Kinect based Intelligent Wheelchair navigation with potential fields

Increasing elderly people population and people with disabilities constitute a huge demand for wheelchairs. Wheelchairs have an important role on improving the lives and mobilization of people with disabilities. Moreover, autonomous wheelchairs constitute a suitable research platform for academic and industrial researchers. In this study, Finite state machine (FSM) based high-level controller and Kinect based navigation algorithm have been developed for ATEKS (Intelligent Wheelchair) which has high-tech control mechanisms, low-cost sensors and open source software (ROS, GAZEBO, ANDROID). © 2014 IEEE

Towards a Legal end Ethical Framework for Personal Care Robots. Analysis of Person Carrier, Physical Assistant and Mobile Servant Robots.

Technology is rapidly developing, and regulators and robot creators inevitably have to come to terms with new and unexpected scenarios. A thorough analysis of this new and continuosuly evolving reality could be useful to better understand the current situation and pave the way to the future creation of a legal and ethical framework. This is clearly a wide and complex goal, considering the variety of new technologies available today and those under development. Therefore, this thesis focuses on the evaluation of the impacts of personal care robots. In particular, it analyzes how roboticists adjust their creations to the existing regulatory framework for legal compliance purposes. By carrying out an impact assessment analysis, existing regulatory gaps and lack of regulatory clarity can be highlighted. These gaps should of course be considered further on by lawmakers for a future legal framework for personal care robot. This assessment should be made first against regulations. If the creators of the robot do not encounter any limitations, they can then proceed with its development. On the contrary, if there are some limitations, robot creators will either (1) adjust the robot to comply with the existing regulatory framework; (2) start a negotiation with the regulators to change the law; or (3) carry out the original plan and risk to be non-compliant. The regulator can discuss existing (or lacking) regulations with robot developers and give a legal response accordingly. In an ideal world, robots are clear of impacts and therefore threats can be responded in terms of prevention and opportunities in form of facilitation. In reality, the impacts of robots are often uncertain and less clear, especially when they are inserted in care applications. Therefore, regulators will have to address uncertain risks, ambiguous impacts and yet unkown effects

A Framework For The Adoption And Effective Use Of Icts For Visually Impaired Learners In Higher Education

ThesisEducation is a vital asset that makes a valuable contribution in society. That is because it helps shape people into responsible citizens. Citizens who attain higher education play an important role in the economic stability and social prosperity of a nation. It is therefore imperative that all individuals in a country are assured of equal educational opportunities. The South African Constitution has embraced an inclusive education policy to ensure that no student is left behind in the education system. Inclusive education is an educational system that is designed in such a way that addresses the needs of all the students regardless of their disabilities. Special schools in South Africa cater for the educational needs of learners with disabilities. However, various researchers have observed that learners who are visually impaired are often excluded from participating in higher education institutions, especially in Engineering courses. Consequently, it is essential to identify the challenges that visually impaired learners in South Africa face when contemplating entry into higher education and more specifically, Engineering courses. Unlike other courses such as Management and Education, Engineering courses are more practical-based. That is because Engineering courses are visual in nature, especially subjects such as Computer Science, IT and Electrical Engineering which might prove challenging to visually impaired learners. Therefore, such learners require the assistance of specialised Information and Communications Technology (ICT) tools and resources for studying Engineering courses. ICT has revolutionised the education sector by facilitating the teaching and learning process of visually impaired learners. This study aims to develop a framework for the provision of visually impaired learners in Engineering education in SA using ICTs. This study also examines the ICT tools that could be adopted to better facilitate the entry of visually impaired learners into Engineering courses. A design science research paradigm is used in this study. The study started with an intensive literature review, followed by a case study which was divided into two parts: Part A and Part B. Part A of the case study was done at school level and utilised focus groups and questionnaires from educators at special schools. Part B of the case study was conducted at university level and utilised questionnaires to collect data from disability units at universities; HODs and senior lecturers from Engineering faculties at universities. The data collected from all the data sources were triangulated to develop the proposed framework for the study. The proposed framework for the provision of visually impaired learners in Engineering education in SA using ICTs comprised six components: government and management support; finance; infrastructure; mobility; teaching and learning; and student support services. The framework was evaluated by specific field experts so as to establish its validity and refine its suitability for higher education in SA. The proposed framework was refined based on the feedback from the experts. Experts consisted of a group of researchers who had done research in Engineering education, HODs of Engineering faculties, managers of disability centres and a visually impaired person working in an Engineering/IT field. Consequently, a modified framework is presented in this thesis. The scientific contribution of this study is the provision of a framework that may be used to provide better access to Engineering courses for VILs in higher education in South Africa using ICT’s. This research has identified six principal factors and twenty-one sub-factors that would assist the provision of VILs in Engineering education. Establishing such a framework could provide improved academic access for VILs in SA, thereby increasing their prospects of employment and empowerment. Accommodating VILs in the labour sector of SA will improve their quality of life, thereby contributing to the country’s economic prosperity

Machine Learning Driven Emotional Musical Prosody for Human-Robot Interaction

This dissertation presents a method for non-anthropomorphic human-robot interaction using a newly developed concept entitled Emotional Musical Prosody (EMP). EMP consists of short expressive musical phrases capable of conveying emotions, which can be embedded in robots to accompany mechanical gestures. The main objective of EMP is to improve human engagement with, and trust in robots while avoiding the uncanny valley. We contend that music - one of the most emotionally meaningful human experiences - can serve as an effective medium to support human-robot engagement and trust. EMP allows for the development of personable, emotion-driven agents, capable of giving subtle cues to collaborators while presenting a sense of autonomy. We present four research areas aimed at developing and understanding the potential role of EMP in human-robot interaction. The first research area focuses on collecting and labeling a new EMP dataset from vocalists, and using this dataset to generate prosodic emotional phrases through deep learning methods. Through extensive listening tests, the collected dataset and generated phrases were validated with a high level of accuracy by a large subject pool. The second research effort focuses on understanding the effect of EMP in human-robot interaction with industrial and humanoid robots. Here, significant results were found for improved trust, perceived intelligence, and likeability of EMP enabled robotic arms, but not for humanoid robots. We also found significant results for improved trust in a social robot, as well as perceived intelligence, creativity and likeability in a robotic musician. The third and fourth research areas shift to broader use cases and potential methods to use EMP in HRI. The third research area explores the effect of robotic EMP on different personality types focusing on extraversion and neuroticism. For robots, personality traits offer a unique way to implement custom responses, individualized to human collaborators. We discovered that humans prefer robots with emotional responses based on high extraversion and low neuroticism, with some correlation between the humans collaborator’s own personality traits. The fourth and final research question focused on scaling up EMP to support interaction between groups of robots and humans. Here, we found that improvements in trust and likeability carried across from single robots to groups of industrial arms. Overall, the thesis suggests EMP is useful for improving trust and likeability for industrial, social and robot musicians but not in humanoid robots. The thesis bears future implications for HRI designers, showing the extensive potential of careful audio design, and the wide range of outcomes audio can have on HRI.Ph.D

Automated Semantic Understanding of Human Emotions in Writing and Speech

Affective Human Computer Interaction (A-HCI) will be critical for the success of new technologies that will prevalent in the 21st century. If cell phones and the internet are any indication, there will be continued rapid development of automated assistive systems that help humans to live better, more productive lives. These will not be just passive systems such as cell phones, but active assistive systems like robot aides in use in hospitals, homes, entertainment room, office, and other work environments. Such systems will need to be able to properly deduce human emotional state before they determine how to best interact with people. This dissertation explores and extends the body of knowledge related to Affective HCI. New semantic methodologies are developed and studied for reliable and accurate detection of human emotional states and magnitudes in written and spoken speech; and for mapping emotional states and magnitudes to 3-D facial expression outputs. The automatic detection of affect in language is based on natural language processing and machine learning approaches. Two affect corpora were developed to perform this analysis. Emotion classification is performed at the sentence level using a step-wise approach which incorporates sentiment flow and sentiment composition features. For emotion magnitude estimation, a regression model was developed to predict evolving emotional magnitude of actors. Emotional magnitudes at any point during a story or conversation are determined by 1) previous emotional state magnitude; 2) new text and speech inputs that might act upon that state; and 3) information about the context the actors are in. Acoustic features are also used to capture additional information from the speech signal. Evaluation of the automatic understanding of affect is performed by testing the model on a testing subset of the newly extended corpus. To visualize actor emotions as perceived by the system, a methodology was also developed to map predicted emotion class magnitudes to 3-D facial parameters using vertex-level mesh morphing. The developed sentence level emotion state detection approach achieved classification accuracies as high as 71% for the neutral vs. emotion classification task in a test corpus of children’s stories. After class re-sampling, the results of the step-wise classification methodology on a test sub-set of a medical drama corpus achieved accuracies in the 56% to 84% range for each emotion class and polarity. For emotion magnitude prediction, the developed recurrent (prior-state feedback) regression model using both text-based and acoustic based features achieved correlation coefficients in the range of 0.69 to 0.80. This prediction function was modeled using a non-linear approach based on Support Vector Regression (SVR) and performed better than other approaches based on Linear Regression or Artificial Neural Networks

Managing healthcare transformation towards P5 medicine (Published in Frontiers in Medicine)

Health and social care systems around the world are facing radical organizational, methodological and technological paradigm changes to meet the requirements for improving quality and safety of care as well as efficiency and efficacy of care processes. In this they’re trying to manage the challenges of ongoing demographic changes towards aging, multi-diseased societies, development of human resources, a health and social services consumerism, medical and biomedical progress, and exploding costs for health-related R&D as well as health services delivery. Furthermore, they intend to achieve sustainability of global health systems by transforming them towards intelligent, adaptive and proactive systems focusing on health and wellness with optimized quality and safety outcomes. The outcome is a transformed health and wellness ecosystem combining the approaches of translational medicine, 5P medicine (personalized, preventive, predictive, participative precision medicine) and digital health towards ubiquitous personalized health services realized independent of time and location. It considers individual health status, conditions, genetic and genomic dispositions in personal social, occupational, environmental and behavioural context, thus turning health and social care from reactive to proactive. This requires the advancement communication and cooperation among the business actors from different domains (disciplines) with different methodologies, terminologies/ontologies, education, skills and experiences from data level (data sharing) to concept/knowledge level (knowledge sharing). The challenge here is the understanding and the formal as well as consistent representation of the world of sciences and practices, i.e. of multidisciplinary and dynamic systems in variable context, for enabling mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc. Based on a framework for dynamically, use-case-specifically and context aware representing multi-domain ecosystems including their development process, systems, models and artefacts can be consistently represented, harmonized and integrated. The response to that problem is the formal representation of health and social care ecosystems through an system-oriented, architecture-centric, ontology-based and policy-driven model and framework, addressing all domains and development process views contributing to the system and context in question. Accordingly, this Research Topic would like to address this change towards 5P medicine. Specifically, areas of interest include, but are not limited: • A multidisciplinary approach to the transformation of health and social systems • Success factors for sustainable P5 ecosystems • AI and robotics in transformed health ecosystems • Transformed health ecosystems challenges for security, privacy and trust • Modelling digital health systems • Ethical challenges of personalized digital health • Knowledge representation and management of transformed health ecosystems Table of Contents: 04 Editorial: Managing healthcare transformation towards P5 medicine Bernd Blobel and Dipak Kalra 06 Transformation of Health and Social Care Systems—An Interdisciplinary Approach Toward a Foundational Architecture Bernd Blobel, Frank Oemig, Pekka Ruotsalainen and Diego M. Lopez 26 Transformed Health Ecosystems—Challenges for Security, Privacy, and Trust Pekka Ruotsalainen and Bernd Blobel 36 Success Factors for Scaling Up the Adoption of Digital Therapeutics Towards the Realization of P5 Medicine Alexandra Prodan, Lucas Deimel, Johannes Ahlqvist, Strahil Birov, Rainer Thiel, Meeri Toivanen, Zoi Kolitsi and Dipak Kalra 49 EU-Funded Telemedicine Projects – Assessment of, and Lessons Learned From, in the Light of the SARS-CoV-2 Pandemic Laura Paleari, Virginia Malini, Gabriella Paoli, Stefano Scillieri, Claudia Bighin, Bernd Blobel and Mauro Giacomini 60 A Review of Artificial Intelligence and Robotics in Transformed Health Ecosystems Kerstin Denecke and Claude R. Baudoin 73 Modeling digital health systems to foster interoperability Frank Oemig and Bernd Blobel 89 Challenges and solutions for transforming health ecosystems in low- and middle-income countries through artificial intelligence Diego M. López, Carolina Rico-Olarte, Bernd Blobel and Carol Hullin 111 Linguistic and ontological challenges of multiple domains contributing to transformed health ecosystems Markus Kreuzthaler, Mathias Brochhausen, Cilia Zayas, Bernd Blobel and Stefan Schulz 126 The ethical challenges of personalized digital health Els Maeckelberghe, Kinga Zdunek, Sara Marceglia, Bobbie Farsides and Michael Rigb