2019/07/22 by Gromit Yeuk-Yin Chan, Luís Gustavo Nonato, Chan, Gromit Yeuk-Yin +9 · 1 citation
Medicine · #FOS: Computer and information sciences #Graphics (cs.GR) #Human-Computer Interaction (cs.HC) #Stroke Rehabilitation and Recovery
paper · pdf · doi:10.48550/arxiv.1907.09146
openalex publication_date 2019/07/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The brachial plexus is a complex network of peripheral nerves that enables\nsensing from and control of the movements of the arms and hand. Nowadays, the\ncoordination between the muscles to generate simple movements is still not well\nunderstood, hindering the knowledge of how to best treat patients with this\ntype of peripheral nerve injury. To acquire enough information for medical data\nanalysis, physicians conduct motion analysis assessments with patients to\nproduce a rich dataset of electromyographic signals from multiple muscles\nrecorded with joint movements during real-world tasks. However, tools for the\nanalysis and visualization of the data in a succinct and interpretable manner\nare currently not available. Without the ability to integrate, compare, and\ncompute multiple data sources in one platform, physicians can only compute\nsimple statistical values to describe patient's behavior vaguely, which limits\nthe possibility to answer clinical questions and generate hypotheses for\nresearch. To address this challenge, we have developed systemname, an\ninteractive visual analytics system which provides an efficient framework to\nextract and compare muscle activity patterns from the patient's limbs and\ncoordinated views to help users analyze muscle signals, motion data, and video\ninformation to address different tasks. The system was developed as a result of\na collaborative endeavor between computer scientists and orthopedic surgery and\nrehabilitation physicians. We present case studies showing physicians can\nutilize the information displayed to understand how individuals coordinate\ntheir muscles to initiate appropriate treatment and generate new hypotheses for\nfuture research.\n