1,930 research outputs found

    Texture recognition using force sensitive resistors

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    This paper presents the results of an experiment that inves- tigates the presence of cues in the signal generated by a low-cost force sensitive resistor (FSR) to recognise surface texture. The sensor is moved across the surface and the data is analysed to investigate the presence of any patterns. We show that the signal contain enough information to recognise at least one sample surface

    W-FYD: a Wearable Fabric-based Display for Haptic Multi-Cue Delivery and Tactile Augmented Reality

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    Despite the importance of softness, there is no evidence of wearable haptic systems able to deliver controllable softness cues. Here, we present the Wearable Fabric Yielding Display (W-FYD), a fabric-based display for multi-cue delivery that can be worn on user's finger and enables, for the first time, both active and passive softness exploration. It can also induce a sliding effect under the finger-pad. A given stiffness profile can be obtained by modulating the stretching state of the fabric through two motors. Furthermore, a lifting mechanism allows to put the fabric in contact with the user's finger-pad, to enable passive softness rendering. In this paper, we describe the architecture of W-FYD, and a thorough characterization of its stiffness workspace, frequency response and softness rendering capabilities. We also computed device Just Noticeable Difference in both active and passive exploratory conditions, for linear and non-linear stiffness rendering as well as for sliding direction perception. The effect of device weight was also considered. Furthermore, performance of participants and their subjective quantitative evaluation in detecting sliding direction and softness discrimination tasks are reported. Finally, applications of W-FYD in tactile augmented reality for open palpation are discussed, opening interesting perspectives in many fields of human-machine interaction

    Tactile Arrays for Virtual Textures

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    This thesis describes the development of three new tactile stimulators for active touch, i.e. devices to deliver virtual touch stimuli to the fingertip in response to exploratory movements by the user. All three stimulators are designed to provide spatiotemporal patterns of mechanical input to the skin via an array of contactors, each under individual computer control. Drive mechanisms are based on piezoelectric bimorphs in a cantilever geometry. The first of these is a 25-contactor array (5 × 5 contactors at 2 mm spacing). It is a rugged design with a compact drive system and is capable of producing strong stimuli when running from low voltage supplies. Combined with a PC mouse, it can be used for active exploration tasks. Pilot studies were performed which demonstrated that subjects could successfully use the device for discrimination of line orientation, simple shape identification and line following tasks. A 24-contactor stimulator (6 × 4 contactors at 2 mm spacing) with improved bandwidth was then developed. This features control electronics designed to transmit arbitrary waveforms to each channel (generated on-the-fly, in real time) and software for rapid development of experiments. It is built around a graphics tablet, giving high precision position capability over a large 2D workspace. Experiments using two-component stimuli (components at 40 Hz and 320 Hz) indicate that spectral balance within active stimuli is discriminable independent of overall intensity, and that the spatial variation (texture) within the target is easier to detect at 320 Hz that at 40 Hz. The third system developed (again 6 × 4 contactors at 2 mm spacing) was a lightweight modular stimulator developed for fingertip and thumb grasping tasks; furthermore it was integrated with force-feedback on each digit and a complex graphical display, forming a multi-modal Virtual Reality device for the display of virtual textiles. It is capable of broadband stimulation with real-time generated outputs derived from a physical model of the fabric surface. In an evaluation study, virtual textiles generated from physical measurements of real textiles were ranked in categories reflecting key mechanical and textural properties. The results were compared with a similar study performed on the real fabrics from which the virtual textiles had been derived. There was good agreement between the ratings of the virtual textiles and the real textiles, indicating that the virtual textiles are a good representation of the real textiles and that the system is delivering appropriate cues to the user

    Development of a surrogate bruising detection system to describe potential bruising patterns associated with common childhood falls.

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    Child abuse is a leading cause of fatality in children aged 0-4 years. An estimated 1,700 children die annually as a result of child abuse of which threequarters (75.7%) of the children were younger than 4 years old1. Infants (younger than 1 year) had the highest rate of fatalities among the group. Many of the serious injuries and fatalities could have potentially been prevented if clinicians and child protective services were able to better distinguish between injuries associated with abuse versus those caused by accidents. Missed cases of child abuse have been shown to be as high as 71% of all admitted cases, where children are presented at hospitals for their injuries and not evaluated as being abused 2. Additionally, when child abuse is legally pursued for criminal charges, a little more than half of the cases move forward to prosecution as opposed to being screened out for reasons including the need for further investigation or insufficient evidence 3. Therefore there is a need to provide clinicians, child protective services and law enforcement personnel with improved knowledge related to the types of injuries that are possible from common household accidents that are often reported to be the underlying cause of injury in child abuse. Bruising is an early sign of abuse, and can be an effective indicator of child abuse. Although not life threatening, bruising injuries or bruising patterns provide a “roadmap” documenting a child’s exposure to impact. Previous research has relied upon the use of instrumented anthropomorphic test devices, or test dummies, to investigate injury risk in common childhood falls and accidents in addition to head injury and bone fracture risk in children 4-7. However, the ability to predict bruising patterns occurring in association with falsely reported events in child abuse does not exist, and could prove extremely useful in the distinction between abusive and accidental injuries. This study required the modification of an existing pediatric test dummy to allow for the prediction of potential bruising locations and bruising patterns in children during common household fall events that are often stated as false scenarios in child abuse. The scope of this project included the development of a “sensing skin” that was adapted to a commercial pediatric test dummy. This modified test dummy was then used in mock laboratory experiments replicating common household injury events while the “sensing skin” measured and recorded levels of impact force and locations of impact on the human surrogate. The data from the “sensing skin” was acquired and compiled in a computerized visual body map image displaying the areas of contact or impact locations. This body map image provided a “roadmap” of the human surrogate’s contact exposure during the specific fall event and defined a compatible impact roadmap–specific event combination. Impact roadmap–event combinations for various common household falls provide an indication of where potential bruising could occur. This knowledge of potential bruising patterns could aid clinicians in distinguishing between abusive and accidental injuries for specific fall types

    Advanced Knowledge Application in Practice

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    The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

    The 3rd International Conference on the Challenges, Opportunities, Innovations and Applications in Electronic Textiles

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    This reprint is a collection of papers from the E-Textiles 2021 Conference and represents the state-of-the-art from both academia and industry in the development of smart fabrics that incorporate electronic and sensing functionality. The reprint presents a wide range of applications of the technology including wearable textile devices for healthcare applications such as respiratory monitoring and functional electrical stimulation. Manufacturing approaches include printed smart materials, knitted e-textiles and flexible electronic circuit assembly within fabrics and garments. E-textile sustainability, a key future requirement for the technology, is also considered. Supplying power is a constant challenge for all wireless wearable technologies and the collection includes papers on triboelectric energy harvesting and textile-based water-activated batteries. Finally, the application of textiles antennas in both sensing and 5G wireless communications is demonstrated, where different antenna designs and their response to stimuli are presented

    Artificial Tactile System and Signal Processing for Haptic applications

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    Human have the ability to interact with the external environment through five main senses which are vision, hearing, smell, taste and touch. Most of all, the sensation like vision or hearing have been well developed and the use of various applications like TV, Camera, or artificial cochlear have been widely generalized. As the next steps, recently, the tactile sensor to mimic the tactile system of human have been attracted by many groups. Especially, after the development of Apple’s iPhone, the public interest about touch sensing applications have been increased explosively. Other researches for tactile sensing have focused on enhancing the performance of tactile sensor like the sensitivity, stability, response time and so on. As a result, there are some researches that the sensor performance of certain criteria is better than that of human tactile system. However, a human tactile system is not only very sensitive but also complex. In other words, ultimately, the tactile system mimicking the human tactile sensation should detect various parameters such as the pressure, temperature, hardness or roughness and also decide the psychological feeling like the pain by a hot material in touching or the smooth/roughness feeling in sliding the certain material. Therefore, in this thesis, it has been studied for the development of multifunctional tactile sensing system detecting various tactile parameters and deciding the kinds of psychological tactile feeling by measured stimulation. As the first step for the development of tactile system, we have studied the tactile sensor using ZnO nanowire. Therefore, in this chapter, the basic characteristics of ZnO nanowire are investigated to confirm the possibility for the tactile sensor. In addition, structural design factors of sensor units have been studied in order to enhance the sensitivity of ZnO nanowire-based tactile sensor. We have primarily demonstrated the effect of a square pattern array design in a pressure sensor using ZnO nanowires. Nanowires grown on the edge of cells can be bent easily because of growth direction, density of nanowires, and buckling effect. Since smaller square pattern arrays induce a higher circumference to cell area ratio, if one sensor unit consists of many micro-level square pattern arrays, the design enhances the piezoelectric efficiency and the sensitivity. As a result, 20um × 20um cell arrays showed three times higher pressure sensitivity than 250um × 250um cell array structures at a pressure range from 4kPa to 14kPa. The induced piezoelectric voltage with the same pressure level also increased drastically. Therefore, the smaller pattern array design is more appropriate for a high-sensitive pressure sensor than a simple one-body cell design for tactile systems, and it has the advantage of better power efficiency, which is also important for artificial tactile systems. Even if, in previous experiments, the possibility of piezoelectric materials as the tactile sensor and the method for the enhancement of pressure sensitivity are confirmed well, the tactile sensor for mimicking the human tactile sensation should measure various parameters as well as the pressure. However, many studies about ‘smooth-rough’ sensation depend on the machine learning technology with simple tactile sensors rather than developing the sensors that can measure various parameters like surface topography, hardness, quality of materials at the same time. Therefore, after the development of the pressure sensor, specific structures based on PDMS are proposed to measure and analyze above-mentioned parameters related to ‘smooth-rough’ decision, as like fingerprint of human. To find the optimized structure, three kinds of the structure shape (cone, cylinder and dome) are fabricated and the pressure sensitivity according to the shape are also measured. FEM simulation is also carried out to support the experimental result. Our tactile sensor with optimized dome structure (500um height) provides high shear force sensitivity, fast response time, stability, and durability. The high sensitivity about the shear force enables better the tactile sensor to measure the various surface information such as the pitch of pattern, the depth, the sliding velocity, the hardness and so on. In addition, after the study to measure the various surface information by dome structure, the research to measure the other surface information is also followed. In our previous study, we confirmed that the surface topography can be reconstructed by mapping the piezoelectric signals according to the location. In this research, to reduce the number of measurements from dozens to once and minimize the data loss at the empty space between adjacent sensors, the electrode array of Zig-Zag type is applied to the tactile sensor. As a result, with just one measurement, the surface topography of broad region can be successfully reconstructed by our tactile sensor as the high-resolution image. Additionally, the temperature sensor based on the resistive mechanism is fabricated between the Zig-Zag electrode lines to measures the temperature of surface materials when the tactile sensor rubs on the materials in real time. Over the development of the tactile sensing applications, the demand for an artificial system like human tactile sensation have been much more increased. Therefore, in this study, as a surrogate for human tactile sensation, we propose an artificial tactile sensing system based on the developed sensors in previous sections. For this, the piezoelectric tactile signal generated by touching and rubbing the material is transferred to DAQ system connected with our tactile sensor. First, the system decides whether the contacted material is dangerous or not. If dangerous like sharp or hot materials, the warning signal is generated by our artificial tactile system. If not, the sensor connected with the system rubs the materials and detects the roughness of the materials. Especially, the human test data related to ‘soft-rough’ detection is applied to a deep learning structure allowing personalization of the system, because tactile responses vary among humans. This approach could be applied to electronic devices with tactile emotional exchange capabilities, as well as various advanced digital experiences. In this thesis, human-like tactile sensing system based on the piezoelectric effect is successfully confirmed through various experiments. Although there are still some issues that need to be improved, this research is expected to be fundamental results for human-like tactile sensing system detecting a variety of the parameters such as the pressure, temperature, surface morphology, hardness, roughness and so on. In the future, through collaborative research with other fields like brain science, signal processing, we hope that this research can mimic psychological tactile sensations and communicate emotional exchange with external environment like real human skin.YList of Contents Abstract i List of contents iii List of tables vi List of figures vii Ⅰ. INTRODUCTION 1 1.1 Motivation 1 1.2 Various transduction mechanisms for the tactile sensor 5 1.2.1 Capacitive mechanism 5 1.2.2 Resistive mechanism 6 1.2.3 Triboelectric effect 7 1.2.4 Piezoelectric effect 9 1.3 Objectives 12 1.4 Reference 13 II. BASIC CHARACTERISTICS AND THE METHOD FOR ENHANC-ING THE PRESSURE SENSITIVITY OF THE TACTILE SENSOR BASED ON ZnO NANOWIRE 19 2.1 Introduction 19 2.2 Basic characteristics of ZnO nanowire 22 2.3 Device Fabrication 31 2.4 Morphological and Electrical characteristics 33 2.5 Pattern structure for enhanced for pressure sensitivity 38 2.6 Simulation result of piezoelectric effect for pattern structure 42 2.7 Reference 46 III. DOME STRUCTURE TO MEAUSRE THE SURFACE INFOR-MATION 52 3.1 Introduction 52 3.2 Basic characteristics of P(VDF-TrFE) 53 3.3 Device fabrication 61 3.4 Interaction mechanism between dome structure and surface material 63 3.5 Simulation and Experimental result comparing cone, cylinder, and dome structure 64 3.6 Simulation and Experimental result of the sensitivity enhancement ef-fect by dome structure 66 3.7 Depth measurement by tactile sensor with dome structure 72 3.8 Pattern of pitch by multi-array tactile sensor with dome structure 77 3.9 Hardness measurement by the tactile sensor with dome structure 79 3.10 Reference 83 IV. ZIG-ZAG ARRAYED TACTILE SENSOR BASED ON PIEZOE-LECTRIC-RESISTIVE MECHANISM TO DETECT THE SURFACE TOPOG-RAPHY AND TEMPERATURE 87 4.1 Introduction 87 4.2 Device fabrication 88 4.3 Piezoelectric characteristics of fabricated tactile sensor 90 4.4 Surface rendering method by the piezoelectric effect 95 4.5 Surface rendering result of 3D printed materials 96 4.6 Temperature sensing in sliding the high temperature material on Zig-Zag tactile sensor 99 4.7 Reference 103 V. TACTILE SENSING SYSTEM FOR PAIN AND SMOOTH/ROUGH DETECTION 105 5.1 Introduction 105 5.2 Components of the tactile sensing system 107 5.3 Artificial tactile sensing system for generating the pain warning 108 5.4 Artificial tactile sensing system for smooth/rough sensing 112 5.5 Reference 117 VⅠ. CONCLUSION 120DoctordCollectio
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