Matching Items (3)
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- All Subjects: Human mechanics
- Creators: Buneo, Christopher
- Creators: Artemiadis, Panagiotis K.
Description
Reaching movements are subject to noise in both the planning and execution phases of movement production. Although the effects of these noise sources in estimating and/or controlling endpoint position have been examined in many studies, the independent effects of limb configuration on endpoint variability have been largely ignored. The present study investigated the effects of arm configuration on the interaction between planning noise and execution noise. Subjects performed reaching movements to three targets located in a frontal plane. At the starting position, subjects matched one of two desired arm configuration 'templates' namely "adducted" and "abducted". These arm configurations were obtained by rotations along the shoulder-hand axis, thereby maintaining endpoint position. Visual feedback of the hand was varied from trial to trial, thereby increasing uncertainty in movement planning and execution. It was hypothesized that 1) pattern of endpoint variability would be dependent on arm configuration and 2) that these differences would be most apparent in conditions without visual feedback. It was found that there were differences in endpoint variability between arm configurations in both visual conditions, but these differences were much larger when visual feedback was withheld. The overall results suggest that patterns of endpoint variability are highly dependent on arm configuration, particularly in the absence of visual feedback. This suggests that in the presence of vision, movement planning in 3D space is performed using coordinates that are largely arm configuration independent (i.e. extrinsic coordinates). In contrast, in the absence of vision, movement planning in 3D space reflects a substantial contribution of intrinsic coordinates.
ContributorsLakshmi Narayanan, Kishor (Author) / Buneo, Christopher (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.
ContributorsYi, Chong-hwan (Author) / Jindrich, Devin L. (Thesis advisor) / Artemiadis, Panagiotis K. (Thesis advisor) / Phelan, Patrick (Committee member) / Santos, Veronica J. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2014
Description
Understanding human-human interactions during the performance of joint motor tasks is critical for developing rehabilitation robots that could aid therapists in providing effective treatments for motor problems. However, there is a lack of understanding of strategies (cooperative or competitive) adopted by humans when interacting with other individuals. Previous studies have investigated the cues (auditory, visual and haptic) that support these interactions but understanding how these unconscious interactions happen even without those cues is yet to be explained. To address this issue, in this study, a paradigm that tests the parallel efforts of pairs of individuals (dyads) to complete a jointly performed virtual reaching task, without any auditory or visual information exchange was employed. Motion was tracked with a NDI OptoTrak 3D motion tracking system that captured each subject’s movement kinematics, through which we could measure the level of synchronization between two subjects in space and time. For the spatial analyses, the movement amplitudes and direction errors at peak velocities and at endpoints were analyzed. Significant differences in the movement amplitudes were found for subjects in 4 out of 6 dyads which were expected due to the lack of feedback between the subjects. Interestingly, subjects in this study also planned their movements in different directions in order to counteract the visuomotor rotation offered in the test blocks, which suggests the difference in strategies for the subjects in each dyad. Also, the level of de-adaptation in the control blocks in which no visuomotor rotation was offered to the subjects was measured. To further validate the results obtained through spatial analyses, a temporal analyses was done in which the movement times for the two subjects were compared. With the help of these results, numerous interaction scenarios that are possible in the human joint actions in without feedback were analyzed.
ContributorsAgrawal, Ankit (Author) / Buneo, Christopher (Thesis advisor) / Santello, Marco (Committee member) / Tillery, Stephen Helms (Committee member) / Arizona State University (Publisher)
Created2016