This book presents the cutting-edge technologies of knee joint vibroarthrographic signal analysis for the screening and detection of knee joint injuries. It describes a number of effective computer-aided methods for analysis of the nonlinear and nonstationary biomedical signals generated by complex physiological mechanics. This book also introduces several popular machine learning and pattern recognition algorithms for biomedical signal classifications. The book is well-suited for all researchers looking to better understand knee joint biomechanics and the advanced technology for vibration arthrometry. Dr. Yunfeng Wu is an Associate Professor at the School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China.

This book includes high-quality papers presented at Second International Conference on Computational Electronics for Wireless Communications (ICCWC 2022), held at National Institute of Technology, Surathkal, Karnataka, India, during June 9 – 10, 2022. The book presents original research work of academics and industry professionals to exchange their knowledge of the state-of-the-art research and development in computational electronics with an emphasis on wireless communications. The topics covered in the book are radio frequency and microwave, signal processing, microelectronics, and wireless networks.

The third international conference on INformation Systems Design and Intelligent Applications (INDIA – 2016) held in Visakhapatnam, India during January 8-9, 2016. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of three different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano-computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.

Smart mobile systems, eHealth and telemedicine, as well as social media and gamification, have all become important enablers for the provision of the next generation of health services. This book presents the proceedings of the 13th International Conference on Wearable, Micro and Nano Technologies for Personalised Health (pHealth 2016), held in Heraklion, Crete, in May 2016. pHealth 2016 brings together experts from medical, technological, political, administrative, legal and social domains with the aim of further emphasizing the integration of biology and medical data, systems and information using mobile technologies. The book includes two keynotes and two specially invited talks as well as 21 oral and 10 poster presentations selected by a rigorous review process (with a rejection rate of more than 30%) from the more than 45 submissions to the conference. The book is divided into two sections. The first covers mHealth, devices, applications and biosensors and the second deals with smart personal health systems, deep learning, interoperability and precision medicine. Subjects covered include the development of micro-, nano-, bio- and smart-systems with an emphasis on personalized health, virtual care, precision medicine, big bio data management and analytics, as well as security, privacy and safety issues. This book will be of interest to all those whose work involves the provision of healthcare, both today and into the future.

The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.