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The purpose of this paper is to provide details of recent developments in human‐robot interfacing technologies.

This paper considers recently developed or emerging technologies which allow humans to interact with robots in novel ways. It first considers inexpensive robots which are simple to programme and which can work alongside humans in a manufacturing environment. It then discusses assistive robots, which aim to help the aged or infirm and finally, the latest progress in controlling robots with the human brain is reported.

This shows that new and improved human‐robot interfacing technologies are the topic of a major development effort. Low‐cost robots that can readily be commissioned and operated in close proximity to humans are starting to impact the market. Assistive robot technology is progressing due to novel man‐machine interfacing techniques and the first instances of quadriplegic patients using their mind to control robots to manipulate object in three‐dimensional space is discussed.

This paper provides details of significant, recent developments in human‐robot interfacing.

This paper aims to provide an insight into the emerging use of robots in the rehabilitation of sufferers from strokes and other neurological impediments.

This considers research, clinical trials and commercial products. Following an introduction, it explains brain neuroplasticity and its role in rehabilitation and then discusses the use of robots in the restoration of upper limb and hand movement in stroke and traumatic injury patients. Robotic techniques aimed at restoring ambulatory ability are then discussed, followed by examples of the application of brain–computer interface technology to robotic rehabilitation. Finally, concluding comments are drawn.

Research has shown that robotic techniques can assist in the restoration of functionality to partially or fully paralysed upper and lower limbs. A growing number of commercial exoskeleton and end-effector robotic products have been launched which are augmenting conventional rehabilitation therapies. These systems frequently include interactive computer games and tasks which encourage repetitive use and allow patients to monitor their progress. Trials which combine robotics with brain–computer interface technology have yielded encouraging and unexpectedly positive results.

This provides details of the increasingly important role played by robots in the rehabilitation of patients suffering from strokes and other neurological disorders.

Many experts consider that the technological convergence of previously separated sciences like nanotechnology, biotechnology, information and communication technologies and cognitive sciences, will – in the long term – impact deeply our society and economy. Key actors in society need to become aware of the challenges linked to converging applications (CA) and take some decision related to processes to develop these. It is hoped that analyzing CA‐related opportunities and risks at a very early stage will contribute to reduce possible adverse effects in the future. This paper seeks to address this issue.

The analysis is based upon a literature review, complemented with ten expert interviews carried out over the telephone. The interviewees were natural and social scientists familiar with the topic of converging technologies/applications.

Setting priorities for discussion on research and strategy within and between the various fields of CA benefits from the early involvement of key stakeholders from the very beginning. Formulating and structuring relevant open questions on opportunities and possible risks of CA helps to contribute to a balanced discussion on opportunities and risks and further work on this topic.

The opportunity and risk analysis is exemplified for four promising areas at the intersection of cognitive science and ICT, namely human brain interfaces; speech recognition technologies; artificial neural networks; and robotics.

The aim of this paper is to gain knowledge in podcast mining as an additional source for Web-based horizon scanning (HS). The paper presents theoretical insights on the potential of podcast mining by exploring topics, which may be relevant in the future, and by reflecting the results against a background of HS approaches. The study provides a preliminary overview by presenting an exemplary list of podcast shows for further research.

The paper uses an exploratory quantitative content analysis, which was conducted on the basis of 30 topics deemed to be relevant in the future and which were identified in the field of applied science. Based on these topics, podcasts and episodes were identified which address future-oriented topics and were discussed in terms of range of content.

The findings indicate that future-oriented topics are addressed in podcasts. However, differences in dynamics and range of content of the podcasts concerned highlight the necessity of identifying a list of suitable podcasts according to the specific scanning focus and the dynamics of each future-oriented topics.

While a growing number of podcast studies have already noted the importance of podcasts as a key medium, for example, educational processes and media sciences, no detailed explanation of podcast mining as a tool for the purposes of HS has been published. The review therefore makes an original contribution to this field, highlighting areas where future research is needed.

There has been little thought given in science to the impact of direct brain‐machine interfacing upon the future development of human consciousness. Even less thought has been given to the possibilities for both optimizing and thwarting development in the cyborg child. A neurocognitive model of the evolution of cyborg consciousness is summarized, and from this model grounded speculations are offered pertaining to the future development of the higher cognitive functions in the cyborg child. It will be shown that cybernetic implants are “multistable”; that is, the artificial intelligence (AI) component of the cyborg brain‐machine linkage may function to condition development along ideological lines (the brain conditioned by the “ideological chip”), or may operate to open up neurocognitive development to new and heretofore unrealized limits (the brain’s development optimized by the “guru programme”). Development of the cyborg child may be conditioned in the interests of ideological concerns, or may lead to a consciousness that easily transcends all forms of ideology. Application of the guru programme may foster the emergence of new levels of cognitive complexity and information processing (à la Piagetian and neo‐Piagetian theory) that in turn allows new strategies of adaptation previously beyond human comprehension. The ethical and regulatory problems raised by cyborg technologies are addressed.

Using cortical neurons of animals to control external devices allows experimenters a unique opportunity to study the capability of the brain to utilize a new actuator. The purpose of this paper is to investigate the ability of unrestrained rats to control a directional task using motor cortical signals.

In freely moving rats, signals recorded from the motor cortex of the brain enabled the use of a closed loop brain machine interface (BMI) system to replace paddle pressing for a directional task. In this system, ring rates from several (two to ten) motor cortical neurons at several consecutive time points were used as input to a support vector machine (SVM) classifier. The decision‐function value obtained from the SVM was then used to determine which relay should be activated to produce paddle‐pressing signals in the task. All five animals tested were able to use this interface immediately and significant changes in neural activity arise in a single, 45‐min, experimental session. Neural data from three of the subjects were examined for changes from the calibration phase (data used to build the SVM model) to the late cortically controlled phase.

Detailed analysis shows that neural activity changes significantly from the calibration phase to the cortically controlled phase, furthermore, the decision‐function values arising from these neural signals change to support better performance. By examining which neurons and times are selected by the SVM to have significant impact on the decision‐function value as well as which of these elements change significantly, a mechanism of adaptation begins to emerge in which the SVM properly assigns high importance to dimensions that easily predict the desired output, however, under closed‐loop control, the animal selects a small number of neurons (at most or all times) and chooses to make the firing rates more distinguishable. Video taken of one of the subjects further suggests the nature of the behavioral correlates of these changes.

In the design of practical BMI devices for human patients, one effective strategy might involve creating mappings from multi‐neuron ensembles using state‐of‐the‐art machine learning techniques, but expect that the patients who use the devices will adapt to the devices using single neuron modulation changes.

In the design of practical BMI devices for human patients, one effective strategy might involve creating mappings from multi‐neuron ensembles using state‐of‐the‐art machine learning techniques, but expect that the patients who use the devices will adapt to the devices using single neuron modulation changes. The proposed decentralization approach is interesting for the design of optimization algorithms that can run on computing systems that use principles of self‐organization and have no central control.

The purpose of this paper is to identify and explore potential applications of cyborgian technologies within service contexts and how service providers may leverage the integration of cyborgian service actors into their service proposition. In doing so, the paper proposes a new category of “melded” frontline employees (FLEs), where advanced technologies become embodied within human actors. The paper presents potential opportunities and challenges that may arise through cyborg technological advancements and proposes a future research agenda related to these.

This study draws on literature in the fields of services management, artificial intelligence, robotics, intelligence augmentation (IA) and human intelligence to conceptualise potential cyborgian applications.

The paper examines how cyborg bio- and psychophysical characteristics may significantly differentiate the nature of service interactions from traditional “unenhanced” service interactions. In doing so, the authors propose “melding” as a conceptual category of technological impact on FLEs. This category reflects the embodiment of emergent technologies not previously captured within existing literature on cyborgs. The authors examine how traditional roles of FLEs will be potentially impacted by the integration of emergent cyborg technologies, such as neural interfaces and implants, into service contexts before outlining future research directions related to these, specifically highlighting the range of ethical considerations.

Service interactions with cyborg FLEs represent a new context for examining the potential impact of cyborgs. This paper explores how technological advancements will alter the individual capacities of humans to enable such employees to intuitively and empathetically create solutions to complex service challenges. In doing so, the authors augment the extant literature on cyborgs, such as the body hacking movement. The paper also outlines a research agenda to address the potential consequences of cyborgian integration.

The purpose of this paper is to present research in the area of control method for the man‐machine systems with brain machine interface (BMI). Concrete target system is, for instance, a car cruising system and so on.

The improved receding horizon control (RHC) method for the sampled‐data systems and the adaptive digital‐to‐analog (DA) converter which has the way to switch the sampling functions according to the system status are used. The feature selection method based on the kernel support vector machines with the backward stepwise selection for the BMI signals are also used.

This paper proposes the new improved RHC method with the adaptive DA converter for the application of the BMI‐based systems. The proposed method is illustrated as useful and effective method for the systems to which switch of control laws is indispensable by the simulations.

Although the proposed method is effective for the BMI‐based systems with switching of control laws, the faster algorithm for RHC will be need to apply to the man‐machine systems with the BMI in practical use.

The basic concept or framework of the proposed method can be used for the real man‐machine systems with the BMI, for examples, car crusing systems, wheel‐chaired systems and so on.

The paper contributes to the development of the new effective control method for the BMI‐based man‐machine systems.

The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD and innovator regarding his pioneering efforts and his personal journey of bringing a technological invention to market. This paper aims to discuss these issues.

The interviewee is Dr Howard Chizeck, Professor of Electrical and Computer Engineering and Adjunct Professor of Bioengineering at the University of Washington (UW). Professor Chizeck is a research testbed leader for the Center for Neurotechnology (a National Science Foundation Engineering Research Center) and also co-director of the UW BioRobotics Laboratory. In this interview, Chizeck shares the details on his latest startup, Olis Robotics.

Howard Jay Chizeck received his BS and MS degrees from Case Western Reserve University and the ScD degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. He served as Chair of the Department of Systems, Control and Industrial Engineering at Case Western Reserve University and was also the Chair of the Electrical and Computer Engineering Department at the University of Washington. His telerobotic research includes haptic navigation and control for telerobotic devices, including robotic surgery and underwater systems. His neural engineering work involves the design and security of brain-machine interfaces and the development of devices to control symptoms of essential tremor and Parkinson’s disease.

Professor Chizeck was elected as a Fellow of the IEEE in 1999 “for contributions to the use of control system theory in biomedical engineering” and he was elected to the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows in 2011 for “contributions to the use of control system theory in functional electrical stimulation assisted walking.” From 2008 to 2012, he was a member of the Science Technology Advisory Panel of the Johns Hopkins Applied Physics Laboratory. Professor Chizeck currently serves on the Visiting Committee of the Case School of Engineering (Case Western Reserve University). He is a founder and advisor of Controlsoft Inc (Ohio) and also is a founder and Chair of the Board of Directors of Olis Robotics, Inc., which was established in 2013 (under the name of BluHaptics) to commercialize haptic rendering, haptic navigation and other UW telerobotic technologies. He holds approximately 20 patents, and he has published more than 250 scholarly papers.

This article attempts to match the future needs of older people with the possibilities arising from applications based on new technology.

This article examines the implications of novel applications for active ageing policy. These applications are forecast to arise from the convergence of two or more previously separated science disciplines and technologies, including information and communication technologies, nanotechnologies, biotechnology and cognitive sciences.

Research on converging applications (CA) is largely driven by health applications, and is likely to spill over into the older generation's specific needs. Today, older people's most urgent needs require little CA. In the future, however, the role of CA will become more important as technology develops and is more widely used.

Owing to demographic change and its expected social and economic implications, there is a need to investigate how upcoming applications could contribute to the future specific needs of the older population.