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- Creators: Artemiadis, Panagiotis K.
- Creators: Brewer, Gene
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
The human body is a complex system comprised of many parts that can coordinate in a variety of ways to produce controlled action. This creates a challenge for researchers and clinicians in the treatment of variability in motor control. The current study aims at testing the utility of a nonlinear analysis measure – the Largest Lyapunov exponent (1) – in a whole body movement. Experiment 1 examined this measure, in comparison to traditional linear measure (standard deviation), by having participants perform a sit-to-stand (STS) task on platforms that were either stable or unstable. Results supported the notion that the Lyapunov measure characterized controlled/stable movement across the body more accurately than the traditional standard deviation (SD) measure. Experiment 2 tested this analysis further by presenting participants with an auditory perturbation during performance of the same STS task. Results showed that both the Lyapunov and SD measures failed to detect the perturbation. However, the auditory perturbation may not have been an appropriate perturbation. Limitations of Experiment 2 are discussed, as well as directions for future study.
ContributorsGibbons, Cameron T (Author) / Amazeen, Polemnia G (Thesis advisor) / Amazeen, Eric (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2016