Journal article

An Online Unsupervised Dynamic Window Method to Track Repeating Patterns From Sensor Data.

Yousef Kowsar, Masud Moshtaghi, Eduardo Velloso, Christopher Leckie, Lars Kulik

IEEE Transactions on Cybernetics | Institute of Electrical and Electronics Engineers (IEEE) | Published : 2020

Abstract

Short bursts of repeating patterns [intervals of recurrence (IoR)] manifest themselves in many applications, such as in the time-series data captured from an athlete's movements using a wearable sensor while performing exercises. We present an efficient, online, one-pass, and real-time algorithm for finding and tracking IoR in a time-series data stream. We provide a detailed theoretical analysis of the behavior of any IoR and derive fundamental properties that can be used on real-world data streams. We show that why our method, unlike current state-of-the-art techniques, is robust to variations in repeats of the same pattern adjacent to each other. To evaluate our algorithm, we build a weara..

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