Texture recognition using force sensitive resistors

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

A Survey on 3D Ultrasound Reconstruction Techniques

This book chapter aims to discuss the 3D ultrasound reconstruction and visualization. First, the various types of 3D ultrasound system are reviewed, such as mechanical, 2D array, position tracking-based freehand, and untracked-based freehand. Second, the 3D ultrasound reconstruction technique or pipeline used by the current existing system, which includes the data acquisition, data preprocessing, reconstruction method and 3D visualization, is discussed. The reconstruction method and 3D visualization will be emphasized. The reconstruction method includes the pixel-based method, volume-based method, and function-based method, accompanied with their benefits and drawbacks. In the 3D visualization, methods such as multiplanar reformatting, volume rendering, and surface rendering are presented. Lastly, its application in the medical field is reviewed as well

Restoration of hand and arm function to people with tetraplegia as a result of damage to the spinal cord in the neck through the use of functional electrical stimulation (FES).

Functional Electrical Stimulation (FES) therapy is a widely used rehabilitation technique to improve the hand functions of people with spinal cord injuries (SCI) and stroke. Two of the upper limb FES devices – the NeuroControl® Freehand System and the NESS H200 have received FDA approval and have been successfully commercialised. At the time of writing, out of the two devices, only NESS H200 was commercially available but the use of rigid arm splint limited the number of people who could functionally use the device. A new four channel upper limb FES device called the TetraGrip was developed during this research work. This device was controlled using an IMU based shoulder position sensor strapped across the contralateral shoulder and did not use a rigid arm splint. This allowed flexibility in electrode position and more people were able to use the system. The device was programmed to perform two hand movements – the key grip and the palmar grasp. Besides these functional modes, it was programmed to generate an exercise sequence that alternated between the palmar grasp and key grip movements. The device was tested on fourteen able bodied volunteers who used the shoulder position sensor to operate the device. This study was helpful in establishing the repeatability and reproducibility of the device and also helped in improving the device based on the feedback from users. This study also helped in exploring the possible combination of electrode positions for achieving functional movements. It was then clinically tested on two people with C6 tetraplegia who participated in a twelve week long study. The volunteers used an Odstock® Microstim to exercise the desired muscles for four weeks and then came back to the clinic once a week for eight weeks to use the TetraGrip. They were assessed using outcome measures such as the grip strength test, the box and block test and the grasp release test. As the study progressed, both the volunteers showed improvements in their ability to perform the specified tasks using key grip and palmar grasp movements and on the last day of the study, they were able to perform activities of daily living using the TetraGrip such as holding a pen and writing and holding a fork and eating lunch

Design and recognition of microgestures for always-available input

Gestural user interfaces for computing devices most commonly require the user to have at least one hand free to interact with the device, for example, moving a mouse, touching a screen, or performing mid-air gestures. Consequently, users find it difficult to operate computing devices while holding or manipulating everyday objects. This limits the users from interacting with the digital world during a significant portion of their everyday activities, such as, using tools in the kitchen or workshop, carrying items, or workout with sports equipment. This thesis pushes the boundaries towards the bigger goal of enabling always-available input. Microgestures have been recognized for their potential to facilitate direct and subtle interactions. However, it remains an open question how to interact using gestures with computing devices when both of the user’s hands are occupied holding everyday objects. We take a holistic approach and focus on three core contributions: i) To understand end-users preferences, we present an empirical analysis of users’ choice of microgestures when holding objects of diverse geometries. Instead of designing a gesture set for a specific object or geometry and to identify gestures that generalize, this thesis leverages the taxonomy of grasp types established from prior research. ii) We tackle the critical problem of avoiding false activation by introducing a novel gestural input concept that leverages a single-finger movement, which stands out from everyday finger motions during holding and manipulating objects. Through a data-driven approach, we also systematically validate the concept’s robustness with different everyday actions. iii) While full sensor coverage on the user’s hand would allow detailed hand-object interaction, minimal instrumentation is desirable for real-world use. This thesis addresses the problem of identifying sparse sensor layouts. We present the first rapid computational method, along with a GUI-based design tool that enables iterative design based on the designer’s high-level requirements. Furthermore, we demonstrate that minimal form-factor devices, like smart rings, can be used to effectively detect microgestures in hands-free and busy scenarios. Overall, the presented findings will serve as both conceptual and technical foundations for enabling interaction with computing devices wherever and whenever users need them.Benutzerschnittstellen für Computergeräte auf Basis von Gesten erfordern für eine Interaktion meist mindestens eine freie Hand, z.B. um eine Maus zu bewegen, einen Bildschirm zu berühren oder Gesten in der Luft auszuführen. Daher ist es für Nutzer schwierig, Geräte zu bedienen, während sie Gegenstände halten oder manipulieren. Dies schränkt die Interaktion mit der digitalen Welt während eines Großteils ihrer alltäglichen Aktivitäten ein, etwa wenn sie Küchengeräte oder Werkzeug verwenden, Gegenstände tragen oder mit Sportgeräten trainieren. Diese Arbeit erforscht neue Wege in Richtung des größeren Ziels, immer verfügbare Eingaben zu ermöglichen. Das Potential von Mikrogesten für die Erleichterung von direkten und feinen Interaktionen wurde bereits erkannt. Die Frage, wie der Nutzer mit Geräten interagiert, wenn beide Hände mit dem Halten von Gegenständen belegt sind, bleibt jedoch offen. Wir verfolgen einen ganzheitlichen Ansatz und konzentrieren uns auf drei Kernbeiträge: i) Um die Präferenzen der Endnutzer zu verstehen, präsentieren wir eine empirische Analyse der Wahl von Mikrogesten beim Halten von Objekte mit diversen Geometrien. Anstatt einen Satz an Gesten für ein bestimmtes Objekt oder eine bestimmte Geometrie zu entwerfen, nutzt diese Arbeit die aus früheren Forschungen stammenden Taxonomien an Griff-Typen. ii) Wir adressieren das Problem falscher Aktivierungen durch ein neuartiges Eingabekonzept, das die sich von alltäglichen Fingerbewegungen abhebende Bewegung eines einzelnen Fingers nutzt. Durch einen datengesteuerten Ansatz validieren wir zudem systematisch die Robustheit des Konzepts bei diversen alltäglichen Aktionen. iii) Auch wenn eine vollständige Sensorabdeckung an der Hand des Nutzers eine detaillierte Hand-Objekt-Interaktion ermöglichen würde, ist eine minimale Ausstattung für den Einsatz in der realen Welt wünschenswert. Diese Arbeit befasst sich mit der Identifizierung reduzierter Sensoranordnungen. Wir präsentieren die erste, schnelle Berechnungsmethode in einem GUI-basierten Designtool, das iteratives Design basierend auf den Anforderungen des Designers ermöglicht. Wir zeigen zudem, dass Geräte mit minimalem Formfaktor wie smarte Ringe für die Erkennung von Mikrogesten verwendet werden können. Insgesamt dienen die vorgestellten Ergebnisse sowohl als konzeptionelle als auch als technische Grundlage für die Realisierung von Interaktion mit Computergeräten wo und wann immer Nutzer sie benötigen.Bosch Researc

Development of a Novel Handheld Device for Active Compensation of Physiological Tremor

In microsurgery, the human hand imposes certain limitations in accurately positioning the tip of a device such as scalpel. Any errors in the motion of the hand make microsurgical procedures difficult and involuntary motions such as hand tremors can make some procedures significantly difficult to perform. This is particularly true in the case of vitreoretinal microsurgery. The most familiar source of involuntary motion is physiological tremor. Real-time compensation of tremor is, therefore, necessary to assist surgeons to precisely position and manipulate the tool-tip to accurately perform a microsurgery. In this thesis, a novel handheld device (AID) is described for compensation of physiological tremor in the hand. MEMS-based accelerometers and gyroscopes have been used for sensing the motion of the hand in six degrees of freedom (DOF). An augmented state complementary Kalman filter is used to calculate 2 DOF orientation. An adaptive filtering algorithm, band-limited Multiple Fourier linear combiner (BMFLC), is used to calculate the tremor component in the hand in real-time. Ionic Polymer Metallic Composites (IPMCs) have been used as actuators for deflecting the tool-tip to compensate for the tremor

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Wrist-worn gesture sensing with wearable intelligence

This paper presents an innovative wrist-worn device with machine learning capabilities and a wearable pressure sensor array. The device is used for monitoring different hand gestures by tracking tendon movements around the wrist. Thus, an array of PDMS-encapsulated capacitive pressure sensors is attached to the user to capture wrist movement. The sensors are embedded on a flexible substrate and their readout requires a reliable approach for measuring small changes in capacitance. This challenge was addressed by measuring the capacitance via the switched capacitor method. The values were processed using a programme on LabVIEW to visually reconstruct the gestures on a computer. Additionally, to overcome limitations of tendon’s uncertainty when the wristband is re-worn, or the user is changed, a calibration step based on the Support Vector Machine (SVM) learning technique is implemented. Sequential Minimal Optimization (SMO) algorithm is also applied in the system to generate SVM classifiers efficiently in real-time. The working principle and the performance of the SVM algorithms demonstrate through experiments. Three discriminated gestures have been clearly separated by SVM hyperplane and correctly classified with high accuracy (>90%) during real-time gesture recognition

Advanced Source Reconstruction and Volume Conductor Modeling for Fetal Magnetocardiography

Abstract Fetuses that are identified with cardiac hypotrophy, hypertension and metabolic anomalies have higher risk of suffering from various health problems in their later life. Therefore, the early detection of congenital heart anomalies is critical for monitoring or prompt interventions, which can reduce the risks of congestive heart failure. Compared to adult cardiac monitoring, fetal electrophysiological heart monitoring using fetal ECG is extremely difficult due to the low signal amplitude and interferences from the maternal cardiac signal and to the complex environment inside the mother's womb. This problem is even worse in conditions such as diabetic pregnancies because of further signal reduction due to maternal obesity. At the same time, the prevalence of congenital heart anomalies is higher for fetuses of diabetic mothers. The purpose of this thesis is to develop and test fetal magnetocardiography (fMCG) techniques as an alternative diagnostic tool for the detection and monitoring of the fetal heart. fMCG is a novel technique that records the magnetic fields generated by the fetal heart's electric activity. From the aspect of signal processing, magnetic signals generated by the fetal heart are less affected by the low electrical conductivity of the surrounding fetal and maternal tissues compared to the electric signals recorded over the maternal abdomen, and can provide reliable recordings as early as 12 weeks of gestation. However, the fetal heart signals recorded with an array of magnetic sensors at a small distance from the maternal abdomen are affected by the source-to-sensor distance as well as by the geometry of the volume conductor, which is variable in different subjects or in the same subject when recordings are made at different gestational ages. The scope of this thesis is to develop a novel methodology for modeling the fetal heart and volume conductor and to use advanced source reconstruction techniques that can reduce the effect of these confounding factors in evaluating heart magnetic signals. Furthermore, we aim to use these new methods for developing a normative database of fMCG metrics at different gestational ages and test their reliability to detect abnormal patterns of cardiac electrophysiology in pregnancies complicated by maternal diabetes. In the first part of the thesis, we review three current fetal heart monitoring modalities, including fetal electrocardiography (ECG), ultrasonography, and fetal magnetocardiography (fMCG). The advantages and drawbacks of each technique are comparatively discussed. Finally, we discuss the developmental changes of fetal heart through gestation as well as the electromagnetic characteristics of the fetal cardiac activation

Exploring At-Your-Side Gestural Interaction for Ubiquitous Environments

International audienceFree-space gestural systems are faced with two major issues: a lack of subtlety due to explicit mid-air arm movements, and the highly effortful nature of such interactions. With an ever-growing ubiquity of interactive devices, displays, and appliances with non-standard interfaces, lower-effort and more socially acceptable interaction paradigms are essential. To address these issues, we explore at-one's-side gestural input. Within this space, we present the results of two studies that investigate the use of side-gesture input for interaction. First, we investigate end-user preference through a gesture elicitation study, present a gesture set, and validate the need for dynamic, diverse, and variable-length gestures. We then explore the feasibility of designing such a gesture recognition system, dubbed WatchTrace, which supports alphanumeric gestures of up to length three with an average accuracy of up to 82%, providing a rich, dynamic, and feasible gestural vocabulary