Humans must manipulate and transport a variety of objects when performing daily life activities. Simple rigid objects readily respond to human control actions and usually have no movement constraints. In contrast, flexible objects contain elements that cannot be directly controlled and pose unique constraints on manipulative actions. For example, coffee in a cup can only be controlled by manipulating the cup, and the coffee may spill if the movements are inappropriate. Most studies to date have focused on tasks with rigid objects that have a well-defined optimal movement pattern that leads to a single goal;however, many everyday tasks do not have precisely defined optimal strategies - many strategies lead to the desired goal. Importantly, some strategies may have less sensitivity to control errors compared to others, and these may be preferred. Extending previous research, we define an error-tolerant movement strategy as one that minimizes the effects of movement variability on task performance. Tolerance is particularly important in the control of flexible objects, where violations of energetic constraints can lead to a loss of stability with undesired consequences, such as spilling coffee. Critical unanswered questions for flexible object control include whether individuals are sensitive to error tolerance and how tolerance changes with learning. Accordingly, the goal of this research is to develop an analysis approach to quantify error tolerance in the continuous control of flexible objects, and examine whether humans learn error-tolerant strategies when transporting flexible objects.
Three specific aims will be pursued: 1) develop an experimental paradigm based on the task of transporting a flexible object with energetic constraints, create a mathematical model of the task, and implement the task using a robotic device;2) extend an existing analysis approach called TNC (Tolerance, Noise, Covariation) to the continuous transportation task;3) show that humans learn error tolerant movement strategies for the transportation task during normal and perturbed task performances. This research combines theoretical and experimental work to address important gaps in our basic understanding of how humans manipulate flexible objects in the presence of movement variability and perturbations. Additionally, given that older adults have increased variability in their movements, the development of tolerant movement strategies may be a key feature of movement control in older adults. Hence, this study will lay the groundwork for future studies in older adults, which will explore whether older adults move slower as a strategic response to increase tolerance rather than simply due to physiological limitations.

Public Health Relevance

When performing everyday activities such as carrying a cup of coffee, humans should move in a way that minimizes the chance that the coffee will be spilled if the cup is unexpectedly disturbed. This research proposes that humans naturally learn such error-tolerant movement strategies. It may explain why older adults move slower, which may be a strategy to increase error tolerance due to their increased movement variability.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F10B-S (20))
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Boyce, Amanda T
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Northeastern University
Schools of Arts and Sciences
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Nasseroleslami, Bahman; Hasson, Christopher J; Sternad, Dagmar (2014) Rhythmic manipulation of objects with complex dynamics: predictability over chaos. PLoS Comput Biol 10:e1003900