Modelado de sensores piezoresistivos y uso de una interfaz basada en guantes de datos para el control de impedancia de manipuladores robóticos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Arquitectura de Computadores y Automática, leída el 21-02-2014Sección Deptal. de Arquitectura de Computadores y Automática (Físicas)Fac. de Ciencias FísicasTRUEunpu

Recent Advances in Motion Analysis

The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application

Impact of Ear Occlusion on In-Ear Sounds Generated by Intra-oral Behaviors

We conducted a case study with one volunteer and a recording setup to detect sounds induced by the actions: jaw clenching, tooth grinding, reading, eating, and drinking. The setup consisted of two in-ear microphones, where the left ear was semi-occluded with a commercially available earpiece and the right ear was occluded with a mouldable silicon ear piece. Investigations in the time and frequency domains demonstrated that for behaviors such as eating, tooth grinding, and reading, sounds could be recorded with both sensors. For jaw clenching, however, occluding the ear with a mouldable piece was necessary to enable its detection. This can be attributed to the fact that the mouldable ear piece sealed the ear canal and isolated it from the environment, resulting in a detectable change in pressure. In conclusion, our work suggests that detecting behaviors such as eating, grinding, reading with a semi-occluded ear is possible, whereas, behaviors such as clenching require the complete occlusion of the ear if the activity should be easily detectable. Nevertheless, the latter approach may limit real-world applicability because it hinders the hearing capabilities.</p

Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization

In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoãoManuel R.S. Tavares, Ed.). The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging. In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place. We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

Health State Estimation

Life's most valuable asset is health. Continuously understanding the state of our health and modeling how it evolves is essential if we wish to improve it. Given the opportunity that people live with more data about their life today than any other time in history, the challenge rests in interweaving this data with the growing body of knowledge to compute and model the health state of an individual continually. This dissertation presents an approach to build a personal model and dynamically estimate the health state of an individual by fusing multi-modal data and domain knowledge. The system is stitched together from four essential abstraction elements: 1. the events in our life, 2. the layers of our biological systems (from molecular to an organism), 3. the functional utilities that arise from biological underpinnings, and 4. how we interact with these utilities in the reality of daily life. Connecting these four elements via graph network blocks forms the backbone by which we instantiate a digital twin of an individual. Edges and nodes in this graph structure are then regularly updated with learning techniques as data is continuously digested. Experiments demonstrate the use of dense and heterogeneous real-world data from a variety of personal and environmental sensors to monitor individual cardiovascular health state. State estimation and individual modeling is the fundamental basis to depart from disease-oriented approaches to a total health continuum paradigm. Precision in predicting health requires understanding state trajectory. By encasing this estimation within a navigational approach, a systematic guidance framework can plan actions to transition a current state towards a desired one. This work concludes by presenting this framework of combining the health state and personal graph model to perpetually plan and assist us in living life towards our goals.Comment: Ph.D. Dissertation @ University of California, Irvin

A novel transparent and flexible pressure sensor for the human machine interface

The movement towards flexible and transparent electronics for use in displays, electronic skins, musical instruments and automotive industries, demands electrical components such as pressure sensors to evolve alongside circuitry and electrodes to ensure a fully flexible and transparent system. In the past, piezoresistive pressure sensors made with flexible electrodes have been fabricated, however, many of these systems are opaque. For the first time, we present a technology that exploits the natural self-assembly of polystyrene nanospheres to reproducibly create nanostructured materials to be used in optically transparent pressure sensors with sensing performance comparable to opaque industry standards. The performance of the piezoresistive pressure sensor relies on uniform elastic nano-dome arrays. A thin and homogeneous lining of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) renders the domes conductive and retains the transparent and flexible qualities of the underlying polymer. The film transparency is primarily dependant on PEDOT:PSS film thickness where transparencies as high as 79.3 \% are achieved for films of less than 100 nm in thickness. The sensors demonstrate a resistance response across the force range appropriate for all human machine interface interactions, which correspond here to 0.07 to 26 N. The fabrication process involves the creation of an electroactive mould which is used to create nanostructred polymer layers. To enable mould reuse and enhance process efficiency, an anti-adhesive treatment in the form of a self-assembled monolayer of alkanethiols has been developed. Three chain lengths for the alkanethiol of chemical structure H$_{3}$C-(CH$_{2}$)$_{n}$-SH where n = 3, 5, and 11 are investigated and SAM functionalisation is confirmed with XPS. Peel tests prove that all three are effective at preventing adhesion between the mould and PEDOT:PSS and the treatment is shown not to be detrimental to the polymer electrodeposition process. An adapted fabrication procedure with custom designed electrode housing enables larger samples to be created for prototype devices. A simple functional prototype in the form of a multi-pixel force sensor atop of an LED display is successfully designed and fabricated to highlight the technology for use at the human machine interface.Open Acces

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research