@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.} }