Doctor of Philosophy

dissertationFingernail imaging is a method of sensing finger force using the color patterns on the nail and surrounding skin. These patterns form as the underlying tissue is compressed and blood pools in the surrounding vessels. Photos of the finger and surrounding skin may be correlated to the magnitude and direction of force on the fingerpad. An automated calibration routine is developed to improve the data-collection process. This includes a novel hybrid force/position controller that manages the interaction between the fingerpad and a flat surface, implemented on a Magnetic Levitation Haptic Device. The kinematic and dynamics parameters of the system are characterized in order to appropriately design a nonlinear compensator. The controller settles within 0.13 s with less than 30% overshoot. A new registration A new registration technique, based on Active Appearance Models, is presented. Since this method accounts for the variation inherent in the finger, it reduces registration and force prediction errors while removing the need to tune registration parameters or reject unregistered images. Modifications to the standard model are also investigated. The number of landmark points is reduced to 25 points with no loss of accuracy, while the use of the green channel is found to have no significant effect on either registration or force prediction accuracy. Several force prediction models are characterized, and the EigenNail Magnitude Model, a Principal Component Regression model on the gray-level intensity, is shown to fit the data most accurately. The mean force prediction error using this prediction and modeling method is 0.55 N. White LEDs and green LEDs are shown to have no statistically significant effect on registration or force prediction. Finally, two different calibration grid designs are compared and found to have no significant effect. Together, these improvements prepare the way for fingernail imaging to be used in less controlled situations. With a wider range of calibration data and a more robust registration method, a larger range of force data may be predicted. Potential applications for this technology include human-computer interaction and measuring finger interaction forces during grasping experiments

Tribological interactions of the finger pad and tactile displays

This thesis summarise the results of an investigation of the tribological interactions of the human finger pad with different surfaces and tactile displays. In the wide range of analyses of the mechanical properties of the finger pad, an attempt has been made to explain the nature of the interactions based on critical material parameters and experimental data. The experimental data are presented together with detailed modelling of the contact mechanics of the finger pad compressed against a smooth flat surface. Based on the model and the experimental data, it was possible to account of the loading behaviour of a finger pad and derive the Young’s modulus of the fingerprint ridges. The frictional measurements of a finger pad against smooth flat surfaces are consistent with an occlusion mechanism that is governed by first order kinetics. In contrast, measurements against a rough surface demonstrated that the friction is unaffected by occlusion since Coulombic slip was exhibited. The thesis includes an investigation of critical parameters such as the contact area. It has been shown that four characteristic length scales, rather than just two as previously assumed, are required to describe the contact mechanics of the finger pad. In addition, there are two characteristic times respectively associated with the growth rates of junctions formed by the finger pad ridges and of the real area of contact. These length and time scales are important in understanding how the Archardian-Hertzian transition drives both the large increase of friction and the reduction of the areal load index during persisting finger contacts with impermeable surfaces. Established and novel models were evaluated with statistically meaningful experiments for phenomena such as lateral displacement, electrostatic forces and squeeze-film that have advanced applications

Computed fingertip touch for the instrumental control of musical sound with an excursion on the computed retinal afterimage

In this thesis, we present an articulated, empirical view on what human music making is, and on how this fundamentally relates to computation. The experimental evidence which we obtained seems to indicate that this view can be used as a tool, to systematically generate models, hypotheses and new technologies that enable an ever more complete answer to the fundamental question as to what forms of instrumental control of musical sound are possible to implement. This also entails the development of two novel transducer technologies for computed fingertip touch: The cyclotactor (CT) system, which provides fingerpad-orthogonal force output while tracking surface-orthogonal fingertip movement; and the kinetic surface friction transducer (KSFT) system, which provides fingerpad-parallel force output while tracking surface-parallel fingertip movement. In addition to the main research, the thesis also contains two research excursions, which are due to the nature of the Ph.D. position. The first excursion shows how repeated and varying pressing movements on the already held-down key of a computer keyboard can be used both to simplify existing user interactions and to implement new ones, that allow the rapid yet detailed navigation of multiple possible interaction outcomes. The second excursion shows that automated computational techniques can display shape specifically in the retinal afterimage, a well-known effect in the human visual system.Computer Systems, Imagery and Medi

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

3-D Force Control on the Human Fingerpad Using a Magnetic Levitation Device for Fingernail Imaging Calibration

This paper demonstrates fast, accurate, and stable force control in three axes simultaneously when a flat surface is pressed against the human fingerpad. The primary application of this force control is for the automated calibration of a fingernail imaging system, where video images of the human fingernail are used to predict the normal and shear forces that occur when the fingerpad is pressed against a flat surface. The system consists of a six degree-of-freedom magnetic levitation device (MLD), whose flotor has been modified to apply forces to the human fingerpad, which is resting in a passive restraint. The system is capable of taking simultaneous steps in normal force and two axes of shear forces with a settling time of less than 0.2 seconds, and achieves a steady-state error as small as 0.05 N in all three axes. The system is also capable of tracking error of less than 0.2 N when the shear force vector rotates with a frequency of 1 rad/s. This paper also demonstrates the successful tracking of a desired force trajectory in three dimensions for calibrating a fingernail imaging system