An upper body model for the kinematical analysis of the joint chain of the human arm

Williams, S.; Schmidt, Robert; Disselhorst‐Klug, Catherine; Rau, G.

doi:10.1016/j.jbiomech.2005.07.023

Cited by 60 publications

(46 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Marker placement methods such as those proposed by Rau et al [1], Schmidt et al [13], and Williams et al [26] are more complex, using triads of markers on each segment. In their study, Rau et al [1] applied their marker placement method to the measurement of a child with plexus lesion and in this case would be unable to extend their method to include analysis of finger and thumb movements during the patient's compensatory movement strategy.…”

Section: Discussionmentioning

confidence: 99%

“…Also to be considered are certain impairments where spasticity, joint subluxation or deformation would hinder the correct application of the marker set, or are cumbersome for patients to wear in addition to concentrating on functional tasks. Complex marker placement methods may also increase the assessment time needed for a patient to attend a trial and in addition, some methods require static calibration trials to identify intermarker distances and marker triads with respect to markers that were positioned on boney landmarks during static calibrations [1], [10], [13], [15], [26]. Compared to previously published techniques, the proposed marker placement system is simple, using single markers that will not interfere with the movements of the fingers.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Validation and Application of a Computational Model for Wrist and Hand Movements Using Surface Markers

Metcalf

Notley

Chappell

et al. 2008

IEEE Trans. Biomed. Eng.

View full text Add to dashboard Cite

Abstract-A kinematic model is presented based on surface marker placement generating wrist, metacarpal arch, fingers and thumb movements. Standard calculations are used throughout the model and then applied to the specified marker placement. A static trial involving eight unimpaired participants was carried out to assess inter-rater reliability. The standard deviations across the data were comparable to manual goniometers. In addition, a test-retest trial of ten unimpaired participants is also reported to illustrate the variability of movement at the wrist joint, metacarpal arch, and index finger as an example of model output when repeating the same task many times.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Validation and Application of a Computational Model for Wrist and Hand Movements Using Surface Markers

Metcalf

Notley

Chappell

et al. 2008

IEEE Trans. Biomed. Eng.

View full text Add to dashboard Cite

show abstract

“…Various standardized methods for assessing upper-limb functional tasks have been proposed for defining an upper-limb motion analysis protocol with varying levels of complexity. Most authors have advocated using motions that simulate a common movement activity of daily living (ADL) task, such as drinking, combing hair or reaching hand to head [1][2][3], jar opening [4], removing a parking token [5], or reaching and placing a ball [6]. In this context, it has been found important to measure not only ranges of upper-limb joint motion but also velocity and dexterity of the motion as an overall indicator of performance [2].…”

Section: Introductionmentioning

confidence: 99%

Normative data for modified Box and Blocks test measuring upper-limb function via motion capture

et al. 2014

View full text Add to dashboard Cite

Abstract-Motion analysis is an important tool for examining upper-limb function. Based on previous work demonstrating a modified Box and Blocks (BB) test with motion capture to assess prosthetic performance, we collected data in 16 nondisabled participants to establish normative kinematics for this test. Four motions of the modified BB test were analyzed to establish kinematic data for upper-limb and trunk motion. The test was repeated for right and left arms in standing and seated positions. Data were compared using a nonparametric Friedman test. No differences were found between right-and lefthand performance other than for task completion time. Small but significant differences were found for standing and seated performance, with slightly greater ranges in standing for axial trunk rotation, medial-lateral sternum displacement, and anterior-posterior hand displacement. The kinematic trajectories, however, were very consistent. The consistency in our nondisabled data suggests that normative kinematic trajectories can be defined for this task. This motion capture procedure may add to the understanding of movement in upper-limb impairment and may be useful for measuring the effect of interventions to improve upper-limb function.

show abstract

“…Our clinical model depends heavily on the humerus segment, which is used for calculating joint angles, in terms of shoulder, elbow and forearm joint angles. It may also improve mean errors further due to GH marker placement methods 20,21) , and it may be suitable for overhead movements. …”

Section: Discussionmentioning

confidence: 99%

Development of a Clinical Model for Upper Extremity Motion Analysis—Comparison with Manual Measurement

et al. 2012

View full text Add to dashboard Cite

Abstract.[Purpose] The aim of this study was to develop a clinical upper extremity model to analyze joint motion in comparison with joint angles measured by a universal goniometer.[Subjects] Active movements of the right upper extremities of ten healthy volunteers were measured with both a universal goniometer and a Vicon 512 motion analyzer, and joint angles were calculated using Euler angles.[Methods] The range of error was established between joint angles measured by the universal goniometer and the Vicon 512. Validity and reliability for our clinical model were established using Pearson's correlation and intraclass correlation coefficients (ICCs), respectively.[Results] The mean error of 34 joint angles was less than 10°. The error was > 10° for 135° and maximum shoulder abduction. Pearson's correlation was > 0.9 between the goniometer and the Vicon 512. For the universal goniometer, intra-rater ICC reliability ranged from 0.71 to 0.96, and inter-rater ICC reliability ranged from 0.61 to 0.95. [Conclusions] We found that our clinical model was both valid and reliable for all upper extremity joints. This model can serve as a comprehensive tool for clinical upper extremity motion analysis.

show abstract

An upper body model for the kinematical analysis of the joint chain of the human arm

Cited by 60 publications

References 17 publications

Validation and Application of a Computational Model for Wrist and Hand Movements Using Surface Markers

Validation and Application of a Computational Model for Wrist and Hand Movements Using Surface Markers

Normative data for modified Box and Blocks test measuring upper-limb function via motion capture

Development of a Clinical Model for Upper Extremity Motion Analysis—Comparison with Manual Measurement

Contact Info

Product

Resources

About