100 research outputs found

    Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

    Get PDF
    Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

    Footfall energy harvesting : footfall energy harvesting conversion mechanisms

    Get PDF
    Ubiquitous computing and pervasive networks are prevailing to impact almost every part of our daily lives. Convergence of technologies has allowed electronic devices to become untethered. Cutting of the power-cord and communications link has provided many benefits, mobility and convenience being the most advantageous, however, an important but lagging technology in this vision is the power source. The trend in power density of batteries has not tracked the advancements in electronic systems development. This has provided opportunity for a bridging technology which uses a more integrated approach with the power source to emerge, where a device has an onboard self sustaining energy supply. This approach promises to close the gap between the increased miniaturisation of electronics systems and the physically constrained battery technology by tapping into the ambient energy available in the surrounding location of an application. Energy harvesting allows some of the costly maintenance and environmentally damaging issues of battery powered systems to be reduced.This work considers the characteristics and energy requirements of wireless sensor and actuator networks. It outlines a range of sources from which the energy can be extracted and then considers the conversion methods which could be employed in such schemes. This research looks at the methods and techniques for harvesting/scavenging energy from ambient sources, in particular from the motion of human traffic on raised flooring and stairwells for the purpose of powering wireless sensor and actuator networks. Mechanisms for the conversion of mechanical energy to electrical energy are evaluated for their benefits in footfall harvesting, from which, two conversion mechanisms are chosen for prototyping.The thesis presents two stair-mounted generator designs. Conversion that extends the intermittent pulses of energy in footfall is shown to be the beneficial. A flyback generator is designed which converts the linear motion of footfall to rotational torque is presented. Secondly, a cantilever design which converts the linear motion to vibration is shown. Both designs are mathematically modelled and the behaviour validated with experimental results & analysis. Power, energy and efficiency characteristics for both mechanisms are compared. Cost of manufacture and reliability are also discussed

    Latest research trends in gait analysis using wearable sensors and machine learning: a systematic review

    Get PDF
    Gait is the locomotion attained through the movement of limbs and gait analysis examines the patterns (normal/abnormal) depending on the gait cycle. It contributes to the development of various applications in the medical, security, sports, and fitness domains to improve the overall outcome. Among many available technologies, two emerging technologies that play a central role in modern day gait analysis are: A) wearable sensors which provide a convenient, efficient, and inexpensive way to collect data and B) Machine Learning Methods (MLMs) which enable high accuracy gait feature extraction for analysis. Given their prominent roles, this paper presents a review of the latest trends in gait analysis using wearable sensors and Machine Learning (ML). It explores the recent papers along with the publication details and key parameters such as sampling rates, MLMs, wearable sensors, number of sensors, and their locations. Furthermore, the paper provides recommendations for selecting a MLM, wearable sensor and its location for a specific application. Finally, it suggests some future directions for gait analysis and its applications

    Theoretical Approaches in Non-Linear Dynamical Systems

    Get PDF
    From Preface: The 15th International Conference „Dynamical Systems - Theory and Applications” (DSTA 2019, 2-5 December, 2019, Lodz, Poland) gathered a numerous group of outstanding scientists and engineers who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without great effort of the staff of the Department of Automation, Biomechanics and Mechatronics of the Lodz University of Technology. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our event was attended by over 180 researchers from 35 countries all over the world, who decided to share the results of their research and experience in different fields related to dynamical systems. This year, the DSTA Conference Proceedings were split into two volumes entitled „Theoretical Approaches in Non-Linear Dynamical Systems” and „Applicable Solutions in Non-Linear Dynamical Systems”. In addition, DSTA 2019 resulted in three volumes of Springer Proceedings in Mathematics and Statistics entitled „Control and Stability of Dynamical Systems”, „Mathematical and Numerical Approaches in Dynamical Systems” and „Dynamical Systems in Mechatronics and Life Sciences”. Also, many outstanding papers will be recommended to special issues of renowned scientific journals.Cover design: Kaźmierczak, MarekTechnical editor: Kaźmierczak, Mare

    Advance in Energy Harvesters/Nanogenerators and Self-Powered Sensors

    Get PDF
    This reprint is a collection of the Special Issue "Advance in Energy Harvesters/Nanogenerators and Self-Powered Sensors" published in Nanomaterials, which includes one editorial, six novel research articles and four review articles, showcasing the very recent advances in energy-harvesting and self-powered sensing technologies. With its broad coverage of innovations in transducing/sensing mechanisms, material and structural designs, system integration and applications, as well as the timely reviews of the progress in energy harvesting and self-powered sensing technologies, this reprint could give readers an excellent overview of the challenges, opportunities, advancements and development trends of this rapidly evolving field

    Classifying gait alterations using an instrumented smart sock and deep learning

    Get PDF
    This paper presents a non-invasive method of classifying gait patterns associated with various movement disorders and/or neurological conditions, utilising unobtrusive, instrumented socks and a deep learning network. Seamless instrumented socks were fabricated using three accelerometer embedded yarns, positioned at the toe (hallux), above the heel and on the lateral malleolus. Human trials were conducted on 12 able-bodied participants, an instrumented sock was worn on each foot. Participants were asked to complete seven trials consisting of their typical gait and six different gait types that mimicked the typical movement patterns associated with various movement disorders and neurological conditions. Four Neural Networks and an SVM were tested to ascertain the most effective method of automatic data classification. The Bi-LSTM generated the most accurate results and illustrates that the use of three accelerometers per foot increased classification accuracy compared to a single accelerometer per foot by 11.4%. When only a single accelerometer was utilised for classification, the ankle accelerometer generated the most accurate results in comparison to the other two. The network was able to correctly classify five different gait types: stomp (100%), shuffle (66.8%), diplegic (66.6%), hemiplegic (66.6%) and “normal walking” (58.0%). The network was incapable of correctly differentiating foot slap (21.2%) and steppage gait (4.8%). This work demonstrates that instrumented textile socks incorporating three accelerometer yarns were capable of generating sufficient data to allow a neural network to distinguish between specific gait patterns. This may enable clinicians and therapists to remotely classify gait alterations and observe changes in gait during rehabilitation

    Foot Motion-Based Falling Risk Evaluation for Patients with Parkinson’s Disease

    Get PDF
    Parkinson’s disease (PD) affects motor functionalities, which are closely associated with increased risks of falling and decreased quality of life. However, there is no easy-to-use definitive tools for PD patients to quantify their falling risks at home. To address this, in this dissertation, we develop Monitoring Insoles (MONI) with advanced data processing techniques to score falling risks of PD patients following Falling Risk Questionnaire (FRQ) developed by the U.S. Centers for Disease Control and Prevention (CDC). To achieve this, we extract motion tasks from daily activities and select the most representative features associated with PD that facilitate accurate falling risk scoring. To address the challenge in uncontrolled daily life environments and to identify the most representative features associated with PD and falling risks, the proposed data processing method firstly recognizes foot motions such as walking and toe tapping from continuous movements with stride detection and fast labeling framework, and then extracts time-axis and acceleration-axis features from the motion tasks, at the end provides a score of falling risks using regression. The data processing method can be integrated into a mobile game to be used at home with MONI. The main contributions of this dissertation includes: (i) developing MONI as a low power solution for daily life use; (ii) utilizing stride detection and developing fast labeling framework for motion recognition that improves recognition accuracy for daily life applications; (iii) analyzing two walking and two toe tapping tasks that are close to real life scenarios and identifying important features associated with PD and falling risks; (iv) providing falling scores as quantitative evaluation to PD patients in daily life through simple foot motion tasks and setups

    Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

    Get PDF
    This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version

    15th Conference on Dynamical Systems Theory and Applications DSTA 2019 ABSTRACTS

    Get PDF
    From Preface: This is the fifteen time when the conference „Dynamical Systems – Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and the Ministry of Science and Higher Education. It is a great pleasure that our invitation has been accepted by so many people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcome nearly 255 persons from 47 countries all over the world. They decided to share the results of their research and many years experiences in the discipline of dynamical systems by submitting many very interesting papers. This booklet contains a collection of 338 abstracts, which have gained the acceptance of referees and have been qualified for publication in the conference edited books.Technical editor and cover design: Kaźmierczak, MarekCover design: Ogińska, Ewelina; Kaźmierczak, Mare
    corecore