Download or read book Sensor Based Human Activity Recognition for Assistive Health Technologies written by Muhammad Adeel Nisar and published by Logos Verlag Berlin GmbH. This book was released on 2023-02-20 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The average age of people has increased due to advances in health sciences, which has led to an increase in the elderly population. This is positive news, but it also raises questions about the quality of independent living for older people. Clinicians use Activities of Daily Living (ADLs) to assess older people's ability to live independently. In recent years, portable computing devices have become more present in our daily lives. Therefore, a software system that can detect ADLs based on sensor data collected from wearable devices is beneficial for detecting health problems and supporting health care. In this context, this book presents several machine learning-based approaches for human activity recognition (HAR) using time-series data collected by wearable sensors in the home environment. In the first part of the book, machine learning-based approaches for atomic activity recognition are presented, which are relatively simple and short-term activities. In the second part, the algorithms for detecting long-term and complex ADLs are presented. In this part, a two-stage recognition framework is also presented, as well as an online recognition system for continuous monitoring of HAR. In the third and final part, a novel approach is proposed that not only solves the problem of data scarcity but also improves the performance of HAR by implementing multitask learning-based methods. The proposed approach simultaneously trains the models of short- and long-term activities, regardless of their temporal scale. The results show that the proposed approach improves classification performance compared to single-task learning.

Download or read book Human Activity Recognition and Behaviour Analysis written by Liming Chen and published by Springer. This book was released on 2019-06-11 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book first defines the problems, various concepts and notions related to activity recognition, and introduces the fundamental rationale and state-of-the-art methodologies and approaches. It then describes the use of artificial intelligence techniques and advanced knowledge technologies for the modelling and lifecycle analysis of human activities and behaviours based on real-time sensing observations from sensor networks and the Internet of Things. It also covers inference and decision-support methods and mechanisms, as well as personalization and adaptation techniques, which are required for emerging smart human-machine pervasive systems, such as self-management and assistive technologies in smart healthcare. Each chapter includes theoretical background, technological underpinnings and practical implementation, and step-by-step information on how to address and solve specific problems in topical areas. This monograph can be used as a textbook for postgraduate and PhD students on courses such as computer systems, pervasive computing, data analytics and digital health. It is also a valuable research reference resource for postdoctoral candidates and academics in relevant research and application domains, such as data analytics, smart cities, smart energy, and smart healthcare, to name but a few. Moreover, it offers smart technology and application developers practical insights into the use of activity recognition and behaviour analysis in state-of-the-art cyber-physical systems. Lastly, it provides healthcare solution developers and providers with information about the opportunities and possible innovative solutions for personalized healthcare and stratified medicine.

Download or read book Human Activity Recognition Using Wearable Sensors written by Jamie O'Halloran and published by Eliva Press. This book was released on 2020-04-04 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advancements in healthcare can contribute unquestionably in reducing healthcare strains by ensuring clinicians, doctors and other medical staff operate and conduct their daily activities more efficiently in the hospital vicinity. Since the turn of the 21st century, Human Activity Recognition (HAR) has undergone significant research in the healthcare domain. HAR utilised with powerful technologies can benefit remote patient monitoring, the elderly, patients suffering from chronic illness and ambient assisted living. Human activity recognition has shown to be effective in benefiting clinicians in the treatment and remote monitoring of patients. This field is not only vital for diagnosis and treatment, but also an assessment of how likely a medical patient will fall ill or die from certain diseases or health problems. To show the great importance of activity recognition in the health sector, analytically driving an improvement in accuracy in classifying patients' activities improves the relationship of patients and clinicians as well as reducing the possibility of a fatality. With Artificial Intelligence at the forefront of its revolutionary capabilities, a bright future is in store if we can implement it beneficially into our healthcare service. This book reveals how.

Download or read book Smartphone Based Human Activity Recognition written by Jorge Luis Reyes Ortiz and published by Springer. This book was released on 2015-01-14 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book reports on the author’s original work to address the use of today’s state-of-the-art smartphones for human physical activity recognition. By exploiting the sensing, computing and communication capabilities currently available in these devices, the author developed a novel smartphone-based activity-recognition system, which takes into consideration all aspects of online human activity recognition, from experimental data collection, to machine learning algorithms and hardware implementation. The book also discusses and describes solutions to some of the challenges that arose during the development of this approach, such as real-time operation, high accuracy, low battery consumption and unobtrusiveness. It clearly shows that it is possible to perform real-time recognition of activities with high accuracy using current smartphone technologies. As well as a detailed description of the methods, this book also provides readers with a comprehensive review of the fundamental concepts in human activity recognition. It also gives an accurate analysis of the most influential works in the field and discusses them in detail. This thesis was supervised by both the Universitat Politècnica de Catalunya (primary institution) and University of Genoa (secondary institution) as part of the Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments.

Download or read book Vision Based Human Activity Recognition written by Zhongxu Hu and published by Springer Nature. This book was released on 2022-04-22 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic, comprehensive, and timely review on V-HAR, and it covers the related tasks, cutting-edge technologies, and applications of V-HAR, especially the deep learning-based approaches. The field of Human Activity Recognition (HAR) has become one of the trendiest research topics due to the availability of various sensors, live streaming of data and the advancement in computer vision, machine learning, etc. HAR can be extensively used in many scenarios, for example, medical diagnosis, video surveillance, public governance, also in human–machine interaction applications. In HAR, various human activities such as walking, running, sitting, sleeping, standing, showering, cooking, driving, abnormal activities, etc., are recognized. The data can be collected from wearable sensors or accelerometer or through video frames or images; among all the sensors, vision-based sensors are now the most widely used sensors due to their low-cost, high-quality, and unintrusive characteristics. Therefore, vision-based human activity recognition (V-HAR) is the most important and commonly used category among all HAR technologies. The addressed topics include hand gestures, head pose, body activity, eye gaze, attention modeling, etc. The latest advancements and the commonly used benchmark are given. Furthermore, this book also discusses the future directions and recommendations for the new researchers.

Download or read book Sensor and Video Based Activity and Behavior Computing written by Md Atiqur Rahman Ahad and published by Springer Nature. This book was released on 2022-05-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the best-selected research papers presented at the 3rd International Conference on Activity and Behavior Computing (ABC 2021), during 20–22 October 2021. The book includes works related to the field of vision- and sensor-based human action or activity and behavior analysis and recognition. It covers human activity recognition (HAR), action understanding, gait analysis, gesture recognition, behavior analysis, emotion, and affective computing, and related areas. The book addresses various challenges and aspects of human activity recognition—both in sensor-based and vision-based domains. It can be considered as an excellent treasury related to the human activity and behavior computing.

Download or read book IoT Sensor Based Activity Recognition written by Md Atiqur Rahman Ahad and published by Springer Nature. This book was released on 2020-07-30 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offer clear descriptions of the basic structure for the recognition and classification of human activities using different types of sensor module and smart devices in e.g. healthcare, education, monitoring the elderly, daily human behavior, and fitness monitoring. In addition, the complexities, challenges, and design issues involved in data collection, processing, and other fundamental stages along with datasets, methods, etc., are discussed in detail. The book offers a valuable resource for readers in the fields of pattern recognition, human–computer interaction, and the Internet of Things.

Download or read book Data Analytics and Applications of the Wearable Sensors in Healthcare written by Shabbir Syed-Abdul and published by MDPI. This book was released on 2020-06-17 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal.

Download or read book Human Activity Recognition written by Miguel A. Labrador and published by CRC Press. This book was released on 2013-12-05 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Design and Implement HAR Systems The pervasiveness and range of capabilities of today’s mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sensors and Smartphones focuses on the automatic identification of human activities from pervasive wearable sensors—a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations. Developed from the authors’ nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user’s activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework.

Download or read book Human Activity Recognition Challenge written by Md Atiqur Rahman Ahad and published by Springer Nature. This book was released on 2020-11-20 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces some challenging methods and solutions to solve the human activity recognition challenge. This book highlights the challenge that will lead the researchers in academia and industry to move further related to human activity recognition and behavior analysis, concentrating on cooking challenge. Current activity recognition systems focus on recognizing either the complex label (macro-activity) or the small steps (micro-activities) but their combined recognition is critical for analysis like the challenge proposed in this book. It has 10 chapters from 13 institutes and 8 countries (Japan, USA, Switzerland, France, Slovenia, China, Bangladesh, and Columbia).

Download or read book Contactless Human Activity Recognition written by Brandon Lamont Harrington and published by . This book was released on 2020 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this thesis is to design passive measurement and classification systems to recognize various human activities. Human Activity Recognition (HAR) can enhance a diverse range of human-centric applications in health care, smart homes, and security. Traditional solutions are based on wearable sensors and vision-based technologies; however, these solutions suffer from considerable limitations. The need for users to wear sensors for activity recognition is inconvenient and impractical for long periods of time. Contactless HAR systems have increased the abilities, practicality, and convenience of sensor based HAR systems. It allows for unobtrusive measurement and classification of sedentary behaviors in the workplace such as time spent sitting at desk, to intense physical activities such as at home exercises. This thesis provides contributions to contactless HAR methods and techniques using different sensing modalities. While activity recognition can be achieved with low cost ultrasound sensors, we show the beneficial impact of adopting radio frequency as a technological means of recognizing human activity. Specifically, WiFi signal analysis enables both macro and micro level activity classification. The ubiquity of WiFi infrastructures in home, university, work, and even outdoor environments makes WiFi the most convenient technology to produce valuable contributions in human activity recognition. The primary contributions of this work are: 1) Development of prototype hardware system, Echolocation Activity Detector (EAD), that achieves contactless activity recognition in office setting. 2) A low-cost system that employs WiFi monitoring of packets to provide a student engagement measure, and 3) Design of a non-invasive system that recognizes exercise activity and provides fine-grained repetition counting information of each exercise set using WiFi channel state information. Each of the contributions passively detects and classifies human activity in a contactless fashion without the need of wearable sensors.

Download or read book Assistive Technology Shaping a Sustainable and Inclusive World written by D. Archambault and published by IOS Press. This book was released on 2023-11-09 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Caring about others and the future is part of what makes us human, and it can be argued that improving the lives of people with disabilities improves the lives of all human beings. Most of what we do as a society for people with disabilities also improves life for others, and if we consider a person’s entire life, a disability of some kind will affect almost everybody at some point. This book, Assistive Technology: Shaping a Sustainable and Inclusive World, presents the proceedings of AAATE 2023, the 17th International Conference of the Association for the Advancement of Assistive Technology in Europe, held in Aubervilliers, France, from 30 August to 1 September 2023. For over 30 years, the biennial AAATE conference has focused on research aimed at improving the lives of people with a disability, and has become one of the main platforms for all stakeholders in the field. A total of 123 papers were submitted in the category intended for publication in these conference proceedings, and after a rigorous process involving review by at least three international reviewers, 74 were selected for inclusion here. Topics covered include service delivery of AT; AT for various groups such as older adults, children, and those with cognitive disabilities; mobility; privacy and security issues; and AT to promote inclusion and facilitate participation in education, culture, and work. Providing a comprehensive and current overview, the book will be of interest to researchers, practitioners, manufacturers, decision-makers and providers, users of AT, and anyone else working in the field.

Download or read book Human Activity Sensing written by Nobuo Kawaguchi and published by Springer Nature. This book was released on 2019-09-09 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Activity recognition has emerged as a challenging and high-impact research field, as over the past years smaller and more powerful sensors have been introduced in wide-spread consumer devices. Validation of techniques and algorithms requires large-scale human activity corpuses and improved methods to recognize activities and the contexts in which they occur. This book deals with the challenges of designing valid and reproducible experiments, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating activity recognition systems in the real world with real users.

Download or read book Human Activity Recognition HAR in Healthcare written by Luigi Bibbò and published by . This book was released on 2024-03-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human activity recognition (HAR) is determined through the acquisition of images or kinematic states, which are analyzed by prediction models. The goal of these systems is to correctly classify the data into one of the following categories: gestures, elementary actions that are components of complex activities, human-object or human-human interactions, and group actions. HAR plays a fundamental role in health monitoring systems through the acquisition of information about the health and psychological statuses of subjects. The development of new medical and assistive technologies has created environmental conditions for the independent living among the elderly and has contributed to the improvement of their quality of life. In this Special Issue, we present the constant development of new data, applications and analysis techniques.

Download or read book Towards Robust Realtime Human Activity Recognition Using Wearable Sensors written by Delaram Yazdansepas and published by . This book was released on 2017 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of smartphones and fitness bands that have various sensors such as accelerometers, wearable sensor-based Human Activity Recognition (HAR) systems have gained wide popularity and researchers have proposed numerous techniques for recognition of these activities. Human activity recognition has many applications particularly in health care, cognitive assistance, city planning, indoor localization and tracking, and human-computer interaction. Although there has been some progress, a practical robust HAR system remains elusive because the collected data are affected by several factors such as noise, data alignment, and other constraints. In addition, the variability in the sensing equipment and their displacement is a practical challenge for implementing HAR in real-world applications. This dissertation explores the twin problems of making wearable sensor-based HAR systems robust and real time. Towards enhancing the robustness of ML-based HAR systems, we adopt feature selection methods on time and frequency domain features and apply classifiers for evaluating the recognition performance. We show the effect of different feature sets on each of the classifiers and further demonstrate in our results the impact of decreasing the size of the training set on the accuracy of the classifiers. Towards building an Online HAR system, this thesis explores the concept of Shapelets to avoid complex feature extraction. We propose a procedure to find the most representative shapelet for each activity class based on time series distance metrics and dynamic time warping. Furthermore, we generate a personalized shapelet library database driven from users' activity time series. We evaluate the proposed algorithm and techniques using a dataset comprised of accelerometer readings of 77 individuals performing various activities such as walking/jogging on treadmill, walking on different surfaces, climbing stairs, and non-ambulatory activities. Our experiments demonstrate that by using selected features from the time and frequency domain, we can achieve higher accuracy rates if we limit the training and testing sets to specific age groups. Furthermore, while we mainly use a single hip-worn accelerometer sensor as our sensing device, we show our method could support any wearable accelerometer sensor.

Download or read book Human Activity and Behavior Analysis written by Md Atiqur Rahman Ahad and published by CRC Press. This book was released on 2024-04-29 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects. The book discusses topics such as action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, and related areas. This volume focuses on two main subject areas: Movement and Sensors, and Sports Activity Analysis. The editors are experts in these arenas, and the contributing authors are drawn from high-impact research groups around the world. This book will be of great interest to academics, students, and professionals working and researching in the field of human activity and behavior analysis.

Download or read book Ubiquitous Computing and Ambient Intelligence Sensing Processing and Using Environmental Information written by Juan M. García-Chamizo and published by Springer. This book was released on 2015-12-12 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2015, held in Puerto Varas, Chile, in December 2015. The 36 full papers presented together with 11 short papers were carefully reviewed and selected from 62 submissions. The papers are grouped in topical sections on adding intelligence for environment adaption; ambient intelligence for transport; human interaction and ambient intelligence; and ambient intelligence for urban areas.