A MoliZoft System Identification Approach of the Just Walk Data. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: dos Santos, P. Lopes; Freigoun, M.T.; Rivera, D.E.; Hekler, E.B.; Martín, C.A.; Romano, R.; Perdicoúlis, T-P; Ramos, J.A.
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 12508
• Page End: 12513
• Publication Date: 2017-07
• Subjects: System identification -- Least squares identification -- Output error identification -- Prediction error methods -- Social -- behavioural sciences; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.2060
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: A system identification approach is used estimate linear time invariant models from the data of physical activity gathered in the Just Walk intervention conducted by the Designing Health Lab and the Control Systems Laboratory at Arizona State University A class of identification algorithms proposed elsewhere by one of the authors, denoted as MoliZoft, was reformulated and adapted to estimate models from data gathered in this experience. In this paper, the identification algorithms are described and the best models estimated for a particular participant are analysed and used to improve the results in future experiments.