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Gaze and Movement Assessment (GaMA): Inter-site validation of a visuomotor upper limb functional protocol.

ABSTRACT: BACKGROUND:Successful hand-object interactions require precise hand-eye coordination with continual movement adjustments. Quantitative measurement of this visuomotor behaviour could provide valuable insight into upper limb impairments. The Gaze and Movement Assessment (GaMA) was developed to provide protocols for simultaneous motion capture and eye tracking during the administration of two functional tasks, along with data analysis methods to generate standard measures of visuomotor behaviour. The objective of this study was to investigate the reproducibility of the GaMA protocol across two independent groups of non-disabled participants, with different raters using different motion capture and eye tracking technology. METHODS:Twenty non-disabled adults performed the Pasta Box Task and the Cup Transfer Task. Upper body and eye movements were recorded using motion capture and eye tracking, respectively. Measures of hand movement, angular joint kinematics, and eye gaze were compared to those from a different sample of twenty non-disabled adults who had previously performed the same protocol with different technology, rater and site. RESULTS:Participants took longer to perform the tasks versus those from the earlier study, although the relative time of each movement phase was similar. Measures that were dissimilar between the groups included hand distances travelled, hand trajectories, number of movement units, eye latencies, and peak angular velocities. Similarities included all hand velocity and grip aperture measures, eye fixations, and most peak joint angle and range of motion measures. DISCUSSION:The reproducibility of GaMA was confirmed by this study, despite a few differences introduced by learning effects, task demonstration variation, and limitations of the kinematic model. GaMA accurately quantifies the typical behaviours of a non-disabled population, producing precise quantitative measures of hand function, trunk and angular joint kinematics, and associated visuomotor behaviour. This work advances the consideration for use of GaMA in populations with upper limb sensorimotor impairment.

SUBMITTER: Williams HE

PROVIDER: S-EPMC6936776 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceNew treatments for upper-limb amputation aim to improve movement quality and reduce visual attention to the prosthesis. However, evaluation is limited by a lack of understanding of the essential features of human-prosthesis behavior and by an absence of consistent task protocols.ObjectiveTo evaluate whether task selection is a factor in visuomotor adaptations by prosthesis users to accomplish 2 tasks easily performed by individuals with normal arm function.Design, setting, and participantsThis cross-sectional study was conducted in a single research center at the University of Alberta, Edmonton, Alberta, Canada. Upper-extremity prosthesis users were recruited from January 1, 2016, through December 31, 2016, and individuals with normal arm function were recruited from October 1, 2015, through November 30, 2015. Eight prosthesis users and 16 participants with normal arm function were asked to perform 2 goal-directed tasks with synchronized motion capture and eye tracking. Data analysis was performed from December 3, 2018, to April 15, 2019.Main outcome and measuresMovement time, eye fixation, and range of motion of the upper body during 2 object transfer tasks (cup and box) were the main outcomes.ResultsA convenience sample comprised 8 male prosthesis users with acquired amputation (mean [range] age, 45 [30-64] years), along with 16 participants with normal arm function (8 [50%] of whom were men; mean [range] age, 26 [18-43] years; mean [range] height, 172.3 [158.0-186.0] cm; all right handed). Prosthesis users spent a disproportionately prolonged mean (SD) time in grasp and release phases when handling the cups (grasp: 2.0 [2.3] seconds vs 0.9 [0.8] seconds; P < .001; release: 1.1 [0.6] seconds vs 0.7 [0.4] seconds; P < .001). Prosthesis users also had increased mean (SD) visual fixations on the hand for the cup compared with the box task during reach (10.2% [12.1%] vs 2.2% [2.8%]) and transport (37.1% [9.7%] vs 22.3% [7.6%]). Fixations on the hand for both tasks were significantly greater for prosthesis users compared with normative values. Prosthesis users had significantly more trunk flexion and extension for the box task compared with the cup task (mean [SD] trunk range of motion, 32.1 [10.7] degrees vs 21.2 [3.7] degrees; P = .01), with all trunk motions greater than normative values. The box task required greater shoulder movements compared with the cup task for prosthesis users (mean [SD] flexion and extension; 51.3 [12.6] degrees vs 41.0 [9.4] degrees, P = .01; abduction and adduction: 40.5 [7.2] degrees vs 32.3 [5.1] degrees, P = .02; rotation: 50.6 [15.7] degrees vs 35.5 [10.0] degrees, P = .02). However, other than shoulder abduction and adduction for the box task, these values were less than those seen for participants with normal arm function.Conclusions and relevanceThis study suggests that prosthesis users have an inherently different way of adapting to varying task demands, therefore suggesting that task selection is crucial in evaluating visuomotor performance. The cup task required greater compensatory visual fixations and prolonged grasp and release movements, and the box task required specific kinematic compensatory strategies as well as increased visual fixation. This is the first study to date to examine visuomotor differences in prosthesis users across varying task demands, and the findings appear to highlight the advantages of quantitative assessment in understanding human-prosthesis interaction.

Project description:Background: Studies aiming to objectively quantify movement disorders during upper limb tasks using wearable sensors have recently increased, but there is a wide variety in described measurement and analyzing methods, hampering standardization of methods in research and clinics. Therefore, the primary objective of this review was to provide an overview of sensor set-up and type, included tasks, sensor features and methods used to quantify movement disorders during upper limb tasks in multiple pathological populations. The secondary objective was to identify the most sensitive sensor features for the detection and quantification of movement disorders on the one hand and to describe the clinical application of the proposed methods on the other hand. Methods: A literature search using Scopus, Web of Science, and PubMed was performed. Articles needed to meet following criteria: 1) participants were adults/children with a neurological disease, 2) (at least) one sensor was placed on the upper limb for evaluation of movement disorders during upper limb tasks, 3) comparisons between: groups with/without movement disorders, sensor features before/after intervention, or sensor features with a clinical scale for assessment of the movement disorder. 4) Outcome measures included sensor features from acceleration/angular velocity signals. Results: A total of 101 articles were included, of which 56 researched Parkinson's Disease. Wrist(s), hand(s) and index finger(s) were the most popular sensor locations. Most frequent tasks were: finger tapping, wrist pro/supination, keeping the arms extended in front of the body and finger-to-nose. Most frequently calculated sensor features were mean, standard deviation, root-mean-square, ranges, skewness, kurtosis/entropy of acceleration and/or angular velocity, in combination with dominant frequencies/power of acceleration signals. Examples of clinical applications were automatization of a clinical scale or discrimination between a patient/control group or different patient groups. Conclusion: Current overview can support clinicians and researchers in selecting the most sensitive pathology-dependent sensor features and methodologies for detection and quantification of upper limb movement disorders and objective evaluations of treatment effects. Insights from Parkinson's Disease studies can accelerate the development of wearable sensors protocols in the remaining pathologies, provided that there is sufficient attention for the standardisation of protocols, tasks, feasibility and data analysis methods.

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Gaze and Movement Assessment (GaMA): Inter-site validation of a visuomotor upper limb functional protocol.

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