Multi-feature Compensatory Motion Analysis for Reaching Motions Over a Discretely Sampled Workspace
<|reference_start|>Multi-feature Compensatory Motion Analysis for Reaching Motions Over a Discretely Sampled Workspace: The absence of functional arm joints, such as the wrist, in upper extremity prostheses leads to compensatory motions in the users' daily activities. Compensatory motions have been previously studied for varying task protocols and evaluation metrics. However, the movement targets' spatial locations in previous protocols were not standardised and incomparable between studies, and the evaluation metrics were rudimentary. This work analysed compensatory motions in the final pose of subjects reaching across a discretely sampled 7*7 2D grid of targets under unbraced (normative) and braced (compensatory) conditions. For the braced condition, a bracing system was applied to simulate a transradial prosthetic limb by restricting participants' wrist joints. A total of 1372 reaching poses were analysed, and a Compensation Index was proposed to indicate the severity level of compensation. This index combined joint spatial location analysis, joint angle analysis, separability analysis, and machine learning (clustering) analysis. The individual analysis results and the final Compensation Index were presented in heatmap format to correspond to the spatial layout of the workspace, revealing the spatial dependency of compensatory motions. The results indicate that compensatory motions occur mainly in a right trapezoid region in the upper left area and a vertical trapezoid region in the middle left area for right-handed subjects reaching horizontally and vertically. Such results might guide motion selection in clinical rehabilitation, occupational therapy, and prosthetic evaluation to help avoid residual limb pain and overuse syndromes.<|reference_end|>
@article{yang2024multi-feature,
    title={Multi-feature Compensatory Motion Analysis for Reaching Motions Over a
  Discretely Sampled Workspace},
    author={Qihan Yang, Yuri Gloumakov, Adam J. Spiers},
    journal={arXiv preprint arXiv:2409.05871},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.05871},
    primaryClass={cs.RO cs.LG}
}