@proceedings {1811, title = {The Effect of Robot Dynamics on Smoothness during Wrist Pointing}, year = {2017}, month = {08/2017}, publisher = {IEEE}, address = {London, England}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Erwin2017\%20-\%20Robot\%20impacts\%20movements.pdf}, author = {Erwin,Andrew and Pezent,Evan and Bradley,Joshua and O{\textquoteright}Malley, M.K.} } @article {1761, title = {An exploration of grip force regulation with a low-impedance myoelectric prosthesis featuring referred haptic feedback}, journal = {Journal of Neuroengineering and Rehabilitation}, volume = {12}, year = {2015}, doi = {10.1186/s12984-015-0098-1}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Brown2015\%20-\%20Grip\%20force\%20regulation.pdf}, author = {J.D. Brown and A. Paek and M. Syed and O{\textquoteright}Malley, M.K. and P.A. Shewokis and J.L. Contreras-Vidal and R.B. Gillespie and A.J. Davis} } @proceedings {1476, title = {Effect of Progressive Visual Error Amplification on Human Motor Adaptation}, year = {2011}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ICORR11_Sung-O\%27Malley-PRESS.pdf}, author = {C. Sung and O{\textquoteright}Malley, M.K.} } @proceedings {1049, title = {Efficacy of Shared-Control Guidance Paradigms for Robot-Mediated Training}, year = {2011}, address = {Istanbul, Turkey}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1049-HAP11_0064_FI.pdf}, author = {Powell, Dane and O{\textquoteright}Malley, M.K.} } @proceedings {526, title = {Effects of Force and Displacement Cues while Adapting in a Rhythmic Motor Task}, year = {2009}, pages = {32-33}, address = {Seattle, WA}, abstract = {

This paper explores the effects of magnitude and phase cues on human motor adaptation. Participants were asked to excite virtual second-order systems at their resonance frequencies via a two-degree of freedom haptic interface, with visual and visual plus haptic feedback conditions. Their motor adaptations were studied through catch trials. The results indicate that, i) humans adapt to a nominal virtual system resonant frequency, ii) humans shift to higher and lower natural frequencies during catch trials regardless of feedback modality and force cues, iii) humans can detect changes in natural frequency when gain, magnitude, and phase cues are manipulated independently, and iv) humans are able to detect changes in natural frequency when the feedback (visual or visual plus haptic) is delayed such that the phase shift between the nominal system and catch trial system is zero.

}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/israr2009robotics.pdf}, author = {Ali Israr and Hakan Kapson and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {107, title = {Effects of Magnitude and Phase Cues on Human Motor Adaptation}, year = {2009}, month = {03/2009}, pages = {344-349}, publisher = {IEEE}, address = {Salt Lake city, Utah}, abstract = {

Recent findings have shown that humans can adapt their internal control model to account for the changing dynamics of systems they manipulate. In this paper, we explore the effects of magnitude and phase cues on human motor adaptation. In our experiments, participants excite virtual second-order systems at resonance via a two-degree of freedom haptic interface, with visual and visual plus haptic feedback conditions. Then, we change the virtual system parameters and observe the resulting motor adaptation in catch trials. Through four experimental conditions we demonstrate the effects of magnitude and phase cues on human motor adaptation. First, we show that humans adapt to a nominal virtual system resonant frequency. Second, humans shift to higher and lower natural frequencies during catch trials regardless of feedback modality and force cues. Third, participants can detect changes in natural frequency when gain, magnitude, and phase cues are manipulated independently. Fourth, participants are able to detect changes in natural frequency when the feedback (visual or visual plus haptic) is delayed such that the phase shift between the nominal system and catch trial system is zero. The persistent ability of participants to perform system identification of the dynamic systems which they control, regardless of the cue that is conveyed, demonstrates the human{\textquoteright}s versatility with regard to manual control situations. We intend to further investigate human motor adaptation and the time for adaptation in order to improve the efficacy of shared control methodologies for training and rehabilitation in haptic virtual environments.

}, keywords = {catch trials, internal models, motor adaptation, Rhythmic motion}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/107-0156.pdf}, author = {Ali Israr and Hakan Kapson and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @article {856, title = {Expertise-Based Performance Measures in a Virtual Training Environment}, journal = {Presence}, volume = {18}, year = {2009}, note = {doi: 10.1162/pres.18.6.449}, month = {2009/12/01}, pages = {449 - 467}, publisher = {MIT Press}, abstract = {

This paper introduces and validates quantitative performance measures for a rhythmic target-hitting task. These performance measures are derived from a detailed analysis of human performance during a month-long training experiment where participants learned to operate a 2-DOF haptic interface in a virtual environment to execute a manual control task. The motivation for the analysis presented in this paper is to determine measures of participant performance that capture the key skills of the task. This analysis of performance indicates that two quantitative measures{\textemdash}trajectory error and input frequency{\textemdash}capture the key skills of the target-hitting task, as the results show a strong correlation between the performance measures and the task objective of maximizing target hits. The performance trends were further explored by grouping the participants based on expertise and examining trends during training in terms of these measures. In future work, these measures will be used as inputs to a haptic guidance scheme that adjusts its control gains based on a real-time assessment of human performance of the task. Such guidance schemes will be incorporated into virtual training environments for humans to develop manual skills for domains such as surgery, physical therapy, and sports.

}, isbn = {1054-7460}, url = {http://dx.doi.org/10.1162/pres.18.6.449}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/856-Huegel2009Presence.pdf}, author = {Joel C. Huegel and Ozkan Celik and Ali Israr and O{\textquoteright}Malley, M.K.} } @proceedings {072310640904, title = {Experimental system identification of force reflecting hand controller}, year = {2006}, note = {

Manipulator design;Environmental impedance;Sinusoidal sweep torque input;

}, pages = {9 -}, address = {Chicago, IL, United States}, abstract = {

This paper describes the combined time and frequency domain identification of the first three degrees-of-freedom (DOF) of a six degree-of-freedom force reflecting hand controller (FRHC). The FRHC is used to teleoperate Robonaut, a humanoid robotic assistant developed by NASA, via a bilateral teleoperation architecture. Three of the six DOF of the FRHC are independently identified due to the decoupled nature of the manipulator design. The frequency response for each axis is acquired by coupling a known environmental impedance to the joint axis and then applying a sinusoidal sweep torque input. Several data sets are averaged in the frequency domain to obtain an averaged frequency response. A coherence analysis is then performed and data with low coherence values are ignored for subsequent analysis and model fitting. The paper describes the use of coherence data to ensure acceptable model fits for transfer function estimation. Results of the identification experiments are presented, including implications of assumptions of decoupling and linearity. In addition, frequency and time domain validations for each axis model are performed using data sets excluded from the parameter estimation, with strong correlation. Copyright {\textcopyright} 2006 by ASME.

}, keywords = {Degrees of freedom (mechanics), Force measurement, Frequency domain analysis, Identification (control systems), Remote control, Robotics}, author = {Zumbado, Fernando and McJunkin, Samuel and O{\textquoteright}Malley, M.K.} } @article {04338307919, title = {The effect of virtual surface stiffness on the haptic perception of detail}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {9}, number = {2}, year = {2004}, note = {

Virtual surface stiffness;Haptic perception;Design specifications;Haptic interface hardware;

}, pages = {448 - 454}, abstract = {

This brief presents a quantitative study of the effects of virtual surface stiffness in a simulated haptic environment on the haptic perception of detail. Specifically, the haptic perception of detail is characterized by identification, detection, and discrimination of round and square cross section ridges. Test results indicate that performance, measured as a percent correct score in the perception experiments, improves in a nonlinear fashion as the maximum level of virtual surface stiffness in the simulation increases. Further, test subjects appeared to reach a limit in their perception capabilities at maximum stiffness levels of 300 to 400 N/m, while the hardware was capable of 1000 N/m of maximum virtual surface stiffness. These results indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user with relatively low levels of virtual surface stiffness. \© 2004 IEEE.

}, keywords = {Computer aided design, Computer hardware, Computer simulation, Degrees of freedom (mechanics), Manipulators, Object recognition, Sensory perception, Specifications, Stiffness, Surface properties, Virtual reality}, url = {http://dx.doi.org/10.1109/TMECH.2004.828625}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/44-09tmech02omalley-print.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} } @article {02427145860, title = {The effect of force saturation on the haptic perception of detail}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {7}, number = {3}, year = {2002}, note = {Force saturation effect;Haptic perception;Force feedback;}, pages = {280 - 288}, abstract = {

This paper presents a quantitative study of the effects of maximum capable force magnitude of a haptic interface on the haptic perception of detail. Specifically, the haptic perception of detail is characterized by identification, detection, and discrimination of round and square cross-section ridges, in addition to corner detection tests. Test results indicate that performance, measured as a percent correct score in the perception experiments, improves in a nonlinear fashion as the maximum allowable level of force in the simulation increases. Further, all test subjects appeared to reach a limit in their perception capabilities at maximum-force output levels of 3-4 N, while the hardware was capable of 10 N of maximum continuous force output. These results indicate that haptic interface hardware may be able to convey sufficient perceptual information to the user with relatively low levels of force feedback. The data is compiled to aid those who wish to design a stylus-type haptic interface to meet certain requirements for the display of physical detail within a haptic simulation.

}, keywords = {Computer control systems, Computer simulation, Feedback control, Haptic interfaces, Identification (control systems), Nonlinear control systems, Virtual reality}, url = {http://dx.doi.org/10.1109/TMECH.2002.802725}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2002ieee.pdf}, author = {O{\textquoteright}Malley, M.K. and Michael Goldfarb} }