks. Such transparency (with the meaning ‘clear’ or ‘easy to understand’) can be achieved by two distinct strategies that complement each other: 1. (i) The design of intelligible systems that would avoid the need for in depth explanation. 2. (ii) The flexible generation of those definitions or aspects of the system or domain that remain ambiguous. The paper illustrates that for the generation of useful explanations going beyond a simple justification of a problem solving trace, specific explanatory knowledge must be acquired. By itself the problem solving techniques are not sufficient. A new approach to acquire and model explanatory knowledge for software systems is presented. The new four-layer explanatory model can be used to determine the range of explanation suitable for a given systems domain. This model has been successfully used for the development of an explanation component for the design assistant system ASSIST that supports factory layout planning, in itself a complex design task.

Different ways to support intelligent assistant systems by use of machine learning methods

Intelligent assistant systems provide an adequate organization of human‐computer interaction for complex problem solving. These knowledge‐based systems are characterized by a cooperative problem‐solving procedure. User and system cooperate intensively to produce the aimed result. Machine learning methods can provide significant support for assistant systems. In this article, it is pointed out how assistant systems can be supported in various ways. For instance, machine learning methods can extend, revise, optimize, and adapt the knowledge base of an assistant system. In this way, they can contribute to the utility and maintainability of an intelligent assistant system. They can also increase the flexibility and effectiveness of human‐computer interaction. The learning apprentice system COSIMA is presented which acquires knowledge about single problem‐solving steps from observation of the user. Production rules for floorplanning, a sub‐task of VLSI design, are acquired and refined cooperatively by different learning strategies. An extended abstract of this article already appeared in the proceedings of the 5th International Conference on Human‐Computer Interaction, Tokyo, 1995 (Herrmann, 1995).

Concept and Relization of Intelligent Medical Assistance System for Operation of the Active Catheter.

Recently, the catheter has been down-sized and has become functional, and it has begun to be used for practical medical operations. Nowadays intravascular neurosurgery using the catheter is carried out for an aneurysm or cerebral thrombosis. However, it is quite difficult to select the direction at a divergence point because brain blood vessels are narrow and complex. For this reason, an active catheter whose tip can be actuated by a microactuator is studied and developed. Even if the active catheter is realized, its control is very difficult. Therefore we investigate an assistance system for the doctor operating the active catheter. In this paper, we propose the concept of an intelligent medical assistance system for operation of the active catheter. To realize this medical assistance system, we built a prototype of a virtual simulator system consisting of an active joystick, which has force feedback capability, and a 3D-computer graphics display. Using this simulator system, we evaluated the effectiveness of the proposed visual and operation assistance methods through extensive experiments.

Human Manipulative Skill Analysis and Acquisition for the Intelligent Assisting System

In this paper we propose a new forthcoming research topic the Intelligent Assisting System IAS. Using this system we want to approach the identification and analysis of human manipulation skills to be used for intelligent human operator assistance. A manipulation skill data base enables the IAS to perform complex manipulations on the motion control level. Through repeated interaction with the operator for unknown environment states, the manipulation skills in the data base can be increased on-line. A model for manipulation skill based 011 the grip transformation matrix is proposed, which describes the transformation between the object trajectory and contact conditions. The dynamic behavior of the grip transform is regarded as the essence of the performed manipulation skill. We describe the experimental system setup of a skill acquisition and transfer system as a first approach to the IAS and some results confirming the calibration method of the developed sensor glove. A simple manipulation example shows the feasibility of the proposed manipulation skill model. Further this paper defines a control algorithm realizing object task trajectories and its feasibility is shown by simulation.

Integrated human-machine intelligence

This paper presents an artificial intelligence approach to integrated human-machine intelligence in space systems. It discusses the motivations for Intelligent Assistant Systems in both nominal and abnormal situations. The problem of constructing procedures is shown to be a very critical issue. In particular, keeping procedural experience in both design and operation is critical. We suggest what artificial intelligence can offer in this direction. Some crucial problems induced by this approach are discussed in detail. Finally, we analyze the various roles that would be shared by both astronauts, ground operators, and the intelligent assistant system.

Skill acquisition system for the intelligent assisting system_IAS

_In this paper we propose a new forthcoming research topic, the Intelligent Assisting System_ IAS. Using this system, we are approaching the identification and analysis of human manipulation skills to be used for intelligent human operator assistance. A manipulation skill database enables the IAS to perform complex manipulations at the motion control level. Through repeated interaction with the operator for unknown environment states, the manipulation skills in the database can be increased on-line. A model for manipulation skill based on the grip transformation matrix is proposed, which describes the transformation between the object trajectory and the contact conditions. The dynamic behaviour of the grip transform is regarded as the essence of the performed manipulation skill. We describe the experimental system set-up of a skill acquisition and transfer system as a first approach to the IAS. A simple example of manipulation shows the feasibility of the proposed manipulation skill model. Furthermore, th...

Artificial intelligence approach in analysis of DNA sequences

We present an approach for designing a knowledge-based system, called Sequence Acquisition In Context (SAIC), that will be able to cooperate with a biologist in the analysis of DNA sequences. The main task of the system is the acquisition of the expert knowledge that the biologist uses for solving ambiguities from gel autoradiograms, with the aim of re-using it later for solving similar ambiguities. The various types of expert knowledge constitute what we call the contextual knowledge of the sequence analysis. Contextual knowledge deals with the unavoidable problems that are common in the study of the living material ( eg noise on data, difficulties of observations). Indeed, the analysis of DNA sequences from autoradiograms belongs to an emerging and promising area of investigation, namely reasoning with images. The SAIC project is developed in a theoretical framework that is shared with other applications. Not all tasks have the same importance in each application. We use this observation for designing an intelligent assistant system with three applications. In the SAIC project, we focus on knowledge acquisition, human-computer interaction and explanation. The project will benefit research in the two other applications. We also discuss our SAIC project in the context of large international projects that aim to re-use and share knowledge in a repository.

An overview of on-line assistance: from on-line documentation to intelligent help and training

AbstractAn important aspect of any interactive computer system is its ease of use. On-line assistance is a major contributor to software usability. Conventional on-line assistance includes on-line documentation, or keyword access to textual help descriptions. More sophisticated on-line assistance includes intelligent help which provides immediate assistance for a specific problem, and intelligent training whose main goal is to support the user in learning about the system. These contemporary forms of intelligent assistance represent knowledge about the particular application, the user and the particular tasks the user is to perform. In addition, they possess inferencing capabilities to model the individual user's goals, plans, intentions and knowledge. This paper provides an overview of on-line assistance research, from empirical studies that attempt to determine the nature of effective assistance, to the design of intelligent on-line assistance systems capable of tailoring the assistance to the individual user. For readers interested in more details, recommendations for further reading in the related areas of advice-giving and intelligent help, intelligent user interfaces, critiquing, intelligent tutoring systems, and on-line documentation and hypertext are given.

Integrated human-machine intelligence in space systems

This paper presents an artificial intelligence approach to integrated human-machine intelligence in space systems. It discusses the motivations for Intelligent Assistant Systems in both nominal and abnormal situations. The problem of constructing procedures is shown to be a very critical issue. In particular, keeping procedural experience in both design and operation is critical. We suggest what artificial intelligence can offer in this direction. Some crucial problems induced by this approach are discussed in detail. Finally, we analyze the various roles that would be shared by both astronauts, ground operators, and the intelligent assistant system.

Cognitive modelling of fighter aircraft process control: a step towards an intelligent on-board assistance system

A baseline description of a cognitive model that has been successfully implemented on high-speed, low-altitude navigation fighter plane missions illustrates designs for an intelligent assistance system for future French combat aircraft. The outcomes are based on several empirical studies. Task complexity (risk, uncertainty, time pressure) is extreme and provides a prototypical example of a rapid process control situation which requires specific assistance problems. The paper is divided into three sections: 1. 1. A general review discusses implications of the specific requirements for coupling an intelligent assistance system to pilots. Special attention is paid to understanding and coherence of the aid, both of which directly influence the nature of the system. 2. 2. An empirical analysis of missions carried out by novice and experienced pilots forms the basis for a cognitive model of in-flight navigation problem solving. Because of time pressure and risk, pilots have as much difficulty applying solutions as diagnosing problems. Pilots tend to develop a sophisticated model of the situation in order to anticipate problems and actively avoid or minimize problem difficulty. In contrast, poor solutions tend to be found for unexpected problems and generally result in renunciation of the mission and/or crash. 3. 3. The cognitive model described above serves as the basis for a computer cognitive model for flying high-speed, low-altitude navigation missions. The model splits functional knowledge into two levels: the local level deals with sub-goals and short-term activities; the global level deals with mission objectives and handles medium- and long-term activities. A resource manager coordinates the two levels. The program uses an Al actor programming style. This computer cognitive model serves to develop an intelligent navigation assistance system which can function as an automaton or as a tactical support system.