AI enhanced collaborative human-machine interactions for home-based telerehabilitation

The use of robots in a telerehabilitation paradigm could facilitate the delivery of rehabilitation on demand while reducing transportation time and cost. As a result, it helps to motivate patients to exercise frequently in a more comfortable home environment. However, for such a paradigm to work, it is essential that the robustness of the system is not compromised due to network latency, jitter, and delay of the internet. This paper proposes a solution to data loss compensation to maintain the quality of the interaction between the user and the system. Data collected from a well-defined collaborative task using a virtual reality (VR) environment was used to train a robotic system to adapt to the users' behaviour. The proposed approach uses nonlinear autoregressive models with exogenous input (NARX) and long-short term memory (LSTM) neural networks to smooth out the interaction between the user and the predicted movements generated from the system. LSTM neural networks are shown to learn to act like an actual human. The results from this paper have shown that, with an appropriate training method, the artificial predictor can perform very well by allowing the predictor to complete the task within 25 s versus 23 s when executed by the human

A Firefly-inspired method for protein structure prediction in lattice models

We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa–Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function valuations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models

Assessing the role of optical head-mounted displays in education: an investigation of Google Glass in creating learning portfolios and providing feedback

Technology Enhanced Learning is a field that has seen impressive developments over the past few years. Educators have experimented with the use of web technologies, introduced innovative e-learning approaches, extended the role of virtual learning environments and introduced learning analytics. The authors’ research aims to investigate how ubiquitous computing and augmented reality can further support students in a range of learning activities. In particular, this paper discusses a research study in the role of Optical Head-Mounted Displays (OHMD) in education. Emphasis is given on how the technology can enhance learning through the provision of additional support via augmented reality. The paper describes how OHMD, and more specifically Google Glass has been used by students in a Higher Education Institution as part of their assessment. The research aim is twofold as it considers (i) the role of OHMD in supporting students during the creation of learning portfolios which can be used for formative and summative assessment, and (ii) the impact OHMD technology has in providing alternative ways of feedback. The scope of the research is to assess the suitability of the technology, the benefits that can be introduced in educational contexts as well as the perceived value of the technology from the learners’ point of view. The first part of the study described in the paper describes how learners have used OHMD to construct a portfolio of learning evidence through cooperative evaluation of their work. In particular the study involved students using Google Glass to take snaps of their work, while recording a video diary of their contribution towards group coursework. Users reflected on the experience in terms of ease of use, simplicity and usefulness. They also evaluated the effectiveness of using OHMD during specific tasks including reading, writing and browsing. The second part of the study is focused on providing feedback by using OHMD to attach vignettes on pictures of presentations. The technology is used for commenting on presentation content and delivery, while it is investigated as an alternative for providing feedback on practical activities. The paper also provides a detailed discussion of preliminary findings from the pilot with 92 participants studying at first and final years of a University degree

Using Optical Head-Mounted Devices (OHMD) for provision of feedback in education

This paper discusses the investigation of using Optical Head-Mounted Devices (OHMD) for provision of feedback in education. In particular it discusses an investigation in the use of Google Glass in real time training and mentoring. First the papers discusses an application created for the device for provision of feedback on student presentation. Next the paper presents, the research conducted with an experiment involving ninety-two participants testing the application in a real life scenario

Creating smarter teaching and training environments: innovative set-up for collaborative hybrid learning

This paper brings together previous work from a number of research projects and teaching initiatives in an effort to introduce good practice in setting up supportive environments for collaborative learning. The paper discusses prior use of social media in learning support, the role of dashboards for learning analytics in Global Software Development training, the use of optical head-mounted displays for feedback and the use of NodeXl visualization in managing distributed teams. The scope of the paper is to provide a structured approach in organizing the creation of smarter teaching and training environments and explore ways to coordinate learning scenarios with the use of various techniques. The paper also discusses challenges from integrating multiple innovative features in educational contexts. Finally the paper attempts to investigate the use of smart laboratories in establishing additional learning support and gather primary data from blended and hybrid learning pilot studies

MIRTO: an open-source robotic platform for education

This paper introduces the MIddlesex RoboTic platfOrm (MIRTO), an open-source platform that has been used for teaching First Year Computer Science students since the academic year 2013/2014, with the aim of providing a physical manifestation of Software Engineering concepts that are often delivered using only abstract or synthetic case studies. In this paper we provide a detailed description of the platform, whose hardware specifications and software libraries are all released open source; we describe a number of teaching usages of the platform, report students’ projects, and evaluate some of its aspects in terms of effectiveness, usability, and maintenance

The social value of a QALY : raising the bar or barring the raise?

Background: Since the inception of the National Institute for Health and Clinical Excellence (NICE) in England, there have been questions about the empirical basis for the cost-per-QALY threshold used by NICE and whether QALYs gained by different beneficiaries of health care should be weighted equally. The Social Value of a QALY (SVQ) project, reported in this paper, was commissioned to address these two questions. The results of SVQ were released during a time of considerable debate about the NICE threshold, and authors with differing perspectives have drawn on the SVQ results to support their cases. As these discussions continue, and given the selective use of results by those involved, it is important, therefore, not only to present a summary overview of SVQ, but also for those who conducted the research to contribute to the debate as to its implications for NICE. Discussion: The issue of the threshold was addressed in two ways: first, by combining, via a set of models, the current UK Value of a Prevented Fatality (used in transport policy) with data on fatality age, life expectancy and age-related quality of life; and, second, via a survey designed to test the feasibility of combining respondents’ answers to willingness to pay and health state utility questions to arrive at values of a QALY. Modelling resulted in values of £10,000-£70,000 per QALY. Via survey research, most methods of aggregating the data resulted in values of a QALY of £18,000-£40,000, although others resulted in implausibly high values. An additional survey, addressing the issue of weighting QALYs, used two methods, one indicating that QALYs should not be weighted and the other that greater weight could be given to QALYs gained by some groups. Summary: Although we conducted only a feasibility study and a modelling exercise, neither present compelling evidence for moving the NICE threshold up or down. Some preliminary evidence would indicate it could be moved up for some types of QALY and down for others. While many members of the public appear to be open to the possibility of using somewhat different QALY weights for different groups of beneficiaries, we do not yet have any secure evidence base for introducing such a system