@article {murali2021vel, title = {Velocity-Domain Motion Quality Measures for Surgical Performance Evaluation and Feedback}, journal = {Journal of Medical Devices}, volume = {15}, number = {1}, year = {2021}, pages = {011107}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/med_015_01_011107.pdf}, author = {Murali, Barathwaj and Belvroy, Viony M and Pandey, Shivam and Bismuth, Jean and Byrne, Michael D and O{\textquoteright}Malley, Marcia K} } @article {1694, title = {Vary Slow Motion: Effect of Task Forces on Movement Variability and Implications for a Novel Skill Augmentation Mechanism}, journal = {IEEE Robotics and Automation Magazine}, year = {2014}, month = {08/2014}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Celik-O\%27Malley_IEEE-RAM_2014_press.pdf}, author = {Ozkan Celik and Marcia K. O{\textquoteright}Malley} } @proceedings {1686, title = {Vibrotactile Feedback of Pose Error Enhances Myoelectric Control of a Prosthetic Hand}, year = {2013}, month = {04/2013}, pages = {531-536}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/WH2013_FINAL_PRESS_Christiansen_et_al.pdf}, author = {Ryan Christiansen and Jose Luis Contreras-Vidal and R B Gillespie and Patricia Shewokis and Marcia K. O{\textquoteright}Malley} } @article {1079, title = {Vision-Based Force Sensing for Nanomanipulation}, journal = {IEEE /ASME Transactions on Mechatronics}, year = {2011}, type = {Journal Article}, abstract = {A vision-based algorithm for estimating tip interaction forces on a deflected Atomic Force Microscope (AFM) cantilever is described. Specifically, we propose that the algorithm can estimate forces acting on an Atomic Force Microscope (AFM) cantilever being used as a nanomanipulator inside a Scanning Electron Microscope (SEM). The vision based force sensor can provide force feedback in real-time, a feature absent in many SEMs. A methodology based on cantilever slope detection is used to estimate the forces acting on the cantilever tip. The technique was tested on a scaled model of the nanoscale AFM cantilever and verified using theoretical estimates as well as direct strain measurements. Artificial SEM noise was introduced in the macroscale images to characterize our sensor under varying levels of noise and other SEM effects. Prior knowledge about the cantilever is not required, and the algorithm runs independent of human input. The method is shown to be effective under varying noise levels, and demonstrates improving performance as magnification levels are decreased. Therefore, we conclude that the vision-based force sensing algorithm is best suited for continuous operation of the SEM, fast scanning rates, and large fields-of-view associated with low magnification levels.}, issn = {1083-4435 }, doi = {10.1109/TMECH.2010.2093535}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5692832}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1079-05692832.pdf}, author = {Vinay Chawda and O{\textquoteright}Malley, M.K.} } @proceedings {530, title = {Validation of a smooth movement model for a human reaching task}, year = {2009}, pages = {799-804}, abstract = {

This paper presents the experiment design, results, and analysis of a human user study that tests and validates the minimum hand jerk (MHJ) model for a human forearm reaching movement task when manipulating a multi-mass object. This work validates and extends prior work that demonstrated the MHJ criteria, a mathematical approach to human movement modeling, more accurately represents movements with multi-mass objects than the alternate optimally smooth transport (OST) model. To validate the prior work, we developed a visual and haptic virtual environment with a five-mass system with friction connected by springs and viscous dampers. The point to point reaching task we implemented required participants to move their hand with the set of masses to a target position, thereby generating movement profiles for analysis. Our experimental design uniquely extends the application of the MHJ criteria to forearm pronation movements and our results show that the MHJ model holds. Our extension to forearm movements and the more general MHJ criteria are economic models of human movements applicable to fields such as computer animation and virtual environments.

}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/530-Huegel2009ICORRpublished.pdf}, author = {Joel C. Huegel and Lynch, Andrew and O{\textquoteright}Malley, M.K.} } @proceedings {110, title = {Visual Versus Haptic Progressive Guidance For Training In A Virtual Dynamic Task}, year = {2009}, month = {03/2009}, publisher = {IEEE}, address = {Salt Lake City, UT, USA}, keywords = {Haptic interface, training, virtual environment}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/110-Huegel-ProgDemo-WHC.pdf}, author = {Joel C. Huegel and O{\textquoteright}Malley, M.K.} } @proceedings {072310640927, title = {Vision based force sensing for nanorobotic manipulation}, year = {2006}, note = {

Nanomanipulation;Nanoassembly;

}, pages = {10 -}, address = {Chicago, IL, United States}, abstract = {

Over the last decade, considerable interest has been generated in building and manipulating nanoscale structures. Applications of nanomanipulation include study of nanoparticles, molecules, DNA and viruses, and bottom-up nanoassembly. We propose a Nanomanipulation System using the Zyvex S100 nanomanipulator, -which operates within a scanning electron microscope (SEM), as its primary component. The primary advantage of the S100 setup over standard scanning probe microscopy based nanomanipulators is the ability to see the object during manipulation. Relying on visual feedback alone to control the nanomanipulator is not preferable due to perceptual limitations of depth and contact within the SEM. To improve operator performance over visual feedback alone, an impedance-controlled bilateral teleoperation setup is envisioned. Lack of on-board force sensors on the S100 system is the primary hindrance in the realization of the proposed architecture. In this paper, we present a computer vision based force sensing scheme. The advantages of this sensing strategy include its low cost and lack of requirement of hardware modifications). Force sensing is implemented using an atomic force microscopy (AFM) probe attached to the S100 end-effector. Deformation of the cantilever probe is monitored using a Hough transform based algorithm. These deformations are mapped to corresponding end-effector forces following the Euler-Bernoulli beam mechanics model. The forces thus sensed can be used to provide force-feedback to the operator through a master manipulator. Copyright {\textcopyright} 2006 by ASME.

}, keywords = {Atomic force microscopy, Force measurement, Manipulators, Nanoparticles, Nanotechnology, Scanning electron microscopy}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/49-IMECE2006-15111-Gupta-small.pdf}, author = {Abhishek Gupta and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {06169823803, title = {Virtual lab for system identification of an electromechanical system}, volume = {74 DSC}, number = {1 PART A}, year = {2005}, note = {

Virtual instrument (vi);Identification laboratory;Virtual Lab (VL);

}, pages = {705 - 712}, address = {Orlando, FL, United States}, abstract = {

A stand-alone virtual instrument (vi) has been developed to augment an experimental system identification laboratory exercise in a required mechanical engineering course on system dynamics. The Virtual Lab (VL) was used productively as a post-lab exercise in conjunction with an existing laboratory experiment for system identification. The VL can be formatted as a standalone file, which the students can download and access at their convenience, without the need for LabVIEW software. The virtual lab presented in this paper used the experimental identification of a transfer function for an xy recorder developed at Rose-Hulman Institute of Technology. In the original Rose-Hulman experiment, students view a video of the acquisition of frequency response data for an X-Y recorder. Then, students complete a detailed optimization procedure using Microsoft Excel in order to determine system parameters for two transfer function models. This paper describes using the Virtual Lab to extend the original lab exercise into an interactive mode. The students complete the Microsoft Excel part of the exercise, but then repeat the optimization using brute force via the LabVIEW based VL developed by the authors, rather than using the optimization toolbox in Excel. With the VL, students can see in real-time the effects of each unknown parameter on the frequency response plot, thus providing additional insight into the relationships between these parameters and the behavior of the electromechanical system. This feature is notably absent in the Microsoft Excel portion of the exercise. Although this exercise uses simple dynamic models, the combination of Excel and LabVIEW approaches provide an insightful introduction to experimental system identification. In this paper, details of the VL are presented, including the functionality of the VL and methodologies for disseminating the VL as a stand-alone piece of software. Finally some assessment results for the original (Excel version) and VL methods of presenting the laboratory exercise are discussed. Copyright {\textcopyright} 2005 by ASME.

}, keywords = {Computer software, Data acquisition, Mathematical models, Mechanical engineering, Real time systems, Students}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2005asme.pdf}, author = {O{\textquoteright}Malley, M.K. and David M. McStravick} } @proceedings {04448428417, title = {Virtual labs in the engineering curriculum}, year = {2004}, note = {

Engineering curriculum;Real-time parametric changes;Graphical interfaces;Virtual labs;

}, pages = {15293 - 15304}, address = {Salt Lake City, UT, United States}, abstract = {

Computer simulations have been developed for use as student exercises to illustrate concepts required for various engineering courses. These simulations or Virtual Labs are highly graphical and interactive to help undergraduate students understand basic concepts by graphically solving problems and by visualization of real-time parametric changes. These Virtual Labs (or VL{\textquoteright}s) can be used productively in conjunction with existing laboratory experiments as pre-lab exercises, but the more important benefit is realized in cases of concepts that have no experimental support and in courses that traditionally do not have an associated laboratory course. These VL{\textquoteright}s are generated in the software package Lab VIEW, which offers graphical interfaces for the student and can be formatted as standalone files, which the students can download and access at their convenience, without the need for Lab VIEW software. Currently five VL{\textquoteright}s have been generated and several have been evaluated by students in appropriate classes.

}, keywords = {Computer programming languages, Computer simulation, Curricula, Data reduction, Graphic methods, Students, Visualization}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/mcstravick2004asee.pdf}, author = {David M. McStravick and O{\textquoteright}Malley, M.K.} }