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The ultimate goal of human movement control research is to understand how natural movements performed in daily activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Here, patterns of arm joint control during daily functional tasks were examined, which are performed through rotation

The ultimate goal of human movement control research is to understand how natural movements performed in daily activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Here, patterns of arm joint control during daily functional tasks were examined, which are performed through rotation of the shoulder, elbow, and wrist with the use of seven DOF: shoulder flexion/extension, abduction/adduction, and internal/external rotation; elbow flexion/extension and pronation/supination; wrist flexion/extension and radial/ulnar deviation. Analyzed movements imitated two activities of daily living: combing the hair and turning the page in a book. Kinematic and kinetic analyses were conducted. The studied kinematic characteristics were displacements of the 7 DOF and contribution of each DOF to hand velocity. The kinetic analysis involved computation of 3-dimensional vectors of muscle torque (MT), interaction torque (IT), gravity torque (GT), and net torque (NT) at the shoulder, elbow, and wrist. Using a relationship NT = MT + GT + IT, the role of active control and the passive factors (gravitation and inter-segmental dynamics) in rotation of each joint was assessed by computing MT contribution (MTC) to NT. MTC was computed using the ratio of the signed MT projection on NT to NT magnitude. Despite the variety of joint movements required across the different tasks, 3 patterns of shoulder and elbow coordination prevailed in each movement: 1) active rotation of the shoulder and predominantly passive rotation of the elbow; 2) active rotation of the elbow and predominantly passive rotation of the shoulder; and 3) passive rotation of both joints. Analysis of wrist control suggested that MT mainly compensates for passive torque and provides adjustment of wrist motion according to requirements of both tasks. The 3 shoulder-elbow coordination patterns during which at least one joint moves largely passively represent joint control primitives underlying performance of well-learned arm movements, although these patterns may be less prevalent during non-habitual movements. The advantage of these control primitives is that they require minimal neural effort for joint coordination, and thus increase neural resources that can be used for cognitive tasks.
ContributorsMarshall, Dirk (Author) / Dounskaia, Natalia (Thesis advisor) / Schaefer, Sydney (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The ultimate goal of human movement control research is to understand how natural movements performed in daily reaching activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Patterns of arm joint control were studied during daily functional tasks, which were performed through the

The ultimate goal of human movement control research is to understand how natural movements performed in daily reaching activities, are controlled. Natural movements require coordination of multiple degrees of freedom (DOF) of the arm. Patterns of arm joint control were studied during daily functional tasks, which were performed through the rotation of seven DOF in the arm. Analyzed movements which imitated the following 3 activities of daily living: moving an empty soda can from a table and placing it on a further position; placing the empty soda can from initial position at table to a position at shoulder level on a shelf; and placing the empty soda can from initial position at table to a position at eye level on a shelf. Kinematic and kinetic analyses were conducted for these three movements. The studied kinematic characteristics were: hand trajectory in the sagittal plane, displacements of the 7 DOF, and contribution of each DOF to hand velocity. The kinetic analysis involved computation of 3-dimensional vectors of muscle torque (MT), interaction torque (IT), gravity torque (GT), and net torque (NT) at the shoulder, elbow, and wrist. Using the relationship NT = MT + GT + IT, the role of active control and passive factors (gravitation and inter-segmental dynamics) in rotation of each joint by computing MT contribution (MTC) to NT was assessed. MTC was computed using the ratio of the signed MT projection on NT to NT magnitude. Despite a variety of joint movements available across the different tasks, 3 patterns of shoulder and elbow coordination prevailed in each movement: 1) active rotation of the shoulder and predominantly passive rotation of the elbow; 2) active rotation of the elbow and predominantly passive rotation of the shoulder; and 3) passive rotation of both joints. Analysis of wrist control suggested that MT mainly compensates for passive torque and provides adjustment of wrist motion according to requirements of each task. In conclusion, it was observed that the 3 shoulder-elbow coordination patterns (during which at least one joint moved) passively represented joint control primitives, underlying the performance of well-learned arm movements, although these patterns may be less prevalent during non-habitual movements.
ContributorsSansgiri, Dattaraj (Author) / Dounskaia, Natalia (Thesis advisor) / Schaefer, Sydney (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Previous research has shown that a loud acoustic stimulus can trigger an individual's prepared movement plan. This movement response is referred to as a startle-evoked movement (SEM). SEM has been observed in the stroke survivor population where results have shown that SEM enhances single joint movements that are usually performed

Previous research has shown that a loud acoustic stimulus can trigger an individual's prepared movement plan. This movement response is referred to as a startle-evoked movement (SEM). SEM has been observed in the stroke survivor population where results have shown that SEM enhances single joint movements that are usually performed with difficulty. While the presence of SEM in the stroke survivor population advances scientific understanding of movement capabilities following a stroke, published studies using the SEM phenomenon only examined one joint. The ability of SEM to generate multi-jointed movements is understudied and consequently limits SEM as a potential therapy tool. In order to apply SEM as a therapy tool however, the biomechanics of the arm in multi-jointed movement planning and execution must be better understood. Thus, the objective of our study was to evaluate if SEM could elicit multi-joint reaching movements that were accurate in an unrestrained, two-dimensional workspace. Data was collected from ten subjects with no previous neck, arm, or brain injury. Each subject performed a reaching task to five Targets that were equally spaced in a semi-circle to create a two-dimensional workspace. The subject reached to each Target following a sequence of two non-startling acoustic stimuli cues: "Get Ready" and "Go". A loud acoustic stimuli was randomly substituted for the "Go" cue. We hypothesized that SEM is accessible and accurate for unrestricted multi-jointed reaching tasks in a functional workspace and is therefore independent of movement direction. Our results found that SEM is possible in all five Target directions. The probability of evoking SEM and the movement kinematics (i.e. total movement time, linear deviation, average velocity) to each Target are not statistically different. Thus, we conclude that SEM is possible in a functional workspace and is not dependent on where arm stability is maximized. Moreover, coordinated preparation and storage of a multi-jointed movement is indeed possible.
ContributorsOssanna, Meilin Ryan (Author) / Honeycutt, Claire (Thesis director) / Schaefer, Sydney (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12