@inproceedings{MarschollekSchulzeGietzeltetal.2013,
  author    = {Michael Marschollek and Mareike Schulze and Matthias Gietzelt and Nigel H. Lovell and Stephen J. Redmond},
  title     = {Sensor-based fall risk assessment - dagger of the mind?},
  series = {MEDINFO 2013 : proceedings of the 14th World Congress on Medical and Health Informatics},
  isbn      = {978-1-61499-289-9},
  doi       = {10.25968/opus-1127},
  url       = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus4-11276},
  pages     = {1048 -- 1048},
  year      = {2013},
  abstract  = {Fall events and their severe consequences represent not only a threatening problem for the affected individual, but also cause a significant burden for health care systems. Our research work aims to elucidate some of the prospects and problems of current sensor-based fall risk assessment approaches. Selected results of a questionnaire-based survey given to experts during topical workshops at international conferences are presented. The majority of domain experts confirmed that fall risk assessment could potentially be valuable for the community and that prediction is deemed possible, though limited. We conclude with a discussion of practical issues concerning adequate outcome parameters for clinical studies and data sharing within the research community. All participants agreed that sensor-based fall risk assessment is a promising and valuable approach, but that more prospective clinical studies with clearly defined outcome measures are necessary.},
  language  = {en}
}