Interactions between human–human multi-threaded dialogues and driving

In-car devices with speech user interfaces are proliferating. How can we build these interfaces such that they allow human–computer interactions with multiple devices to overlap in time, but without interfering with the driving task? We suggest that interface design can be inspired by the way people deal with this problem in human–human dialogues and propose discovering human dialogue behaviors of interest through experiments. In this paper, we discuss how to design an appropriate human–human dialogue scenario for such experiments. We also report on one human–human experiment, in terms of the dialogue behaviors found, and impact on the verbal tasks and on driving. We also offer design considerations based on the results of the study.     

From human – machine interaction to human – machine cooperation

Since the 1960s, the rapid growth of information systems has led to the wide development of research on human—computer interaction (HCI) that aims at the designing of human-computer interfaces presenting ergonomic properties, such as friendliness, usability, transparency, etc. Various work situations have been covered—clerical work, computer programming, design, etc. However, they were mainly static in the sense that the user fully controls the computer. More recently, public and private organizations have engaged themselves in the enterprise of managing more and more complex and coupled systems by the means of automation. Modern machines not only process information, but also act on dynamic situations as humans have done in the past, managing stock exchange, industrial plants, aircraft, etc. These dynamic situations are not fully controlled and are affected by uncertain factors. Hence, degrees of freedom must be maintained to allow the humans and the machine to adapt to unforeseen contingencies. A human-machine cooperation (HMC) approach is necessary to address the new stakes introduced by this trend. This paper describes the possible improvement of HCI by HMC, the need for a new conception of function allocation between humans and machines, and the main problems encountered within the new forms of human—machine relationship. It proposes a conceptual framework to study HMC from a cognitive point of view in highly dynamic situations like aircraft piloting or air-traffic control, and concludes on the design of ‘cooperative’ machines.     

Robot adaptation to human physical fatigue in human–robot co-manipulation

In this paper, we propose a novel method for human–robot collaboration, where the robot physical behaviour is adapted online to the human motor fatigue. The robot starts as a follower and imitates the human. As the collaborative task is performed under the human lead, the robot gradually learns the parameters and trajectories related to the task execution. In the meantime, the robot monitors the human fatigue during the task production. When a predefined level of fatigue is indicated, the robot uses the learnt skill to take over physically demanding aspects of the task and lets the human recover some of the strength. The human remains present to perform aspects of collaborative task that the robot cannot fully take over and maintains the overall supervision. The robot adaptation system is based on the Dynamical Movement Primitives, Locally Weighted Regression and Adaptive Frequency Oscillators. The estimation of the human motor fatigue is carried out using a proposed online model, which is based on the human muscle activity measured by the electromyography. We demonstrate the proposed approach with experiments on real-world co-manipulation tasks: material sawing and surface polishing.     

Impact of two types of partner,perceived or actual,in human–human and human–agent interaction

Participants engaged in the Prisoner’s dilemma game with a partner through a computer terminal. We define two types of partner: a perceived partner and an actual partner, and manipulated the two factors independently. A perceived partner means a partner with whom participants imagined themselves to be interacting; instruction given by an experimenter controls the image of the perceived partner. An actual partner can change its behavior. In one scenario participants actually interacted with a human partner, in another scenario their partner was either a mostly cooperating computer agent or a mostly defecting computer agent. Three experiments were performed. The result suggested that the participants’ selection behavior was largely influenced by the instruction given about the partner by the experimenter and not influenced by the partner’s actual behavior. The analysis of the participants’ impressions of the partner showed that the effect of instruction about the partner disappeared. Individual likeability for a partner was very influenced by the partner’s behavior; as the participants incurred more defect actions from the partner, individual likeability for the partner decreased. On the other hand, social likeability for a partner was not so influenced by the partner’s behavior, but rather related to the participants’ own behavior. The participants who made more defect actions rated their partner’s social likeability lower.     

Improved stability of haptic human–robot interfaces using measurement of human arm stiffness

Necessary physical contact between an operator and a force feedback haptic device creates a coupled system consisting of human and machine. This contact, combined with the natural human tendency to increase arm stiffness to attempt to stabilize its motion, can reduce the stability of the system. This paper proposes a method to increase stability on demand while maintaining speed and performance. Operator arm stiffness is not directly measurable, so controllers cannot typically account for this issue. The causes of arm end-point stiffness are examined as related to system stability, and a method for estimating changes in arm stiffness based on arm muscle activity was designed to provide a robotic controller with additional information about the operator. This was accomplished using electromyograms (EMGs) to measure muscle activities and estimating the level of arm stiffness, which was used to adjust the dynamic characteristics of an impedance controller. To support this design, the correlation between EMGs and arm stiffness was validated experimentally. Further experiments characterized the effects of the designed system on operator performance. This showed increased stability and faster, more accurate movements using the compensating system. Such a system could be used in many applications, including force assisting devices in industrial facilities.     

Generating phenotypical erroneous human behavior to evaluate human–automation interaction using model checking

Breakdowns in complex systems often occur as a result of system elements interacting in unanticipated ways. In systems with human operators, human–automation interaction associated with both normative and erroneous human behavior can contribute to such failures. Model-driven design and analysis techniques provide engineers with formal methods tools and techniques capable of evaluating how human behavior can contribute to system failures. This paper presents a novel method for automatically generating task analytic models encompassing both normative and erroneous human behavior from normative task models. The generated erroneous behavior is capable of replicating Hollnagel's zero-order phenotypes of erroneous action for omissions, jumps, repetitions, and intrusions. Multiple phenotypical acts can occur in sequence, thus allowing for the generation of higher order phenotypes. The task behavior model pattern capable of generating erroneous behavior can be integrated into a formal system model so that system safety properties can be formally verified with a model checker. This allows analysts to prove that a human–automation interactive system (as represented by the model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. We present benchmarks related to the size of the statespace and verification time of models to show how the erroneous human behavior generation process scales. We demonstrate the method with a case study: the operation of a radiation therapy machine. A potential problem resulting from a generated erroneous human action is discovered. A design intervention is presented which prevents this problem from occurring. We discuss how our method could be used to evaluate larger applications and recommend future paths of development.     

Lessons from molecular modeling human α-l-iduronidase

Human α-l-iduronidase (IDUA) is a member of glycoside hydrolase family and is involved in the catabolism of glycosaminoglycans (GAGs), heparan sulfate (HS) and dermatan sulfate (DS). Mutations in this enzyme are responsible for mucopolysaccharidosis I (MPS I), an inherited lysosomal storage disorder. Despite great interest in determining and studying this enzyme structure, the lack of a high identity to templates and other technical issues have challenged both bioinformaticians and crystallographers, until the recent publication of an IDUA crystal structure (PDB: 4JXP). In the present work, four alternative IDUA models, generated and evaluated prior to crystallographic determination, were compared to the 4JXP structure. A combined analysis using several viability assessment tools and molecular dynamics simulations highlights the strengths and limitations of different comparative modeling protocols, all of which are based on the same low identity template (only 22%). Incorrect alignment between the target and template was confirmed to be a major bottleneck in homology modeling, regardless of the modeling software used. Moreover, secondary structure analysis during a 50 ns simulation seems to be useful for indicating alignment errors and structural instabilities. The best model was achieved through the combined use of Phyre 2 and Modeller, suggesting the use of this protocol for the modeling of other proteins that still lack high identity templates.     

Community computing as human ‐ computer interaction

There is too little engagement between community computing and human - computer interaction. In the future there should be more. Better integrating community computing and human - computer interaction can help to make HCI richer and more comprehensive, conceptually and methodologically. It can help HCI to have more of an impact on society and on everyday collective life. Six examples are briefly discussed.     

Advance human–machine interface automatic evaluation

The need for accessibility evaluation tools is motivated by several endogenous and exogenous reasons coming from the end user (the designer and the developer) and companies releasing information systems. Existing evaluation tools mainly concentrate on examining the code of Web pages: Web pages more and more frequently contain non-HTML parts that entirely escape from being treated by existing techniques. This is the case of the advanced human–machine interface (AHMI), a piece of software programmed in C/C++, used for controlling the advanced flight management system in the aircraft cockpit. Studying this new user interface (UI) requires a structured approach to evaluate and validate AHMI designs. The goal in this work is to develop an evaluation tool to automate the process of evaluating the AHMI. The method addresses: support of multiple bases of guidelines (accessibility or usability or both) on-demand (partial or total evaluation), with different levels of details (a presentation for developers and for those responsible for certifying accessibility). The method goes a step toward the automatic evaluation of UI containing non-HTML parts.     

Human factors/ergonomics as a systems discipline? “The human use of human beings” revisited

Discussions of the possible future of Human factors/ergonomics (HFE) usually take the past for granted in the sense that the future of HFE is assumed to be more of the same. This paper argues that the nature of work in the early 2010s is so different from the nature of work when HFE was formulated 60–70 years ago that a critical reassessment of the basis for HFE is needed. If HFE should be a systems discipline, it should be a soft systems rather than a hard systems discipline. It is not enough for HFE to seek to improve performance and well-being through systems design, since any change to the work environment in principle alters the very basis for the change. Instead HFE should try to anticipate how the nature of work will change so that it can both foresee what work will be and propose what work should be.     

Information Security management: A human challenge?

This paper considers to what extent the management of Information Security is a human challenge. It suggests that the human challenge lies in accepting that individuals in the organisation have not only an identity conferred by their role but also a personal and social identity that they bring with them to work. The challenge that faces organisations is to manage this while trying to achieve the optimum configuration of resources in order to meet business objectives. The paper considers the challenges for Information Security from an organisational perspective and develops an argument that builds on research from the fields of management and organisational behaviour. It concludes that the human challenge of Information Security management has largely been neglected and suggests that to address the issue we need to look at the skills needed to change organisational culture, the identity of the Information Security Manager and effective communication between Information Security Managers, end users and Senior Managers.     

Analyzing soft tissue stiffness of human upper arms during physical dynamic and quasi-static impacts in human–machine interaction

Knowledge of the changes in the behavior of human soft tissue stiffness during physical impact in human–machine interaction (HMI) plays a vital role in the development of biofidelity testing devices such as a human dummy. These testing devices are widely applied as an effective means to validate the safety of machinery during dynamic or static contact with humans in HMI. In this study, we assess changes in soft tissue stiffness in the upper arm of individuals under both dynamic (0.7 and 0.25 m/s) and quasi-static (QS) impacts under a constrained contact condition. Three impactor shapes (cylindrical, cubic, and spherical) are used in this study. Impact experiments are conducted using impactors attached to a pendulum. The soft-tissue displacement is determined using an ultrasound device. The impact force-displacement curves illustrate the nonlinear behavior of the soft tissue stiffness under both dynamic and QS impacts. By utilizing the “Linear Mixed Model” statistical analysis, we found that changes in the impact velocity significantly influenced the changes in the nonlinear behavior of soft tissue stiffness while there was no significant effect of the changes in the impactor shape on the nonlinear behavior of the soft tissue stiffness. Additionally, we revealed that the changes in the soft tissue stiffness are influenced by the size of the contact area. Moreover, we demonstrated a range of changes in soft tissue stiffness for different impact velocities, which provide valuable information for developing future validation test devices in HMI, such as the design and evaluation of dummy skin.     

ETSI’s human factors contribution to eEurope

This article describes the most recent development in the European telecommunications industry from the end-user perspective, considering generic user interface elements for interaction with mobile communication systems, as described in a series of European Telecommunication Standards Institute (ETSI) deliverables. It also reports the results of work from recent and ongoing activities in the ETSI Technical Committee Human Factors (TCHF), performed by major industry representatives under the European Commissions eEurope Initiative. The availability of a standardised set of universal, generic interaction elements increases the transfer of knowledge to use mobile devices and services, improves the overall usability of the entire interactive mobile environment and improves access for all. Such a transfer becomes even more important in a world of ubiquitous devices and services to the young, elderly and disabled.     

A human–robot interface for mobile manipulator

This paper presents a remote manipulation method for mobile manipulator through operator’s gesture. In particular, a track mobile robot is equipped with a 4-DOF robot arm to grasp objects. Operator uses one hand to control both the motion of mobile robot and the posture of robot arm via scheme of gesture polysemy method which is put forward in this paper. A sensor called leap motion (LM), which can obtain the position and posture data of hand, is employed in this system. Two filters were employed to estimate the position and posture of human hand so as to reduce the inherent noise of the sensor. Kalman filter was used to estimate the position, and particle filter was used to estimate the orientation. The advantage of the proposed method is that it is feasible to control a mobile manipulator through just one hand using a LM sensor. The effectiveness of the proposed human–robot interface was verified in laboratory with a series of experiments. And the results indicate that the proposed human–robot interface is able to track the movements of operator’s hand with high accuracy. It is found that the system can be employed by a non-professional operator for robot teleoperation.     

How social distance shapes human–robot interaction

This paper investigates how social distance can serve as a lens through which we can understand human–robot relationships and develop guidelines for robot design. In two studies, we examine the effects of distance based on physical proximity (proxemic distance), organizational status (power distance), and task structure (task distance) on people׳s experiences with and perceptions of a humanlike robot. In Study 1, participants (n=32) played a card-matching game with a humanlike robot. We manipulated the power distance (supervisor vs. subordinate) and proxemic distance (close vs. distant) between participants and the robot. Participants who interacted with the supervisor robot reported a more positive user experience when the robot was close than when the robot was distant, while interactions with the subordinate robot resulted in a more positive experience when the robot was distant than when the robot was close. In Study 2, participants (n=32) played the game in two different task distances (cooperation vs. competition) and proxemic distances (close vs. distant). Participants who cooperated with the robot reported a more positive experience when the robot was distant than when it was close. In contrast, competing with the robot resulted in a more positive experience when it was close than when the robot was distant. The findings from the two studies highlight the importance of consistency between the status and proxemic behaviors of the robot and of task interdependency in fostering cooperation between the robot and its users. This work also demonstrates how social distance may guide efforts toward a better understanding of human–robot interaction and the development of effective design guidelines.     

Brain–computer interfaces for human gait restoration

In this review article, we present more than a decade of our work on the development of brain–computer interface (BCI) systems for the restoration of walking following neurological injuries such as spinal cord injury (SCI) or stroke. Most of this work has been in the domain of non-invasive electroencephalogram-based BCIs, including interfacing our system with a virtual reality environment and physical prostheses. Real-time online tests are presented to demonstrate the ability of able-bodied subjects as well as those with SCI to purposefully operate our BCI system. Extensions of this work are also presented and include the development of a portable low-cost BCI suitable for at-home use, our ongoing efforts to develop a fully implantable BCI for the restoration of walking and leg sensation after SCI, and our novel BCI-based therapy for stroke rehabilitation.     

Efficient behavior learning in human–robot collaboration

We present a novel method for a robot to interactively learn, while executing, a joint human–robot task. We consider collaborative tasks realized by a team of a human operator and a robot helper that adapts to the human’s task execution preferences. Different human operators can have different abilities, experiences, and personal preferences so that a particular allocation of activities in the team is preferred over another. Our main goal is to have the robot learn the task and the preferences of the user to provide a more efficient and acceptable joint task execution. We cast concurrent multi-agent collaboration as a semi-Markov decision process and show how to model the team behavior and learn the expected robot behavior. We further propose an interactive learning framework and we evaluate it both in simulation and on a real robotic setup to show the system can effectively learn and adapt to human expectations.     

A micro amperometric immunosensor for detection of human immunoglobulin

1 Introduction In recent years, electrochemical immunosensors have gained considerable interests as bioanalytical devices[1―3]. They have many attractive features, such as convenience for manipulate, being easy to achieve high sensitivity and excellent d…