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Fillet welding is one of the most widespread types of welding in the industry, which is still carried out manually or automated by contact. This paper aims to describe an online programming system for noncontact fillet welding robots with U and L shaped structures, which responds to the needs of the Fourth Industrial Revolution. In this paper, the authors propose an online robot programming methodology that eliminates unnecessary steps traditionally performed in robotic welding, so that the operator only performs three steps to complete the welding task. First, choose the piece to weld. Then, enter the welding parameters. Finally, it sends the automatically generated program to the robot. The system finally managed to perform the fillet welding task with the proposed method in a more efficient preparation time than the compared methods. For this, a reduced number of components was used compared to other systems, such as, a structured light 3D camera, two computers and a concentrator, in addition to the six axis industrial robotic arm. The operating complexity of the system has been reduced as much as possible. To the best of the authors knowledge, there is no scientific or commercial evidence of an online robot programming system capable of performing a fillet welding process, simplifying the process so that it is completely transparent for the operator and framed in the Industry 4.0 paradigm. Its commercial potential lies mainly in its simple and low cost implementation in a flexible system capable of adapting to any industrial fillet welding job and to any support that can accommodate it., 11 pages, 8 figures

This study is aimed at evaluating the impact of different technical solutions of a virtual reality simulator to support the assessment of advanced human–machine interfaces for hydraulic excavator based on a new coordinated control paradigm and haptic feedbacks. By mimicking the end-effector movements, the control is conceived to speed up the learning process for novice operators and to reduce the mental overload on those already trained. The design of the device can fail if ergonomics, usability and performance are not grounded on realistic simulations where the combination of visual, auditory and haptic feedbacks make the users feel like being in a real environment rather than a computer-generated one. For this reason, a testing campaign involving 10 subjects was designed to discriminate the optimal set-up for the hardware to ensure a higher immersion into the VR experience. Both the audio–video configurations of the simulator (head-mounted display and surround system vs. monitor and embedded speakers) and the two types of haptic feedback for the soil–bucket interaction (contact vs. shaker) are compared in three different scenarios. The performance of both the users and simulator are evaluated by processing subjective and objective data. The results show how the immersive set-up improves the users’ efficiency and ergonomics without putting any extra mental or physical effort on them, while the preferred haptic feedback (contact) is not the more efficient one (shaker).

Magnetic tracking systems have been widely investigated in biomedical engineering due to the transparency of the human body to static magnetic fields. We recently proposed a novel human-machine interface for prosthetic application, namely the myokinetic interface. This controls multi-articulated prostheses by tracking magnets implanted in the residual muscles of individuals with amputation. Previous studies in this area focused solely on the choice and tuning of the localization algorithm. Here, we addressed the role of the intrinsic properties of the sensors, by analysing their effects on the tracking accuracy and on the computation time of the localization algorithm, through experimentally-verified computer simulations. We observed that the tracking accuracy is primarily affected by the localization rate, which is directly related to the sampling frequency of the sensors, and less significantly affected by the sensor resolution. The computation time, instead, proved positively correlated to the number of MMs, and negatively correlated with the localization rate. Our results may contribute to the development of novel human-machine interfaces for prosthetic limbs and could be extended to a broad range of applications involving magnetic tracking.

Present computing power and enhanced technology is progressing at a dramatic rate. These systems can unravel complex issues, assess and control processes, learn, and—in many cases—fully automate production. There is no doubt that technological advancement is improving many aspects of life, changing the landscape of virtually all industries and enhancing production beyond what was thought possible. However, the human is still a part of these systems. Consequently, as the advancement of systems transpires, the role of humans within those systems will unavoidably continue to adapt as well. Due to the human tendency for error, this technological advancement should compel a persistent emphasis on human error reduction as part of maximizing system efficiency and safety—especially in the context of the nuclear industry. Within this context, as new systems are designed and the role of the human is transformed, human error should be targeted for a significant decrease relative to predecessor systems and an equivalent increase in system stability and safety. This article contends that optimizing the roles of humans and machines in the design and implementation of new types of automation in nuclear facility systems should involve human error reduction without ignoring the essential importance of human interaction within those systems.

International audience; In partially automated vehicles, the driver and the automated system share control of the vehicle. Consequently, the driver may have to switch between driving and monitoring activities. This can critically impact the driver’s situational awareness. The human–machine interface (HMI) is responsible for efficient collaboration between driver and system. It must keep the driver informed about the status and capabilities of the automated system, so that he or she knows who or what is in charge of the driving. The present study was designed to compare the ability of two HMIs with different information displays to inform the driver about the system’s status and capabilities: a driving-centered HMI that displayed information in a multimodal way, with an exocentric representation of the road scene, and a vehicle-centered HMI that displayed information in a more traditional visual way. The impact of these HMIs on drivers was compared in an on-road study. Drivers’ eye movements and response times for questions asked while driving were measured. Their verbalizations during the test were also transcribed and coded. Results revealed shorter response times for questions on speed with the exocentric and multimodal HMI. The duration and number of fixations on the speedometer were also greater with the driving-centered HMI. The exocentric and multimodal HMI helped drivers understand the functioning of the system, but was more visually distracting than the traditional HMI. Both HMIs caused mode confusions. The use of a multimodal HMI can be beneficial and should be prioritized by designers. The use of auditory feedback to provide information about the level of automation needs to be explored in longitudinal studies.

Pada era teknologi yang semakin berkembang pesat, penggunaan elektronika daya semakin banyak digunakan seperti untuk penggontrolan motor dan lain – lain. Untuk mendukung semua itu tentu juga di iringi dengan metode – metode interfacing yang memudahkan user dalam penggunaaan alat – alat elektronika daya seperti contohnya buck conveter. Interfacing yang di maksud disini adalah dengan melakukan pengaturan keluaran buck converter dengan menggunakan interfacing pada personal computer sekaligus memonitoringnya. Buck converter adalah jenis dc-dc converter yang berfungsi untuk mengubah keluaran tegangan output lebh kecil dibandingkan dengan tegangan keluaran input. Perancangan monitoring menggunakan visual basic dalam pembuatan interfacing, hal ini dilakukan karena kemudahan komunikasi antara visual basic dengan arduino. Metode pengontrolan menggunakan pengaturan duty cycle yang diberikan dari visual basic ke arduino. Dengan mengatur duty cycle, maka tegangan yang dkeluarkan pun akan berubah-ubah. Berdasarkan hasil pengujiaan, maka dengan memperbesar duty cycle maka keluaran tegangan dari buck converter akan semakin kecil, Dengan hasil pengukuran buck converter pada input tegangan 24 volt dan duty 15.97 menghasilkan tegangan keluaran sebesar 19,5 sedangkan pada duty cycle 34.57 menghasilkan tegangan sebesar 13.9.

Human-machine interface (HMI) techniques use bioelectrical signals to gain real-time synchronised communication between the human body and machine functioning. HMI technology not only provides a real-time control access but also has the ability to control multiple functions at a single instance of time with modest human inputs and increased efficiency. The HMI technologies yield advanced control access on numerous applications such as health monitoring, medical diagnostics, development of prosthetic and assistive devices, automotive and aerospace industry, robotic controls and many more fields. In this paper, various physiological signals, their acquisition and processing techniques along with their respective applications in different HMI technologies have been discussed.

The article reviews retrospectives and prospects of design and technological solutions for man-machine interfaces of manned spacecraft in order to determine possible trends in their development for information support of crews of lunar expeditions in manual modes of spacecraft operation in conditions of limited opportunities for operational interaction with a groundbased fl ight control center. Prospects and trends of this kind are especially important to be known and taken into account at the stage of the preliminary design of the considered human-machine interfaces.

To increase flight safety and operational availability for helicopters, the potential benefits of helmet-mounted displays (HMD) are investigated, with a focus on maritime flight operations. Helicopters have long downtimes, due to harsh weather conditions or other visual impairments, especially in maritime scenarios. Flying in these poor conditions can drastically reduce flight safety. It is often difficult to recognize the horizon due to sea fog, and the absence of reference objects can complicate the maritime flight. These conditions and especially the downtimes cost money or, at worst, life’s. Therefore, DLR integrated the augmented reality glasses Microsoft HoloLens into DLR’s simulator AVES to use it as HMD for pilots. Subsequently, displays and symbology were developed and evaluated. To carry out a piloted simulator study, a maritime scenario was created to measure changes in the pilots’ performance with the HMD, like workload or situational awareness. The paper focuses (a) on the integration of the HoloLens into the simulator with its challenges, solutions and findings, (b) on the symbology and (c) on the piloted simulator study. Both the quality of the HoloLens as HMD and the study results are very positive. The pilots rated high usability, reduced workload, increased situational awareness and increased safety.

The global construction industry is one the least productive sectors over a 30-year period, which arguably could be related to virtually no implementation of digital and automation technologies within the construction industry. Construction processes arguably consist of expensive manual labor or manual operation of mechanized processes, where hand-drawn markings on work-objects or partly build structures are used to inform and steer the construction process or allows for ad hoc adjustments of elements. As such, the use of on-object, hand-drawn information is considered integral to the modus operandi of a plurality of construction trades, where timber construction and carpentry are of special interest. In contrast, emerging methods of digital production in timber construction implicitly or explicitly seek to eliminate the interpretive component to the construction work, imposing a top-down paradigm of file-to-factory execution. While such systems offer a performance increase compared to manual labor, it is notoriously sensitive to construction tolerances and requires a high level of specialism to be operated, which could alienate craft-educated workers. This research argues that developing methods for digital production compatible with on-site human interpretation and adaptation can help overcome these challenges. In addition, these methods offer the opportunity to increase the robustness and versatility of digital fabrication in the context of the construction site. The article reports on a new method titled “augmented drawn construction symbols” that through a visual communication system converts on-object hand-drawn markings to CAD drawings and sends them to a robotic system. The process is demonstrated on a full-scale prototypical robot setup.

The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life, for example, healthcare monitoring and treatment, ambient monitoring, soft robotics, prosthetics, flexible display, communication, human‐machine interactions, and so on. According to the development in recent years, the next‐generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence (AI) and internet of things (IoT), to achieve a higher level of comfort, convenience, connection, and intelligence. Herein, this review provides an opportune overview of the recent progress in wearable electronics, photonics, and systems, in terms of emerging materials, transducing mechanisms, structural configurations, applications, and their further integration with other technologies. First, development of general wearable electronics and photonics is summarized for the applications of physical sensing, chemical sensing, human‐machine interaction, display, communication, and so on. Then self‐sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage technologies. Next, technology fusion of wearable systems and AI is reviewed, showing the emergence and rapid development of intelligent/smart systems. In the last section of this review, perspectives about the future development trends of the next‐generation wearable electronics/photonics are provided, that is, toward multifunctional, self‐sustainable, and intelligent wearable systems in the AI/IoT era.

Nowadays, with the development of automotive driving technologies, more and more functions and devices with control systems based on tactile, optical, and acoustic sensors are assembled into cars. ...

The latest advances in the design of vehicles with the adaptive level of automation pose new challenges in the vehicle-driver interaction. Safety requirements underline the need to explore optimal cockpit architectures with regard to driver cognitive and perceptual workload, eyes-off-the-road time and situation awareness. We propose to integrate existing task analysis approaches into system architecture evaluation for the early-stage design optimization. We built the discrete-event simulation tool and applied it within the multi-sensory (sight, sound, touch) cockpit design industrial project.

Technological developments in the domain of vehicle automation are targeted toward driver-less, or driver-out-of-the-loop driving. The main societal motivation for this ambition is that the majority of (fatal) accidents with manually driven vehicles are due to human error. However, when interacting with technology, users often experience the need to customize the technology to their personal preferences. This paper considers how this might apply to vehicle automation, by a conceptual analysis of relevant use cases. The analysis proceeds by comparing how handling of relevant situations is likely to differ between manual driving and automated driving. The results of the analysis indicate that full out-of-the-loop automated driving may not be acceptable to users of the technology. It is concluded that a technology that allows shared control between the vehicle and the user should be pursued. Furthermore, implications of this view are explored for the concrete temporal dynamics of shared control, and general characteristics of human machine interface that support shared control are proposed. Finally, implications of the proposed view and directions for further research are discussed.

This essay tracks the ‘human’ emergent in human-centred technologies (HCTs) in Japan. A primary aim of HCTs is to extract the true intention of the user and actualise it as machine action. Beyond this, HCT researchers maintained that creating such technologies would give them access to the truth of the human itself. In this essay, I examine the games of truth played in HCT, in which teachers exercise authority over students by defining their true intentions for them, and students learned what they needed to become good researchers. I then show how through analogical relations, human subjects with esteemed qualities became what HCTs must be, and HCTs a means for imagining what human beings truly are. What emerged were truths that transcended human and machine: all are systems of information and, in the end, the right machine can approach humanity enough to fulfil even the most human of responsibilities.

Progress toward intelligent human–robotic interactions requires monitoring sensors that are mechanically flexible, facile to implement, and able to harness recognition capability under harsh environments. Conventional sensing methods have been divided for human‐side collection or robot‐side feedback and are not designed with these criteria in mind. However, the iontronic polymer is an example of a general method that operates properly on both human skin (commonly known as skin electronics or iontronics) and the machine/robotic surface. Here, a unique iontronic composite (silk protein/glycerol/Ca(II) ion) and supportive molecular mechanism are developed to simultaneously achieve high conductivity (around 6 kΩ at 50 kHz), self‐healing (within minutes), strong stretchability (around 1000%), high strain sensitivity and transparency, and universal adhesiveness across a broad working temperature range (−40–120 °C). Those merits facilitate the development of iontronic sensing and the implementation of damage‐resilient robotic manipulation. Combined with a machine learning algorithm and specified data collection methods, the system is able to classify 1024 types of human and robot hand gestures under challenging scenarios and to offer excellent object recognition with an accuracy of 99.7%., This work presents a silk‐based iontronic film which is designed to be simultaneously conductive, self‐healable, antifreezing, and antiheating, based on the developed unique material composition (silk protein/glycerol/Ca(II) ion) and dynamic molecular mechanism. Furthermore, when coupled with a specified machine learning algorithm, the approach permits accurate human/robotic gesture identification across over 1024 classes with high accuracy in harsh environment.

In recent years, surface Electromyography (sEMG) signals have been effectively applied in various fields such as control interfaces, prosthetics, and rehabilitation. We propose a neck rotation estimation from EMG and apply the signal estimate as a game control interface that can be used by people with disabilities or patients with functional impairment of the upper limb. This paper utilizes an equation estimation and a machine learning model to translate the signals into corresponding neck rotations. For testing, we designed two custom-made game scenes, a dynamic 1D object interception and a 2D maze scenery, in Unity 3D to be controlled by sEMG signal in real-time. Twenty-two (22) test subjects (mean age 27.95, std 13.24) participated in the experiment to verify the usability of the interface. From object interception, subjects reported stable control inferred from intercepted objects more than 73% accurately. In a 2D maze, a comparison of male and female subjects reported a completion time of 98.84 s. ± 50.2 and 112.75 s. ± 44.2, respectively, without a significant difference in the mean of the one-way ANOVA (p = 0.519). The results confirmed the usefulness of neck sEMG of sternocleidomastoid (SCM) as a control interface with little or no calibration required. Control models using equations indicate intuitive direction and speed control, while machine learning schemes offer a more stable directional control. Control interfaces can be applied in several areas that involve neck activities, e.g., robot control and rehabilitation, as well as game interfaces, to enable entertainment for people with disabilities.

The GCS (Ground Control Station) is an elementary part of the UAS (Unmanned Aircraft System). It provides the connection between the human pilot and the airborne part of the UAS, the drone. While early GCS have been merely more than simple remote controls, a modern GCS can do more than just relaying steering commands to the drone. Instead, it provides an important contribution to the safety of the UAS operation. This is achieved by presenting the pilot pre-processed information from the drone and secondary data sources. Utilizing design principles developed in human machine interface (HMI) theory, these information can be shown to the pilot without distraction and making optimal use of the data. This chapter summarizes design principles and challenges for HMIs in aviation use. The focus is on challenges related to UAS operations and UAS GCS in particular. The design process for the GCS U-FLY will be described, and some results of a real-world test in the context of two application projects will be presented.

Human motion intention detection is an essential part of the control of upper-body exoskeletons. While surface electromyography (sEMG)-based systems may be able to provide anticipatory control, they typically require exact placement of the electrodes on the muscle bodies which limits the practical use and donning of the technology. In this study, we propose a novel physical interface for exoskeletons with integrated sEMG- and pressure sensors. The sensors are 3D-printed with flexible, conductive materials and allow multi-modal information to be obtained during operation. A K-Nearest Neighbours classifier is implemented in an off-line manner to detect reaching movements and lifting tasks that represent daily activities of industrial workers. The performance of the classifier is validated through repeated experiments and compared to a unimodal EMG-based classifier. The results indicate that excellent prediction performance can be obtained, even with a minimal amount of sEMG electrodes and without specific placement of the electrode.

Measuring temperature in various systems can be quite challenging, such as in power breakers, railway power lines contacts or in electric traction substations. This article presents an on-line monitoring system with Human Machine Interface to supervise the temperature of a high railway voltage separator. The temperature is measured using an infrared temperature sensor that converts the temperature in an electrical signal, which, afterwards, is used as an analogue input for the Siemens S7-1200 PLC.

The human–machine interface plays an important role in the diversified interactions between humans and machines, especially by swaping information exchange between human and machine operations. Considering the high wearable compatibility and self-powered capability, triboelectric-based interfaces have attracted increasing attention. Herein, this work developed a minimalist and stable interacting patch with the function of sensing and robot controlling based on triboelectric nanogenerator. This robust and wearable patch is composed of several flexible materials, namely polytetrafluoroethylene (PTFE), nylon, hydrogels electrode, and silicone rubber substrate. A signal-processing circuit was used in this patch to convert the sensor signal into a more stable signal (the deviation within 0.1 V), which provides a more effective method for sensing and robot control in a wireless way. Thus, the device can be used to control the movement of robots in real-time and exhibits a good stable performance. A specific algorithm was used in this patch to convert the 1D serial number into a 2D coordinate system, so that the click of the finger can be converted into a sliding track, so as to achieve the trajectory generation of a robot in a wireless way. It is believed that the device-based human–machine interaction with minimalist design has great potential in applications for contact perception, 2D control, robotics, and wearable electronics.

Truck overtaking maneuvers on freeways are inefficient, risky and promote high potential for conflict between road users. Collective perception based on V2X communication allow coordination with all parties to reduce the negative impact and could be installed in a timely manner compared to automation. However, the prerequisite for the success of this system is a human-machine interface that the driver can easily operate, trusts and accepts. In this approach, a user-centered conception and design of a human-machine interface for cooperative truck overtaking maneuver on freeways is presented. The development process is separated in two steps: After a prototype is build based on task analysis it is initially evaluated and improved iteratively with a heuristic evaluation by experts. The final prototype is tested in a simulator study with 30 truck drivers. The study provides initial feedback regarding the drivers' attitudes towards such a system and how it can be further improved.

In view of its capacity to create physical objects for a wide range of different potential applications, 3D printing has become increasingly popular over the years. However, given its scope of application, 3D printing can be challenging. Novice users often need assistance from experts, who are not always available. Recent interest in the development of conversational agents opens up the possibility of assisting novice users in their interactions with 3D printers, thus improving their experience. In this paper, we illustrate a potential concept of a conversational agent and present a prototype of a Telegram chatbot to improve the user experience of 3D printing.

The article addresses the concept of human-machine interface operation and problems solved during interface design. We provide a general description of problems related to the drivers’ readiness to enhance the automation level of vehicles. A basic algorithm of human-machine interface operation for an automated vehicle is described.

Industrial spraying operations in high-mix, low-volume manufacturing are usually not automated due to variety and variability among workpieces. Automated path planning for industrial spraying operations offers the potential to automate surface preparation and coating in such environments. Autonomous spray path planners in the literature have been limited to generally continuous and convex surfaces, which is not true of most real parts. There is a need for planners that consistently handle concavities and discontinuities, such as sharp corners, holes, protrusions, and other surface abnormalities when building a path. This research uses slicing-based adaptive planning methods to generate path trajectories. It identifies and quantifies the importance of concavities and surface abnormalities and whether they should be considered in the path plan by comparing the true part geometry to the convex hull path. Based on these considerations, the path is adapted accordingly. Results show that the path planning method generates smooth trajectories and indicate that the adaptive methods developed substantially increase both mean impingement and uniformity of impingement in a pressure washing application. From this, it is concluded that the method represents a substantial step toward one-off robotic path planning for complex geometries.

Recent developments of social virtual reality (VR) services using avatars have increased the need for facial expression recognition (FER) technology. FER systems are generally implemented using optical cameras; however, the performance of these systems can be limited when users are wearing head-mounted displays (HMDs) as users' faces are largely covered by the HMDs. Facial electromyograms (fEMGs) that can be recorded around users' eyes can be potentially used for implementing FER systems for VR applications. However, this technology lacks practicality owing to the need for large-scale training datasets; furthermore, it is hampered by a relatively low performance. In this study, we proposed an fEMG-based FER system based on the Riemannian manifold-based approach to reduce the number of training datasets needed and enhance FER performance. Our experiments with 42 participants showed an average classification accuracy as high as 85.01% for recognizing 11 facial expressions with only a single training dataset for each expression. We further developed an online FER system that could animate a virtual avatar's expression reflecting a user's facial expression in real time, thus demonstrating that our FER system can be potentially used for practical interactive VR applications, such as social VR networks, smart education, and virtual training.

This paper aims to develop an automatic neonatal incubator equipped with phototherapy, biometric fingerprint reader, remote monitoring and heart rate control modules for developing countries due to the lack of neonatal incubators. The proposed device consists of an acquisition module that senses temperatures (of the enclosure and the baby) and humidity, a biometric fingerprint reader to identify the user, a remote monitoring module in charge of supervising the temperature and the heart rate of the baby, a video surveillance module which allows filming and transmitting the images to the web server in order to give parents and nurses the possibility of being able to visualize whatever their location the newborn baby, a phototherapy module used to treat newborn jaundice by lowering the bilirubin levels in the baby's blood, a digital control module from a pulse width modulation (PWM) signal generated by a microcontroller of Arduino Nano type for system operation monitoring, and a human machine interface module for setting parameters. The equations describing the energy balance and heat transfer for newborn baby (Ostrowski and Rojczyk, 2018) are taken into account for the implementation of power supply and the choice of the heating resistor. The desired temperature of 37 °C was obtained after only a few minutes inside the incubator.

In many work domains, the push toward higher levels of automation raises the concern of diminishing human expertise. Ecological interfaces could help operators in retaining and potentially even in acquiring expertise as they are hypothesized to lead to a deeper understanding of the work domain. This study explores the short-term impact of ecological interfaces on knowledge development and compares the results with an instruction-based training method. To monitor and compare students' progress, their decision-making strategies, identified from verbal comments recorded in 'think-aloud' simulator sessions, are mapped onto the decision ladder. This method has been applied to an experiment (N=16) aimed at training novices in conflict detection and resolution (CD&R) within a simplified air traffic control context. Results show that the overall CD&R performance in the final measurement sessions, featuring a transfer manipulation, was not significantly different between the 'ecological' and 'instructional' groups. In terms of cognitive behavior, however, students in the ecological group exhibited more laborious rule- and knowledge-based behaviors that sparked goal-oriented thoughts and corresponding control performances beyond the CD&R task. These findings indicate that ecological interfaces can change how people think and approach a control problem, even after removing the support. It is therefore reasonable to believe that ecological interfaces can play an important role in the early stages of deep knowledge development.

International audience; Rapid technological innovations are constantly influencing the complexification and automatization of the work lines pushing human operators to use diverse cognitive processes for supervising complex industrial machines. This urges factories to offer wearable cognitive assistants to human operators to analyze, integrate and maintain a considerable amount of information. The aim of this review is twofold. First, we borrow theoretical elements from the working memory literature to question the way these wearable cognitive assistants could optimize human operators’ cognitive load. Second, we argue that Technology Acceptance Model (TAM) and Job Characteristics Model (JCM) may theoretically predict the effectiveness of cognitive wearable assistants in enhancing the person–job fit, namely their cognitive performance and well-being. A critical review method was used to collect and summarize the most studied models associated with application of wearable devices in the workplace. Our review suggests that the current literature on working memory give useful insights concerning the way in which information should be displayed to operators to optimize the efficiency of wearable cognitive assistants. Moreover, JCM suggests original explanations on the way they can facilitate access to information and in turn increase job satisfaction. Finally, a small number of studies that used TAM with wearable devices in an industrial setting provide some interesting theoretical and empirical evidence on the acceptance of wearable cognitive assistants. As a conclusion, we argue that using wearable cognitive assistants properly would enhance both cognitive performance and well-being of human operators through promoting the person–job fit.

It is evident that non-invasive muscle-based human–machine interface (HMI) has been the research focus of human–machine interaction. To improve the performance of muscle-based HMI, it is significantly important to obtain electrophysiological and morphological changes of muscle contraction. However, there is still lacking of solution to present electrophysiological and morphological information of the same muscle at the same time. Surface electromyography (sEMG) can reflect the electrical activity of functional muscle contraction and A-mode ultrasound (AUS) can monitor the morphological structure of active muscle, both in non-invasive manners. This paper proposes a portable hybrid sEMG/AUS system for HMI. The system consists of composite sensor armband and signal acquisition modules, where the former achieves arrangement of two kinds of sensors at the same muscle position and the latter enables the simultaneous acquisition of sEMG and AUS signals. The hardware evaluation experiment proves that the system can provide high-quality signals in respect to signal-to-noise ratio (SNR) and time–frequency characteristics. Furthermore, the hand gesture recognition experiment validates the complementarity between sEMG-based and AUS-based HMI, since the recognition accuracy of hybrid sEMG/AUS feature is significantly improved by 4.85% ( ${p}$ = 0.0095) and 20.6% ( ${p} ) compared to the results of ultrasound features and sEMG features, respectively.

This study evaluates the use of virtual reality (VR) platforms, which is an integrated part of the digital factory for an industrial training and maintenance system. The digital factory-based VR pl...

This paper proposes a method for prompting drivers’ spatial attention by presenting visual cue in their peripheral visual field. Computer-generated images of forward-facing driving scenes were projected on a screen 6 m wide and 1.8 m high, with a 140° viewing angle. The gaze movement of subjects was measured when hazardous events were presented, such as cardboard boxes collapsing onto the road or a child running out into the road. The task defined for the subjects was to detect visual cue presented in their central visual field while observing the driving scene in front of them. A preceding visual cue was presented in the right and left visual fields, at a visual angle of 10° to 40°, for 1–5 s in advance of the visual cue presented in the center of the visual field. The detection time for the visual cue in the central visual field was then measured. The results of the experiments conducted with six subjects revealed two types of gaze movement patterns with respect to a hazardous event. In one type, the subjects broadly captured the overall scene without shifting their gaze markedly; in the other type, the subjects sequentially scanned the scene and fixed their gaze on the hazardous event when it occurred. The former type tended to be seen in subjects with long driving experience. It was also found that presenting visual cue in the peripheral visual field quickened recognition of the visual cue in the central visual field. By varying the viewing angle at which the preceding cue was presented in the peripheral visual field and the time interval between the presentation of the preceding cue and the detection cue in the central visual field, conditions were found for assisting prompt detection of the latter visual cue.

Developing interactive systems and testing with realistic scenarios requires a detailed understanding of how these systems are used in their real environment. In this paper, we report on our experience from implementing a usage monitoring approach for the touch-enabled human machine interface of an industrial machine. The approach supports automated recording of user interface events as basis for analyzing interactions of users with the system. It collects information about navigation paths to different screens, activities on these screens, and the usage of functionality provided by the application. We evaluated three different approaches to integrate the required usage monitoring into the UI, considering aspects such as necessary changes to the existing code base, dependencies to third-party libraries, and the entailed performance overhead. The paper provides a detailed description of the implementation of the selected approach and a discussion of the lessons we learned from integrating the monitoring in an existing application.

In this work, we extend the previously proposed approach of improving mutual perception during human–robot collaboration by communicating the robot’s motion intentions and status to a human worker using hand-worn haptic feedback devices. The improvement is presented by introducing spatial tactile feedback, which provides the human worker with more intuitive information about the currently planned robot’s trajectory, given its spatial configuration. The enhanced feedback devices communicate directional information through activation of six tactors spatially organised to represent an orthogonal coordinate frame: the vibration activates on the side of the feedback device that is closest to the future path of the robot. To test the effectiveness of the improved human–machine interface, two user studies were prepared and conducted. The first study aimed to quantitatively evaluate the ease of differentiating activation of individual tactors of the notification devices. The second user study aimed to assess the overall usability of the enhanced notification mode for improving human awareness about the planned trajectory of a robot. The results of the first experiment allowed to identify the tactors for which vibration intensity was most often confused by users. The results of the second experiment showed that the enhanced notification system allowed the participants to complete the task faster and, in general, improved user awareness of the robot’s movement plan, according to both objective and subjective data. Moreover, the majority of participants (82%) favoured the improved notification system over its previous non-directional version and vision-based inspection. Web of Science 21 17 art. no. 5748

The absence of a human driver in an automated vehicle (AV) raises new challenges in communication and cooperation between road users, especially for ambiguous situations where road users would like to communicate their intention explicitly. This paper investigates the effect of a novel external human-machine interface (eHMI) which was designed to address this issue by signaling the AV’s intention through a 360° LED light-band mounted outside of the AV. In a simulator study an eHMI interaction strategy was implemented that should convey the message “I am giving way” to a manually driven vehicle operated by participants waiting at a t-junction. The experimental study incorporated three t-junction scenarios where the AV had always the right of way but may yield to a driver waiting at the intersection. The intention of the AV was communicated either implicitly (braking) or implicitly and explicitly (braking and eHMI). It was analyzed whether participants would understand the AV’s intention and accept the gap provided in front of the AV. Through participants’ subjective ratings the understandability, the usability and the acceptance of the eHMI solution were evaluated. The results showed that the majority of participants (85%) understood the meaning of the eHMI signal after two interactions. Initial gap acceptance results showed a positive effect of the eHMI solution. The presence of an eHMI improved participants perceived safety and trust. Subjective ratings for usability and acceptance indicated that participants perceived this eHMI interaction strategy as easy to use and were willing to communicate with an AV in this way. The results of the present study will be used to investigate the beneficial impact of this eHMI interaction strategy further in more complex traffic scenarios.

The utilization of robotic systems has been increasing in the last decade. This increase has been derived by the evolvement in the computational capabilities, communication systems, and the information systems of the manufacturing systems which is reflected in the concept of Industry 4.0. Furthermore, the robotics systems are continuously required to address new challenges in the industrial and manufacturing domain, like keeping humans in the loop, among other challenges. Briefly, the keeping humans in the loop concept focuses on closing the gap between humans and machines by introducing a safe and trustworthy environment for the human workers to work side by side with robots and machines. It aims at increasing the engagement of the human as the automation level increases rather than replacing the human, which can be nearly impossible in some applications. Consequently, the collaborative robots (Cobots) have been created to allow physical interaction with the human worker. However, these cobots still lack of recognizing the human emotional state. In this regard, this paper presents an approach for adapting cobot parameters to the emotional state of the human worker. The approach utilizes the Electroencephalography (EEG) technology for digitizing and understanding the human emotional state. Afterwards, the parameters of the cobot are instantly adjusted to keep the human emotional state in a desirable range which increases the confidence and the trust between the human and the cobot. In addition, the paper includes a review on technologies and methods for emotional sensing and recognition. Finally, this approach is tested on an ABB YuMi cobot with commercially available EEG headset. publishedVersion

Exoskeleton suits can be considered as a wearable robotic item ,where the main inution is to increase,improve& boost the physical performance of operator/user by a desired margin , it has a great practicality in the present time as it can be implemented in a variety of filed extending from Health sector to industries .The scope of this is to design a full-body,rigid,Active,performance type mobile-exoskeleton prototype, by targeting it as mainly applicable for the Industry sector , Defence sector& Civil-(construction,fire & safety department, etc) Sectors , which has seen to be taking a leap in to this genre .This paper explicates the methodology for the design which was modeled in “Solidworks” and analysys of mechanical strucuture– performed by “Ansys Workbench”& selection of actuation mechanism with a coustomised design which was validated by a series of analysis in “Altiar Flux Motor” , this paper also scrutinize very succinctly the “gait” cycle & its phases ,itsummarise the necessity of the “gait” analysis- which was performed by “Opensim”from which data was acquired for the analysis of designed prototype& for the guidance inactuation of the prototype by prediction & restriction of drive controller valueto the normal gait values during locomotion by “gait assist function”,where the actuator control is primarly by the sensing of a series of “Strain guage” belts attached to the users muscles , 4 different control drivers used for actuation out of which for thigh joint the control drive was coustamised , the battery houses 728 high-performance Lithium-ion cells 0f “Panasonic-NCR18650B 3400MAh”,for cooling system a common aluminium heat sink was used.the other critical factors which was considered during the designing was cost-effectiveness, minimal maintenance, ergonomic , efficiency and safety of the designed prototype is also pithily considered . the total weight of the designed prototype model was 79Kg & was able to lift & locomote at 1.36m/s with apayload of 258kg.

As human and an automation system cooperate to complete the driving task, whether the spatio-temporal distribution of HMI elements is sufficiently reasonable to disclose information clearly and effectively for drivers to develop an accurate mental model of the system's form and behavior will significantly impact the system transparency and drivers’ trust on the system. Moreover, this will further affect the safety of driving, as well as the willingness of drivers to adopt the intelligent driving functions. In this study, an investigation was conducted on the spatial and temporal distribution characteristics exhibited by human-machine interface (HMI) elements in Adaptive Cruise Control (ACC) cut-in scenarios, and the trust of drivers under different distributions was compared.

Introduction: Neural tube defects (NTDs) are multifactorial congenital anomalies of the central nervous system that results from failed neural tube closure between the 3rd and 4th weeks of embryonic development. Numerous clinical and experimental studies indicate that supplementation with folic acid before and during early pregnancy reduces the development of these anomalies. The present study examined the incidence and risk factors for NTDs and evaluated the effects of folic acid supplementation.Methods: This cross-sectional study included all children with NTDs who were hospitalized at the Pediatric Clinic, Clinical Centre University of Sarajevo during the period from January 01, 2008 to December 31, 2012. Data were collected retrospectively from the medical histories of hospitalized children. The study included children in pediatric clinics from four cantons (Sarajevo, Zenica–Doboj, Unsko–Sanski, and Central Bosnia) of the Federation of Bosnia and Herzegovina. The number of live births for the specified period in each of the four cantons was taken from a report by the Cantonal Ministry of Health.Results: Among the 69,096 live births recorded during the study period, 39 children had verified NTDs, with an overall incidence of 0.56:1,000 (or 5.6:10,000) in all four cantons. The most common NTDs were myelomeningocele with hydrocephalus (22/39, 56.4%), followed by isolated myelomeningocele (9/39, 23.1%), spina bifida occulta (7/39, 17.9%), and occipitocele (1/39, 2.6%). A total of 33.3% (13/39) of mothers took folic acid, but only one began supplementation prior to pregnancy, while 67.7% (26/39) of mothers did not take folic acid during pregnancy. NTDs were found more frequently in primiparas (53.8%), women with low education (basic school, 64.1%), and unemployed women (82.1%).Conclusion: It is important to make national recommendations for folic acid supplementation for women of reproductive age, but also change the public health policy that includes mandatory fortification of basic foods as this is the best measure for primary prevention of NTDs in the whole population regardless of employment and education status. Additional comprehensive studies are required to assess the incidence and risk factors throughout Bosnia and Herzegovina.

In intelligent vehicles, it is essential to monitor the driver’s condition, however, recognizing the driver’s emotional state is one of the most challenging and important tasks. Most previous studies focused on facial expression recognition to monitor the driver’s emotional state. However, while driving, many factors are preventing the drivers from revealing the emotions on their faces. To address this problem, we propose a deep learning-based driver’s real emotion recognizer (DRER), which is a deep learning-based algorithm to recognize the drivers’ real emotions that cannot be completely identified based on their facial expressions. The proposed algorithm comprises of two models: (i) facial expression recognition model, which refers to the state-of-the-art convolutional neural network structure, and (ii) sensor fusion emotion recognition model, which fuses the recognized state of facial expressions with electrodermal activity, a bio-physiological signal representing electrical characteristics of the skin, in recognizing even the driver’s real emotional state. Hence, we categorized the driver’s emotion and conducted human-in-the-loop experiments to acquire the data. Experimental results show that the proposed fusing approach achieves 114% increase in accuracy compared to using only the facial expressions and 146% increase in accuracy compare to using only the electrodermal activity. In conclusion, our proposed method achieves 86.8% recognition accuracy in recognizing the driver’s induced emotion while driving situation.

Electroencephalogram (EEG) based Brain Computer Interface (BCI) has a huge market with big potential and wide prospect, however, the acquisition equipment is too expensive to be popular with ordinary users, which makes the majority of applications are still in the laboratory. Inspired by the development of hybrid Human-Computer Interaction (HCI), a utility HCI using low-cost EEG cap and eye tracker are investigated in this paper. The validation experiment indicates that the proposed system is able to detect and classify multiple patterns of EEG signals and translate them into control commands to interact with the environment. Furthermore, an eye tracker enables subjects to freely observe the surrounding environment and select a target object under the naked eye VR technique. Comparing to the HCI only based on eye tracker, EEG signals are used to realize the motor function in this paper to reduce the fatigue caused by long-time fixation in traditional eye tracker application. Furthermore, compared to the BCI system at the same price, the lack of electrodes can be compensated by an eye tracker. In conclusion, the hybrid HCI proposed in this paper achieves superior performance through low-cost equipment, which may promote the development of the interaction between the human and environment based on the physiological signals.

This study is about the manufacturing of a personified automatic robotic lawn mower with image recognition. The system structure is that the platform above the crawler tracks is combined with the lawn mower, steering motor, slide rail, and webcam to achieve the purpose of personification. Crawler tracks with a strong grip and good ability to adapt to terrain are selected as a moving vehicle to simulate human feet. In addition, a lawn mower mechanism is designed to simulate the left and right swing of human mowing to promote efficiency and innovation, and then human eyes are replaced by Webcam to identify obstacles. A human-machine interface is added so that through the mobile phone remote operation, users can choose a slow mode, inching mode, and obstacle avoidance mode on the human-machine interface. When the length of both sides of the rectangular area is input to the program, the automatic robotic lawn mower will complete the instruction according to the specified path. The chip of a Digital Signal Processor (DSP) TMS320F2808 is used as the core controller, and Raspberry Pi is used as image recognition and human-machine interface design. This robot can reduce labor costs and improve the efficiency of mowing by remote control. In addition to the use as an automatic mower on farms, this study concept can also be used in the lawn maintenance of golf courses and school playgrounds.