Haptic Tumor Augmentation: Exploring Multi-Point Interaction

Jeon, Seokhee; Harders, Matthias

doi:10.1109/toh.2014.2330300

Cited by 13 publications

(6 citation statements)

References 28 publications

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“…The system transmits vibrations and audio feedback to the user during the interaction. Jeon and Harders [44] introduced a system to operate on palpate tumors through the use of AR and haptic devices. A comparison of environments that aid learning visuo-haptically to perform surgeries and traditional forms was presented in the work of Esteban et al [45].…”

Section: Surgerymentioning

confidence: 99%

Systematic Review of Multimodal Human–Computer Interaction

et al. 2022

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This document presents a systematic review of Multimodal Human–Computer Interaction. It shows how different types of interaction technologies (virtual reality (VR) and augmented reality, force and vibration feedback devices (haptics), and tracking) are used in different domains (concepts, medicine, physics, human factors/user experience design, transportation, cultural heritage, and industry). A systematic literature search was conducted identifying 406 articles initially. From these articles, we selected 112 research works that we consider most relevant for the content of this article. The articles were analyzed in-depth from the viewpoint of temporal patterns, frequency of usage in types of technology in different domains, and cluster analysis. The analysis allowed us to answer relevant questions in searching for the next steps in work related to multimodal HCI. We looked at the typical technology type, how the technology type and frequency have changed in time over each domain, and how papers are grouped across metrics given their similarities. This analysis determined that VR and haptics are the most widely used in all domains. While VR is the most used, haptic interaction is presented in an increasing number of applications, suggesting future work on applications that configure VR and haptic together.

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Section: Surgerymentioning

confidence: 99%

Systematic Review of Multimodal Human–Computer Interaction

et al. 2022

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“…Otherwise, the force will represent repulsion between them. The torque reference τ ref , is estimated with equation (14). In Figure 20, the reference positions of the virtual point charges are shown.…”

Section: Exponential Force Behavior (Coulomb's Law)mentioning

confidence: 99%

“…The haptic interaction that students have with theoretical information may be enhanced with interactive technology [4], [5]. Haptic interactive technology may facilitate hands-on laboratory content by improving learning in topics like physics [4], chemistry [6], mechatronics [7], mechanics [8], [9], electricity and magnetism [10], mathematics [11], manufacture [12], [13], and medicine [14], [15]. The need for alternative tools and methods that increase learning outcomes has driven many investigations towards enhanced learning e.g.…”

Section: Introductionmentioning

confidence: 99%

Haptic Augmentation Towards a Smart Learning Environment: The Haptic Lever Design

et al. 2020

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This paper presents the design of a haptic interface called the Haptic Lever, to show four force-related phenomena for haptic augmentation towards Smart Learning Environments. The Haptic Lever is a mechanism with a sensorless torque control developed by means of a Disturbance Observer (DOB) to render forces that allow users to feel virtual phenomena. The control response converges in the torque reference as a result of a gain calibration and the DOB response. The Haptic Lever was evaluated experimentally with four dynamic models for constant (membrane), linear (Hook's law and viscous damping), and exponential (Coulomb's law) haptic augmentation. In the first experiment, the user can feel a constant force when passing between two reference points and feel resistance while moving through a virtual membrane. In the second and third experiment, the user can feel and interact with the linear dynamic models of Hook's law and viscous damping, in the form of a compression or tension spring by pushing or pulling them, respectively. Finally, in the fourth experiment, the user can feel an attraction or repulsion force between two virtual point charges that follows the exponential dynamic model of Coulomb's law. The results obtained from the experiments showed that the Haptic Lever successfully rendered the equivalent forces to each virtual phenomenon. The haptic sensation is estimated in terms of the torque response under a profile determined by the dynamic models. From the experimental results, it can be observed that the torque in Nm corresponded to each represented phenomenon.

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“…Based on (22), the transfer function G(s) describing the relation between the control input U i and F e can be given by…”

Section: Robot Dynamics and Control System Formulationmentioning

confidence: 99%

“…On the other hand, nonlinear models, such as the Hunt-Crossley model, are expected to be more accurate for describing the real behavior during the contact with soft human tissues [18,20]. However, so far nonlinear models have only been used for parameter estimation [18,21,22], but not for force control design.…”

Section: Introductionmentioning

confidence: 99%

Hunt–Crossley model based force control for minimally invasive robotic surgery

Pappalardo

Albakri

Liu

et al. 2016

Biomedical Signal Processing and Control

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a b s t r a c tIn minimally invasive surgery (MIS) the continuously increasing use of robotic devices allows surgical operations to be conducted more precisely and more efficiently. Safe and accurate interaction between robot instruments and living tissue is an important issue for both successful operation and patient safety. Human tissue, which is generally viscoelastic, nonlinear and anisotropic, is often described as purely elastic for its simplicity in contact force control design and online computation. However, the elastic model cannot reproduce the complex properties of a real tissue. Based on in vitro animal tissue relaxation tests, we identify the Hunt-Crossley viscoelastic model as the most realistic one to describe the soft tissue's mechanical behavior among several candidate models. A force control method based on Hunt-Crossley model is developed following the state feedback design technique with a Kalman filter based active observer (AOB). Both simulation and experimental studies were carried out to verify the performance of developed force controller, comparing with other linear viscoelastic and elastic model based force controllers. The studies and comparisons show that the Hunt-Crossley model based force controller ensures comparable rise time in transient response as the controller based on Kelvin-Boltzmann model which is reported as the most accurate description for robot-tissue interaction in recent literature, but it causes much less overshoot and remains stable for tasks with faster response time requirements.

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Haptic Tumor Augmentation: Exploring Multi-Point Interaction

Cited by 13 publications

References 28 publications

Systematic Review of Multimodal Human–Computer Interaction

Systematic Review of Multimodal Human–Computer Interaction

Haptic Augmentation Towards a Smart Learning Environment: The Haptic Lever Design

Hunt–Crossley model based force control for minimally invasive robotic surgery

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