preha: Establishing Precision Rehabilitation with Visual Analytics

Information

• Publication Type: Conference Paper
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: September 2019
• Lecturer: Renata Raidou
• Event: Eurographics Workshop on Visual Computing for Biology and Medicine (2019)
• DOI: 10.2312/vcbm.20191234
• Call for Papers: Call for Paper
• Booktitle: Eurographics Workshop on Visual Computing for Biology and Medicine (2019)
• Pages: 79 – 89

Abstract

This design study paper describes preha, a novel visual analytics application in the field of in-patient rehabilitation. We conducted extensive interviews with the intended users, i.e., engineers and clinical rehabilitation experts, to determine specific requirements of their analytical process.We identified nine tasks, for which suitable solutions have been designed and developed in the flexible environment of kibana. Our application is used to analyze existing rehabilitation data from a large cohort of 46,000 patients, and it is the first integrated solution of its kind. It incorporates functionalities for data preprocessing (profiling, wrangling and cleansing), storage, visualization, and predictive analysis on the basis of retrospective outcomes. A positive feedback from the first evaluation with domain experts indicates the usefulness of the newly proposed approach and represents a solid foundation for the introduction of visual analytics to the rehabilitation domain.

Additional Files and Images

Weblinks

• DOI: 10.2312/vcbm.20191234

BibTeX

@inproceedings{raidou_2019_preha,
  title =      "preha: Establishing Precision Rehabilitation with Visual
               Analytics",
  author =     "Georg Bernold and Kresimir Matkovic and Eduard Gr\"{o}ller
               and Renata Raidou",
  year =       "2019",
  abstract =   "This design study paper describes preha, a novel visual
               analytics application in the field of in-patient
               rehabilitation. We conducted extensive interviews with the
               intended users, i.e., engineers and clinical rehabilitation
               experts, to determine specific requirements of their
               analytical process.We identified nine tasks, for which
               suitable solutions have been designed and developed in the
               flexible environment of kibana. Our application is used to
               analyze existing rehabilitation data from a large cohort of
               46,000 patients, and it is the first integrated solution of
               its kind. It incorporates functionalities for data
               preprocessing (profiling, wrangling and cleansing), storage,
               visualization, and predictive analysis on the basis of
               retrospective outcomes. A positive feedback from the first
               evaluation with domain experts indicates the usefulness of
               the newly proposed approach and represents a solid
               foundation for the introduction of visual analytics to the
               rehabilitation domain.",
  month =      sep,
  event =      "Eurographics Workshop on Visual Computing for Biology and
               Medicine (2019)",
  doi =        "10.2312/vcbm.20191234",
  booktitle =  "Eurographics Workshop on Visual Computing for Biology and
               Medicine (2019)",
  pages =      "79--89",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_preha/",
}