Characterization of normative hand movements during two functional upper limb tasks

Abstract

BackgroundDexterous hand function is crucial for completing activities of daily living (ADLs), which typically require precise hand-object interactions. Kinematic analyses of hand trajectory, hand velocity, and grip aperture provide valuable mechanistic insights into task performance, but there is a need for standardized tasks representative of ADLs that are amenable to motion capture and show consistent performance in non-disabled individuals. Our objective was to develop two standardized functional upper limb tasks and to quantitatively characterize the kinematics of normative hand movement.MethodsTwenty non-disabled participants were recruited to perform two tasks: the Pasta Box Task and Cup Transfer Task. A 12-camera motion capture system was used to collect kinematic data from which hand movement and grip aperture measures were calculated. Measures reported for reach-grasp and transport-release segments were hand distance travelled, hand trajectory variability, movement time, peak and percent-to-peak hand velocity, number of movement units, peak and percent-to-peak grip aperture, and percent-to-peak hand deceleration. A between-session repeatability analysis was conducted on 10 participants.ResultsMovement times were longer for transport-release compared to reach-grasp for every movement. Hand and grip aperture measures had low variability, with 55 out of 63 measures showing good repeatability (ICC > 0.75). Cross-body movements in the Pasta Box Task had longer movement times and reduced percent-to-peak hand velocity values. The Cup Transfer Task showed decoupling of peak grip aperture and peak hand deceleration for all movements. Movements requiring the clearing of an obstacle while transporting an object displayed a double velocity peak and typically a longer deceleration phase.DiscussionNormative hand kinematics for two standardized functional tasks challenging various aspects of hand-object interactions important for ADLs showed excellent repeatability. The consistency in normative task performance across a variety of task demands shows promise as a potential outcome assessment for populations with upper limb impairment.

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

“…Data from two participants were removed due to problems arising from software issues. The characteristics of the 20 participants from the original study [7]–[9] and the 20 participants in the repeated study are detailed in Error! Reference source not found.…”

“…Various functional assessments are used to gauge the functional impact of upper limb impairment and to monitor rehabilitative progress thereafter [5], [6]. However, such assessments often do not precisely quantify hand and joint movements, grip adjustments [7], [8], or hand-eye interaction, which is recognized as an important behaviour during grasp control [9], [10]. Quantitative measurement of visuomotor behaviour collected during the execution of functional tasks can enhance the understanding of these movement features.…”

“…The Gaze and Movement Assessment (GaMA) protocol was designed to overcome these limitations. GaMA includes two standardized functional upper limb tasks that incorporate common dextrous hand demands of daily living [7]. GaMA also includes an analysis software, which requires a standardized data set of synchronized motion and eye data coordinates as input (obtained using motion capture and eye tracking during functional task execution), and outputs metrics of hand movement, angular joint kinematics, and eye gaze behavior [7]–[9].…”

“…GaMA includes two standardized functional upper limb tasks that incorporate common dextrous hand demands of daily living [7]. GaMA also includes an analysis software, which requires a standardized data set of synchronized motion and eye data coordinates as input (obtained using motion capture and eye tracking during functional task execution), and outputs metrics of hand movement, angular joint kinematics, and eye gaze behavior [7]–[9]. GaMA’s input data set can be obtained by various data collection hardware and software solutions, rendering the assessment protocol amenable to technological evolution (for example, markerless motion capture and mobile eye trackers).…”

“…Due to the inherent variability found in clinical populations, reproducibility of a test to assess movement behaviour is typically first studied in a non-disabled population. While intra-rater test-retest reliability of GaMA has been demonstrated for hand movement and angular joint kinematic measures for non-disabled individuals [7], [8], it has yet to be determined whether these and other measures obtainable by GaMA are reproducible across raters and sites. Furthermore, it is often assumed that the non-disabled population will behave similarly (or identically) across test sites; yet, it is known that deviations from protocols can result in data set disparity amongst the population [12].…”