title: A nomenclature for the analysis of continuous sensor and other data in the context of health-enabling technologies.
abstract: Due to the progress in technology, it is possible to capture continuous sensor data pervasively and ubiquitously. In the area of health-enabling and ambient assisted technologies we are faced with the problem of analyzing these data in order to improve or at least maintain the health status of patients. But due to the interdisciplinarity of this field every discipline makes use of their own analyzing methods. In fact, the choice of a certain analyzing method often solely depends on the set of methods known to the data analyst. It would be an advantage if the data analyst would know about all available analyzing methods and their advantages and disadvantages when applied to the manifold of data. In this paper we propose a nomenclature that structures existing analyzing methods and assists in the choice of a certain method that fits to a given measurement context and a given problem.
authors: Peter L. Reichertz Institute for Medical Informatics, University of Braunschweig - Institute of Technology and Hannover Medical School, Germany. Matthias.Gietzelt@plri.de
authors: Matthias
authors: M
authors: Gietzelt
authors: Klaus-Hendrik
authors: KH
authors: Wolf
authors: Reinhold
authors: R
authors: Haux
mesh_terms: D000465:Algorithms; D003195:Computer Communication Networks; D003198:Computer Simulation; D006801:Humans; D019451:Information Management / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D007256:Information Systems; D018670:Monitoring, Ambulatory / Q000379:methods*; D012656:Self-Help Devices; D009626:Terminology as Topic