title: Model driven mobile care for patients with type 1 diabetes.
abstract: We gathered a data set from 30 patients with type 1 diabetes by giving the patients a mobile phone application, where they recorded blood glucose measurements, insulin injections, meals, and physical activity. Using these data as a learning data set, we describe a new approach of building a mobile feedback system for these patients based on periodicities, pattern recognition, and scale-space trends. Most patients have important patterns for periodicities and trends, though better resolution of input variables is needed to provide useful feedback using pattern recognition.
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway. stein.olav.skrovseth@telemed.no
authors.forename: Stein Olav
authors.initials: SO
authors.lastname: Skrøvseth
authors.forename: Eirik
authors.initials: E
authors.lastname: Arsand
authors.forename: Fred
authors.initials: F
authors.lastname: Godtliebsen
authors.forename: Ragnar M
authors.initials: RM
authors.lastname: Joakimsen
mesh_terms: D000328:Adult; D001676:Biofeedback, Psychology / Q000379:methods; D040421:Cell Phone; D034201:Computers, Handheld; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D003922:Diabetes Mellitus, Type 1 / Q000175:diagnosis* / Q000628:therapy*; D005260:Female; D006801:Humans; D008297:Male; D018802:Patient-Centered Care / Q000379:methods*; D017216:Telemedicine / Q000379:methods*; D013813:Therapy, Computer-Assisted / Q000379:methods*; D016896:Treatment Outcome