Estimating hand-grip forces causing Cumulative Trauma Disorder

Wearable sensors have garnered considerable interest because of their potential for various applications. However, much less has been studied about the Stretchsense pressure sensor characteristics and its workability for industrial application to prevent potential risk situations such as accidents and injuries. The proposed study helps investigate Stretchsense pressure sensors\u27 applicability for measuring hand-handle interface forces under static and dynamic conditions. The BendLabs sensors - a multi-axis, soft, flexible sensing system was attached to the wrist to evaluate the wrist angle deviations. In addition, the StretchSense stretch sensors were attached to the elbow joint to help estimate the elbow flexion/extension. The research tests and evaluates the real-time pressure distribution across the hand while performing given tasks and investigates the relationship between the wrist and elbow position and grip strength. The research provides objective means to assess the magnitudes of high pressures that may cause pressure-induced discomfort and pain, thereby increasing the hand\u27s stress. The experiment\u27s most significant benefit lies in its applicability to the actual tool handles outside the laboratory settings

From wearable towards epidermal computing : soft wearable devices for rich interaction on the skin

Human skin provides a large, always available, and easy to access real-estate for interaction. Recent advances in new materials, electronics, and human-computer interaction have led to the emergence of electronic devices that reside directly on the user's skin. These conformal devices, referred to as Epidermal Devices, have mechanical properties compatible with human skin: they are very thin, often thinner than human hair; they elastically deform when the body is moving, and stretch with the user's skin. Firstly, this thesis provides a conceptual understanding of Epidermal Devices in the HCI literature. We compare and contrast them with other technical approaches that enable novel on-skin interactions. Then, through a multi-disciplinary analysis of Epidermal Devices, we identify the design goals and challenges that need to be addressed for advancing this emerging research area in HCI. Following this, our fundamental empirical research investigated how epidermal devices of different rigidity levels affect passive and active tactile perception. Generally, a correlation was found between the device rigidity and tactile sensitivity thresholds as well as roughness discrimination ability. Based on these findings, we derive design recommendations for realizing epidermal devices. Secondly, this thesis contributes novel Epidermal Devices that enable rich on-body interaction. SkinMarks contributes to the fabrication and design of novel Epidermal Devices that are highly skin-conformal and enable touch, squeeze, and bend sensing with co-located visual output. These devices can be deployed on highly challenging body locations, enabling novel interaction techniques and expanding the design space of on-body interaction. Multi-Touch Skin enables high-resolution multi-touch input on the body. We present the first non-rectangular and high-resolution multi-touch sensor overlays for use on skin and introduce a design tool that generates such sensors in custom shapes and sizes. Empirical results from two technical evaluations confirm that the sensor achieves a high signal-to-noise ratio on the body under various grounding conditions and has a high spatial accuracy even when subjected to strong deformations. Thirdly, Epidermal Devices are in contact with the skin, they offer opportunities for sensing rich physiological signals from the body. To leverage this unique property, this thesis presents rapid fabrication and computational design techniques for realizing Multi-Modal Epidermal Devices that can measure multiple physiological signals from the human body. Devices fabricated through these techniques can measure ECG (Electrocardiogram), EMG (Electromyogram), and EDA (Electro-Dermal Activity). We also contribute a computational design and optimization method based on underlying human anatomical models to create optimized device designs that provide an optimal trade-off between physiological signal acquisition capability and device size. The graphical tool allows for easily specifying design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. Finally, taking a multi-disciplinary perspective, we outline the roadmap for future research in this area by highlighting the next important steps, opportunities, and challenges. Taken together, this thesis contributes towards a holistic understanding of Epidermal Devices}: it provides an empirical and conceptual understanding as well as technical insights through contributions in DIY (Do-It-Yourself), rapid fabrication, and computational design techniques.Die menschliche Haut bietet eine große, stets verfügbare und leicht zugängliche Fläche für Interaktion. Jüngste Fortschritte in den Bereichen Materialwissenschaft, Elektronik und Mensch-Computer-Interaktion (Human-Computer-Interaction, HCI) [so that you can later use the Englisch abbreviation] haben zur Entwicklung elektronischer Geräte geführt, die sich direkt auf der Haut des Benutzers befinden. Diese sogenannten Epidermisgeräte haben mechanische Eigenschaften, die mit der menschlichen Haut kompatibel sind: Sie sind sehr dünn, oft dünner als ein menschliches Haar; sie verformen sich elastisch, wenn sich der Körper bewegt, und dehnen sich mit der Haut des Benutzers. Diese Thesis bietet, erstens, ein konzeptionelles Verständnis von Epidermisgeräten in der HCI-Literatur. Wir vergleichen sie mit anderen technischen Ansätzen, die neuartige Interaktionen auf der Haut ermöglichen. Dann identifizieren wir durch eine multidisziplinäre Analyse von Epidermisgeräten die Designziele und Herausforderungen, die angegangen werden müssen, um diesen aufstrebenden Forschungsbereich voranzubringen. Im Anschluss daran untersuchten wir in unserer empirischen Grundlagenforschung, wie epidermale Geräte unterschiedlicher Steifigkeit die passive und aktive taktile Wahrnehmung beeinflussen. Im Allgemeinen wurde eine Korrelation zwischen der Steifigkeit des Geräts und den taktilen Empfindlichkeitsschwellen sowie der Fähigkeit zur Rauheitsunterscheidung festgestellt. Basierend auf diesen Ergebnissen leiten wir Designempfehlungen für die Realisierung epidermaler Geräte ab. Zweitens trägt diese Thesis zu neuartigen Epidermisgeräten bei, die eine reichhaltige Interaktion am Körper ermöglichen. SkinMarks trägt zur Herstellung und zum Design neuartiger Epidermisgeräte bei, die hochgradig an die Haut angepasst sind und Berührungs-, Quetsch- und Biegesensoren mit gleichzeitiger visueller Ausgabe ermöglichen. Diese Geräte können an sehr schwierigen Körperstellen eingesetzt werden, ermöglichen neuartige Interaktionstechniken und erweitern den Designraum für die Interaktion am Körper. Multi-Touch Skin ermöglicht hochauflösende Multi-Touch-Eingaben am Körper. Wir präsentieren die ersten nicht-rechteckigen und hochauflösenden Multi-Touch-Sensor-Overlays zur Verwendung auf der Haut und stellen ein Design-Tool vor, das solche Sensoren in benutzerdefinierten Formen und Größen erzeugt. Empirische Ergebnisse aus zwei technischen Evaluierungen bestätigen, dass der Sensor auf dem Körper unter verschiedenen Bedingungen ein hohes Signal-Rausch-Verhältnis erreicht und eine hohe räumliche Auflösung aufweist, selbst wenn er starken Verformungen ausgesetzt ist. Drittens, da Epidermisgeräte in Kontakt mit der Haut stehen, bieten sie die Möglichkeit, reichhaltige physiologische Signale des Körpers zu erfassen. Um diese einzigartige Eigenschaft zu nutzen, werden in dieser Arbeit Techniken zur schnellen Herstellung und zum computergestützten Design von multimodalen Epidermisgeräten vorgestellt, die mehrere physiologische Signale des menschlichen Körpers messen können. Die mit diesen Techniken hergestellten Geräte können EKG (Elektrokardiogramm), EMG (Elektromyogramm) und EDA (elektrodermale Aktivität) messen. Darüber hinaus stellen wir eine computergestützte Design- und Optimierungsmethode vor, die auf den zugrunde liegenden anatomischen Modellen des Menschen basiert, um optimierte Gerätedesigns zu erstellen. Diese Designs bieten einen optimalen Kompromiss zwischen der Fähigkeit zur Erfassung physiologischer Signale und der Größe des Geräts. Das grafische Tool ermöglicht die einfache Festlegung von Designpräferenzen und die visuelle Analyse der generierten Designs in Echtzeit, was eine Optimierung durch den Designer im laufenden Betrieb ermöglicht. Experimentelle Ergebnisse zeigen eine hohe quantitative Übereinstimmung zwischen den Vorhersagen des Optimierers und den experimentell erfassten physiologischen Daten. Schließlich skizzieren wir aus einer multidisziplinären Perspektive einen Fahrplan für zukünftige Forschung in diesem Bereich, indem wir die nächsten wichtigen Schritte, Möglichkeiten und Herausforderungen hervorheben. Insgesamt trägt diese Arbeit zu einem ganzheitlichen Verständnis von Epidermisgeräten bei: Sie liefert ein empirisches und konzeptionelles Verständnis sowie technische Einblicke durch Beiträge zu DIY (Do-It-Yourself), schneller Fertigung und computergestützten Entwurfstechniken

Haptic Media Scenes

The aim of this thesis is to apply new media phenomenological and enactive embodied cognition approaches to explain the role of haptic sensitivity and communication in personal computer environments for productivity. Prior theory has given little attention to the role of haptic senses in influencing cognitive processes, and do not frame the richness of haptic communication in interaction design—as haptic interactivity in HCI has historically tended to be designed and analyzed from a perspective on communication as transmissions, sending and receiving haptic signals. The haptic sense may not only mediate contact confirmation and affirmation, but also rich semiotic and affective messages—yet this is a strong contrast between this inherent ability of haptic perception, and current day support for such haptic communication interfaces. I therefore ask: How do the haptic senses (touch and proprioception) impact our cognitive faculty when mediated through digital and sensor technologies? How may these insights be employed in interface design to facilitate rich haptic communication? To answer these questions, I use theoretical close readings that embrace two research fields, new media phenomenology and enactive embodied cognition. The theoretical discussion is supported by neuroscientific evidence, and tested empirically through case studies centered on digital art. I use these insights to develop the concept of the haptic figura, an analytical tool to frame the communicative qualities of haptic media. The concept gauges rich machine- mediated haptic interactivity and communication in systems with a material solution supporting active haptic perception, and the mediation of semiotic and affective messages that are understood and felt. As such the concept may function as a design tool for developers, but also for media critics evaluating haptic media. The tool is used to frame a discussion on opportunities and shortcomings of haptic interfaces for productivity, differentiating between media systems for the hand and the full body. The significance of this investigation is demonstrating that haptic communication is an underutilized element in personal computer environments for productivity and providing an analytical framework for a more nuanced understanding of haptic communication as enabling the mediation of a range of semiotic and affective messages, beyond notification and confirmation interactivity

Sistema de miografia óptica para reconhecimento de gestos e posturas de mão

Orientador: Éric FujiwaraDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia MecânicaResumo: Nesse projeto, demonstrou-se um sistema de miografia óptica como uma alternativa promissora para monitorar as posturas da mão e os gestos do usuário. Essa técnica se fundamenta em acompanhar as atividades musculares responsáveis pelos movimentos da mão com uma câmera externa, relacionando a distorção visual verificada no antebraço com a contração e o relaxamento necessários para dada postura. Três configurações de sensores foram propostas, estudadas e avaliadas. A primeira propôs monitorar a atividade muscular analisando a variação da frequência espacial de uma textura de listras uniformes impressa sobre a pele, enquanto que a segunda se caracteriza pela contagem de pixels de pele visível dentro da região de interesse. Ambas as configurações se mostraram inviáveis pela baixa robustez e alta demanda por condições experimentais controladas. Por fim, a terceira recupera o estado da mão acompanhando o deslocamento de uma série de marcadores coloridos distribuídos ao longo do antebraço. Com um webcam de 24 fps e 640 × 480 pixels, essa última configuração foi validada para oito posturas distintas, explorando principalmente a flexão e extensão dos dedos e do polegar, além da adução e abdução do último. Os dados experimentais, adquiridos off-line, são submetidos a uma rotina de processamento de imagens para extrair a informação espacial e de cor dos marcadores em cada quadro, dados esses utilizados para rastrear os mesmos marcadores ao longo de todos os quadros. Para reduzir a influência das vibrações naturais e inerentes ao corpo humano, um sistema de referencial local é ainda adotado dentro da própria região de interesse. Finalmente, os dados quadro a quadro com o ground truth são alimentados a uma rede neural artificial sequencial, responsável pela calibração supervisionada do sensor e posterior classificação das posturas. O desempenho do sistema para a classificação das oito posturas foi avaliado com base na validação cruzada com 10-folds, com a câmera monitorando o antebraço pela superfície interna ou externa. O sensor apresentou uma precisão de ?92.4% e exatidão de ?97.9% para o primeiro caso, e uma precisão de ?75.1% e exatidão de ?92.5% para o segundo, sendo comparável a outras técnicas de miografia, demonstrando a viabilidade do projeto e abrindo perspectivas para aplicações em interfaces humano-robôAbstract: In this work, an optical myography system is demonstrated as a promising alternative to monitor hand posture and gestures of the user. This technique is based on accompanying muscular activities responsible for hand motion with an external camera, and relating the visual deformation observed on the forearm to the muscular contractions/relaxations for a given posture. Three sensor designs were proposed, studied and evaluated. The first one intended to monitor muscular activity by analyzing the spatial frequency variation of a uniformly distributed stripe pattern stamped on the skin, whereas the second one is characterized by reckoning visible skin pixels inside the region of interest. Both designs are impracticable due to their low robustness and high demand for controlled experimental conditions. At last, the third design retrieves hand configuration by tracking visually the displacements of a series of color markers distributed over the forearm. With a webcam of 24 fps and 640 × 480 pixels, this design was validated for eight different postures, exploring fingers and thumb flexion/extension, plus thumb adduction/abduction. The experimental data are acquired offline and, then, submitted to an image processing routine to extract color and spatial information of the markers in each frame; the extracted data is subsequently used to track the same markers along all frames. To reduce the influence of human body natural and inherent vibrations, a local reference frame is yet adopted in the region of interest. Finally, the frame by frame data, along with the ground truth posture, are fed into a sequential artificial neural network, responsible for sensor supervised calibration and subsequent posture classification. The system performance was evaluated in terms of eight postures classification via 10-fold cross-validation, with the camera monitoring either the underside or the back of the forearm. The sensor presented a ?92.4% precision and ?97.9% accuracy for the former, and a ?75.1% precision and ?92.5% accuracy for the latter, being thus comparable to other myographic techniques; it also demonstrated that the project is feasible and offers prospects for human-robot interaction applicationsMestradoEngenharia MecanicaMestre em Engenharia Mecânica33003017CAPE

Surface Electromyographic (sEMG) Transduction of Hand Joint Angles for Human Interfacing Devices (HID)

This is an investigation of the use of surface electromyography (sEMG) as a tool to improve human interfacing devices (HID) information bandwidth through the transduction of the fingertip workspace. It combines the work of Merletti et al and Jarque-Bou et al to design an open-source framework for Fingertip Workspace based Human Interfacing Devices (HID). In this framework, the fingertip workspace is defined as the system of forearm and hand muscle force through a tensor which describes hand anthropometry. The thesis discusses the electrophysiology of muscle tissue along with the anatomy and physiology of the arm in pursuit of optimizing sensor location, muscle force measurements, and viable command gestures. Algorithms for correlating sEMG to hand joint angle are investigated using MATLAB for both static and moving gestures. Seven sEMG spots and Fingertip Joint Angles recorded by Jarque Bou et al are investigated for the application of sEMG to Human Interfacing Devices (HID). Such technology is termed Gesture Computer Interfacing (GCI) and has been shown feasible through devices such as CTRL Labs interface, and models such as those of Sartori, Merletti, and Zhao. Muscles under sEMG spots in this dataset and the actions related to them are discussed, along with what muscles and hand actions are not visible within this dataset. Viable gestures for detection algorithms are discussed based on the muscles discerned to be visible in the dataset through intensity, spectral moment, power spectra, and coherence. Detection and isolation of such viable actions is fundamental to designing an EMG driven musculoskeletal model of the hand needed to facilitate GCI. Enveloping, spectral moment, power spectrum, and coherence analysis are applied to a Sollerman Hand Function Test sEMG dataset of twenty-two subjects performing 26 activities of living to differentiate pinching and grasping tasks. Pinches and grasps were found to cause very different activation patterns in sEMG spot 3 relating to flexion of digits I - V. Spectral moment was found to be less correlated with differentiation and provided information about the degree of object manipulation performed and extent of fatigue during each task. Coherence was shown to increase between flexors and extensors with intensity of task but was found corrupted by crosstalk with increasing intensity of muscular activation. Some spectral results correlated between finger flexor and extensor power spectra showed anticipatory coherence between the muscle groups at the end of object manipulation. An sEMG amplification system capable of capturing HD-sEMG with a bandwidth of 300 and 500 Hz at a sampling frequency of 2 kHz was designed for future work. The system was designed in ordinance with current IEEE research on sensor-electrode characteristics. Furthermore, discussion of solutions to open issues in HD-sEMG is provided. This work did not implement the designed wristband but serves as a literature review and open-source design using commercially available technologies

A REVIEW OF FACTORS, SEATING DESIGN, AND SHAPE CAPTURE METHODS FOR REDUCING PRESSURE INJURY RISK

This dissertation in the form of three papers ready for submission to peer-reviewed journals is submitted toward the requirements of the PhD in Health Related Sciences program at Virginia Commonwealth University. Chapter One provides an introductory overview of the project, including: (a) an overview of pressure injuries, (b) the impact of seating as an intervention, and (c) aims of the three-paper dissertation in addressing various aspects of pressure injury prevention. Each paper is unique and singular in its focus, yet all share the overlying aim of addressing pressure injury risk associated with wheelchair seating. Paper One describes the unique facilitators and barriers associated with pressure injury prevention practices among individuals with upper motor neuron lesions. Paper Two consists of a systematic review of the literature on the comparative effectiveness of various wheelchair seat cushions in reducing pressure injuries. Paper Three presents the results of a pilot study of a unique shape-capture method for custom-fitted wheelchair cushions conducted by the student researcher

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

Evaluation of a Soft Robotic Knee Exosuit for Assistance in Stair Ascent

abstract: Muscular weakness is a common manifestation for Stroke survivors and for patients with Anterior Cruciate Ligament reconstruction leading to reduced functional independence, especially mobility. Several rigid orthotic devices are being designed to assist mobility. However, limitations in majority of these devices are: 1) that they are constrained only to level walking applications, 2) are mostly bulky and rigid lacking user comfort. For these reasons, rehabilitation using soft-robotics can serve as a powerful modality in gait assistance and potentially accelerate functional recovery. The characteristics of soft robotic exosuit is that it’s more flexible, delivers high power to weight ratio, and conforms with the user’s body structure making it a suitable choice. This work explores the implementation of an existing soft robotic exosuit in assisting knee joint mechanism during stair ascent for patients with muscular weakness. The exosuit assists by compensating the lack of joint moment and minimizing the load on the affected limb. It consists of two I-cross-section soft pneumatic actuators encased within a sleeve along with insole sensor shoes and control electronics. The exosuit actuators were mechanically characterized at different angles, in accordance to knee flexion in stair gait, to enable the generation of the desired joint moments. A linear relation between the actuator stiffness and internal pressure as a function of the knee angle was obtained. Results from this characterization along with the insole sensor outputs were used to provide assistance to the knee joint. Analysis of stair gait with and without the exosuit ‘active’ was performed, using surface electromyography (sEMG) sensors, for two healthy participants at a slow walking speed. Preliminary user testing with the exosuit presented a promising 16% reduction in average muscular activity of Vastus Lateralis muscle and a 3.6% reduction on Gluteus Maximus muscle during the stance phase and unrestrained motion during the swing phase of ascent thereby demonstrating the applicability of the soft-inflatable exosuit in rehabilitation.Dissertation/ThesisMasters Thesis Biomedical Engineering 201

Human Health Engineering Volume II

In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being