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Human Activity Analysis in Visual Surveillance and Healthcare
An automatic recognition of human activities enables their use in several interesting applications of daily life. This dissertation emphases on the analysis of human activities in a visual surveillance scenario and the classification of physical activities in the therapeutic procedure using visual data. The first part of the dissertation proposes a robust gait representation to recognise the identity of a person using his/her walking style, dealing with its several real world challenges as well as taking into consideration the effects of cross-view recognition. In the second part, a complete framework is proposed to capture and analyse the movement of different body parts in human which is useful in the clinical assessment to detect any movement disorders and the assessment of the desired therapeutic program.
Computer and Information Science
This edited book presents scientific results of the 15th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2016) which was held on June 26– 29 in Okayama, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review. This publication captures 12 of the conference’s most promising papers, and we impatiently await the important contributions that we know these authors will bring to the field of computer and information science.
Machine Learning Methods for Pain Investigation Using Physiological Signals
Pain assessment has remained largely unchanged for decades and is currently based on self-reporting. Although there are different versions, these self-reports all have significant drawbacks. For example, they are based solely on the individual’s assessment and are therefore influenced by personal experience and highly subjective, leading to uncertainty in ratings and difficulty in comparability. Thus, medicine could benefit from an automated, continuous and objective measure of pain. One solution is to use automated pain recognition in the form of machine learning. The aim is to train learning algorithms on sensory data so that they can later provide a pain rating. This thesis summarises s...
Information Technology in Biomedicine
This book presents a comprehensive study in the field of advances in medical data science and contains carefully selected articles contributed by experts of information technology. Continuous growth of the amount of medical information and the variety of multimodal content necessitates the demand for a fast and reliable technology able to process data and deliver results in a user-friendly manner at the time and place the information is needed. Computational approaches for understanding human complexity, AI-powered applications in image and signal processing, bioinformatics, sound and motion as activity stimulus, joint activities in biomedical engineering and physiotherapy, disorder in child...
Automatic Assessment of Prosody in Second Language Learning
Worldwide there is a universal need for second language language learning. It is obvious that the computer can be a great help for this, especially when equipped with methods for automatically assessing the learner's pronunciation. While assessment of segmental pronunciation quality (i.,e. whether phones and words are pronounced correctly or not) is already available in commercial software packages, prosody (i.e. rhythm, word accent, etc.) is largely ignored--although it highly impacts intelligibility and listening effort. The present thesis contributes to closing this gap by developing and analyzing methods for automatically assessing the prosody of non-native speakers. We study the detection of word accent errors and the general assessment of the appropriateness of a speaker's rhythm. We propose a flexible, generic approach that is (a) very successful on these tasks, (b) competitive to other state-of-the-art result, and at the same time (c) flexible and easily adapted to new tasks.
Information Modelling and Knowledge Bases XIX
In the last decades information modelling and knowledge bases have become hot topics not only in academic communities related to information systems and computer science, but also in business areas where information technology is applied. This book includes papers submitted to the 17th European-Japanese Conference on Information Modelling and Knowledge Bases (EJC 2007). The EJC conferences constitute a world-wide research forum for the exchange of scientific results and experiences achieved in computer science and other related disciplines using innovative methods and progressive approaches. I.
Analysis of Speech of People with Parkinson's Disease
The analysis of speech of people with Parkinson's disease is an interesting and highly relevant topic that has attracted the research community during several years. The advances in digital signal processing and pattern recognition have motivated the research community to work on the development of computational tools to perform automatic analysis of speech. Most of the contributions on this topic are focused on sustained phonation of vowels and only consider recordings of one language. This thesis addresses two problems considering recordings of sustained phonations of vowels and continuous speech signals: (1) the automatic classification of Parkinson's patients vs. healthy speakers, and (2...
