Reproducibility and Application of the Gaze and Movement Assessment (GaMA)

Introduction: State-of-the-art upper limb prosthetic devices are complex, with multi-articulating hands that can open and close on user command. These so-called myoelectric prostheses harness the signals of a user’s residual muscles to trigger a desired function, such as grasping an object. Despite functional advancements, myoelectric prostheses still have limited dexterity and lack sensory feedback. As such, users exhibit compensatory arm and trunk movements and allocate increased visual attention during device-object interactions. A standardized and quantitative measurement protocol that assesses the movement quality of prosthetic device users has yet to be adopted by researchers and clinicians, despite the motivation to improve function. One method of evaluating upper limb function, with relevance to prosthesis use, is through assessment of hand movement, angular joint kinematics, and eye gaze measures. These measures can be derived from data that are commonly collected using optical motion capture and eye tracking technologies. Motion capture data can be used to analyze upper limb motion and hand-object interactions, and simultaneously collected eye tracking data can facilitate analysis of hand-eye coordination. Assessments reliant on specialized data capture technologies such as these, however, lack standardized protocols, are not necessarily generalizable to activities of daily living (ADLs), and risk becoming obsolete. Background: A collaborative group of researchers at the University of Alberta has developed the Gaze and Movement Assessment (GaMA) protocol to address the need for standardized outcome performance measures that are representative of ADLs and achievable by individuals both with and without upper limb mobility restrictions. GaMA encompasses two standardized functional upper limb tasks and analysis software. This software requires a standardized data set of synchronized motion and eye data coordinates as input, and outputs hand movement, angular joint kinematic, and eye gaze measures. Although GaMA’s input has been collected using optical motion capture and state-of-the-art eye tracking technologies, the protocol is amenable to future advances in data capture solutions. Objectives: The first objective of this thesis was to determine if GaMA is reproducible – that is, whether GaMA could be used to obtain the same hand movement, angular joint kinematic, and eye gaze measures when testing two independent groups of non-disabled participants, at different research sites equipped with different data capture technologies, and by different raters. With the reproducibility of GaMA established, the second objective of this thesis was to use this assessment protocol to test the assumption that movement measures from actual myoelectric users are comparable to those of non-disabled individuals wearing a simulated prosthetic device. Methods: To accomplish the first objective, twenty non-disabled adults performed GaMA’s two functional tasks: the Pasta Box Transfer Task, which required participants to move a box of pasta to shelves of different heights; and the Cup Transfer Task, which required the same participants to move deformable, filled cups over a partition at table-top height. Participants’ upper body and eye movements were recorded using optical motion capture and eye tracking technologies, respectively. GaMA’s analysis software provided measures of hand movement, angular joint kinematics, and eye gaze. These measures were then compared to those from twenty non-disabled adults who had previously performed GaMA’s functional tasks at a different site. To accomplish the second objective of this thesis, three participants completed GaMA’s Pasta Box Transfer Task using their custom-fitted myoelectric prosthesis. Motion capture methods were followed for data acquisition, and GaMA’s software was used to derive hand movement and angular joint kinematic measures. Resulting performance metrics, end effector movements, and angular kinematics were compared to those from an already established data set, collected from twelve non-disabled participants wearing a simulated prosthesis at a different site. Results: The research conducted in this thesis concluded that GaMA is reproducible and can serve as a quantitative assessment tool for individuals both with and without sensory-motor impairment of the upper limb. Furthermore, it supports the notion that non-disabled individuals wearing a simulated prosthesis can act as substitutes for actual prosthesis users in research and expands the potential to compare data sets across different sites. Recommendation: Given that GaMA has been shown to be reproducible, it should be promoted as a measurement protocol for use in ongoing upper limb prosthesis research, inter-site research comparisons, and considered as a means of merging data sets to overcome sample size limitations of research participants with amputations.

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