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These repeated maneuvers can be extracted by analyzing the inputs and outputs of the human operator using control theory and data mining tools. In this paper, we introduce geometrical shape-based pattern detection approach for input-output data. A pattern or a maneuver is defined as the maximum repeated behavior in time series trajectory data that is generated from the operator\u2019s inputs and outputs. A two-phase algorithm is developed in this paper, the first phase consists of trajectory segmentation, creating segment fingerprint, clustering, and symbolic representations. The second phase of the proposed algorithm is pattern extraction phase, which is inherited from the motif finding algorithms in time series data and DNA sequences.<\/jats:p>","DOI":"10.3233\/jifs-179070","type":"journal-article","created":{"date-parts":[[2019,4,23]],"date-time":"2019-04-23T12:04:27Z","timestamp":1556021067000},"page":"115-123","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Pattern detection for time series trajectories in human in the loop applications"],"prefix":"10.1177","volume":"37","author":[{"given":"Mohamed A.","family":"Mabrok","sequence":"first","affiliation":[{"name":"Department of Mathematics, School of Engineering, Australian College of Kuwait, Kuwait"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdel-Haleem","family":"Abdel-Aty","sequence":"additional","affiliation":[{"name":"Department of Mathematics, School of Engineering, Australian College of Kuwait, 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