@proceedings {1816, title = {Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial}, year = {2017}, month = {07/2018}, publisher = {IEEE}, address = {London, UK}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sullivan_ICORR\%202017_BMI\%20Exo.pdf}, author = {Sullivan, J.L. and Bhagat, N.A. and Yozbatiran, N. and Paranjape, R. and Losey, C.G. and Grossman, R.G. and Contreras-Vidal, J.L. and Francisco, G.E. and O{\textquoteright}Malley, M.K.} } @article {1760, title = {An index finger exoskeleton with series elastic actuation for rehabilitation: Design, control and performance characterization}, journal = {International Journal of Robotics Research}, volume = {34}, number = {14}, year = {2015}, pages = {1747-1772}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Agarwal2015\%20-\%20Index\%20finger\%20exo.pdf}, author = {Priyanshu Agarwal and Jonas Fox and Youngmok Yun and O{\textquoteright}Malley, M.K. and Ashish D. Deshpande} } @article {1695, title = {Identifying Successful Motor Task Completion via Motion-Based Performance Metrics}, journal = {Human-Machine Systems, IEEE Transactions on}, volume = {44}, year = {2014}, pages = {139-145}, keywords = {Accelerometers, human{\textendash}computer interaction, motion analysis}, doi = {10.1109/THMS.2013.2290129}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/O\%27Malley_et_al_IEEE_Trans_HMS_PRESS.pdf}, author = {O{\textquoteright}Malley, M.K. and Purkayastha, S.N. and Howie, N. and Byrne, M.D.} } @article {917, title = {Incorporating simulation in vascular surgery education}, journal = {Journal of vascular surgery : official publication, the Society for Vascular Surgery [and] International Society for Cardiovascular Surgery, North American Chapter}, year = {2010}, month = {2010/08/05}, pages = { - }, publisher = {Mosby-Year Book}, isbn = {0741-5214}, url = {http://linkinghub.elsevier.com/retrieve/pii/S0741521410013054?showall=true}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/bismuth2010jvascsurg.pdf}, author = {Jean Bismuth and Michael A. Donovan and O{\textquoteright}Malley, M.K. and Hosam F. El Sayed and Joseph J. Naoum and Eric K. Peden and Mark G. Davies and Alan B. Lumsden} } @proceedings {529, title = {Impact of visual error augmentation methods on task performance and motor adaptation}, year = {2009}, pages = {793-798}, abstract = {

We hypothesized that augmenting the visual error feedback provided to subjects training in a point-to-point reaching task under visual distortion would improve the amount and speed of adaptation. Previous studies showing that human learning is error-driven and that visual error augmentation can improve the rate at which subjects decrease their trajectory error in such a task provided the motivation for our study. In a controlled experiment, subjects were required to perform point-to- point reaching movements in the presence of a rotational visual distortion. The amount and speed of their adaptation to this distortion were calculated based on two performance measures: trajectory error and hit time. We tested how three methods of error augmentation (error amplification, traditional error offsetting, and progressive error offsetting) affected the amount and speed of adaptation, and additionally propose definitions for {\textquotedblleft}amount{\textquotedblright} and {\textquotedblleft}speed{\textquotedblright} of adaptation in an absolute sense that are more practical than definitions used in previous studies. It is concluded that traditional error offsetting promotes the fastest learning, while error amplification promotes the most complete learning. Progressive error offsetting, a novel method, resulted in slower training than the control group, but we hypothesize that it could be improved with further tuning and indicate a need for further study of this method. These results have implications for improvement in motor skill learning across many fields, including rehabilitation after stroke, surgical training, and teleoperation.

}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/529-Celik2009ICORRpublished.pdf}, author = {Ozkan Celik and Powell, Dane and O{\textquoteright}Malley, M.K.} } @proceedings {920, title = {Implementing Haptic Feedback Environments from High-level Descriptions}, year = {2009}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/zhu2009shoes.pdf}, author = {Angela Yun Zhu and Jun Inoue and Marisa Peralta and Walid Taha and O{\textquoteright}Malley, M.K. and Powell, Dane} } @article {101, title = {Improved Haptic Fidelity via Reduced Sampling Period with an FPGA-Based Real-Time Hardware Platform }, journal = {ASME Journal of Computing and Information Science in Engineering}, volume = {9}, number = {1}, year = {2009}, note = {
Improved Haptic Fidelity Via Reduced Sampling Period With an FPGA-Based Real-Time Hardware Platform
Marcia K. O{\textquoteright}Malley, Kevin S. Sevcik, and Emilie Kopp, J. Comput. Inf. Sci. Eng. 9, 011002 (2009), DOI:10.1115/1.3072904


}, month = {03/2009}, abstract = {

A haptic virtual environment is considered to be high-fidelity when the environment is perceived by the user to be realistic. For environments featuring rigid objects, perception of a high degree of realism often occurs when the free space of the simulated environment feels free and when surfaces intended to be rigid are perceived as such. Because virtual surfaces (often called virtual walls) are typically modeled as simple unilateral springs, the rigidity of the virtual surface depends on the stiffness of the spring model. For impedance-based haptic interfaces, the stiffness of the virtual surface is limited by the damping and friction inherent in the device, the sampling rate of the control loop, and the quantization of sensor data. If stiffnesses greater than the limit for a particular device are exceeded, the interaction between the human user and the virtual surface via the haptic device becomes nonpassive. We propose a computational platform that increases the sampling rate of the system, thereby increasing the maximum achievable virtual surface stiffness, and subsequently the fidelity of the rendered virtual surfaces. We describe the modification of a PHANToM Premium 1.0 commercial haptic interface to enable computation by a real-time operating system (RTOS) that utilizes a field programmable gate array (FPGA) for data acquisition between the haptic interface hardware and computer. Furthermore, we explore the performance of the FPGA serving as a standalone system for communication and computation. The RTOS system enables a sampling rate for the PHANToM that is 20 times greater than that achieved using the \“out of the box\” commercial hardware system, increasing the maximum achievable surface stiffness twofold. The FPGA platform enables sampling rates of up to 400 times greater, and stiffnesses over 6 times greater than those achieved with the commercial system. The proposed computational platforms will enable faster sampling rates for any haptic device, thereby improving the fidelity of virtual environments.

}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/101-JCISE\%20proof\%20FINAL\%202-09.pdf}, author = {O{\textquoteright}Malley, M.K. and Sevcik, Kevin S. and Kopp, E} } @proceedings {674, title = {Intermittency of slow arm movements increases in distal direction}, year = {2009}, pages = {4499-4504}, address = {St. Louis, MO}, abstract = {

When analyzed in the tangential speed domain, human movements exhibit a multi-peaked speed profile which is commonly interpreted as evidence for submovements. At slow speeds, the number of the peaks increases and the peaks also become more distinct, corresponding to non-smoothness or intermittency in the movement. In this study, we evaluate two potential sources proposed in the literature for the origins of movement intermittency and conclude that intermittency is more likely due to noise in the neuromuscular system as opposed to a central movement planner that generates intermittent plans. This conclusion is based on the assumption that the central planner would be expected to introduce similar levels of intermittency for different joints, while accumulating noise in the neuromuscular circuitry would be expected to exhibit itself as increase in noise in distal direction. We have used a 3D motion capture system to record trajectories of fingertip, wrist, elbow and shoulder as five participants completed a simple manual circular tracking task at various constant speed levels. Statistical analyses indicated that movement intermittency, quantified by a number of peaks metric, increased in distal direction, supporting the noise model for origins of intermittency. Movement speed was determined to have a significant effect on intermittency, while orientation of the task plane showed no significance.

}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/674-Celik2009IROS.pdf}, author = {Ozkan Celik and Gu, Qin and Deng, Zhigang and O{\textquoteright}Malley, M.K.} } @proceedings {082211289621, title = {Improved haptic fidelity via reduced sampling period with an FPGA-based real-time hardware platform (IMECE)}, volume = {9 PART B}, year = {2007}, note = {

Real Time Operating System (RTOS) control system;Proprietary control card;

}, pages = {1335 - 1342}, address = {Seattle, WA, United States}, abstract = {

Impedance based haptic interfaces face inherent challenges in displaying stiff virtual environments. Fidelity of a virtual environment is enhanced by stiff virtual walls combined with low damping and passive behavior of the interface. However, the stiffness of virtual walls displayed on an impedance based interface is limited by the damping inherent in the controller, the sampling rate of the control loop, and the quantization of the controller{\textquoteright}s position. Attempting to display a stiffness larger than this limiting value destroys the passivity of the interface, leading to active controller behavior and eventually closed loop instability. We propose a method of increasing the fidelity of a PHANToM Premium 1.0 commercial haptic interface by controlling it via a Field Programmable Gate Array (FPGA) both alone and with a Real Time Operating System (RTOS) control system. This custom controller enjoys several benefits over the standard control achieved via a proprietary control card in a Multitasking OS, including reduced system overhead and deterministic loop rate timing. The performance of the proposed FPGA/RTOS controller compares favorably with the performance of an FPGA/Multitasking OS controller. The FPGA/RTOS controller achieves control loop rates an order of magnitude greater than that of the proprietary controller, allowing virtual walls to be displayed with greatly increased stiffnesses, while retaining the passivity and low damping of the PHANToM interface. Copyright {\textcopyright} 2007 by ASME.

}, keywords = {Computer operating systems, Damping, Field programmable gate arrays (FPGA), Multitasking, Real time systems, Virtual reality}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/56-IMECE2007-42085.pdf}, author = {Sevcik, Kevin S. and Kopp, E and O{\textquoteright}Malley, M.K.} } @proceedings {7379354, title = {The implications of surface stiffness for size identification and perceived surface hardness in haptic interfaces}, volume = {vol.2}, year = {2002}, note = {

surface stiffness;virtual surface stiffness;haptic perception;time delays;size identification;perceived surface hardness;haptic interfaces;

}, pages = {1255 - 60}, address = {Washington, DC, USA}, abstract = {

This paper presents a two-part study of the effects of virtual surface stiffness on haptic perception. First, size identification experiments were performed to determine the effects of system quality, in terms of surface stiffness, on the ability of a human to identify square cross-section ridges by size in a simulated environment. Then, discrimination experiments were performed to determine relationships between virtual surface stiffness and simulation quality in terms of perceived surface hardness. Results of experiments to test human haptic perception for varying virtual surface stiffnesses indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user at relatively low levels of virtual surface stiffness. Subjects, however, can perceive improvements in perceived simulated surface hardness as stiffness levels are increased in the range of achievable parameters for this hardware. The authors draw several conclusions about the allowable time delays in a haptic interface system based on the results of the surface stiffness experiments

}, keywords = {delays, Haptic interfaces, human factors, Virtual reality}, url = {http://dx.doi.org/10.1109/ROBOT.2002.1014715}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2002ieeesurfacestiffness.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} }