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IMU Consensus Exception Detection with Dynamic Time Warping—A Comparative Approach

1
Department of Electrical Engineering, National Taipei University, New Taipei City 23741, Taiwan
2
Department of Computer and Communication Engineering, Taipei City University of Science & Technology, Taipei 11202, Taiwan
3
Graduate Institute of Animation and Film Art, Tainan National University of the Arts, Tainan City 72045, Taiwan
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(10), 2237; https://doi.org/10.3390/s19102237
Received: 28 February 2019 / Revised: 22 April 2019 / Accepted: 10 May 2019 / Published: 14 May 2019
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Abstract

A dynamic time warping (DTW) algorithm has been suggested for the purpose of devising a motion-sensitive microelectronic system for the realization of remote motion abnormality detection. In combination with an inertial measurement unit (IMU), the algorithm is potentially applicable for remotely monitoring patients who are at risk of certain exceptional motions. The fixed interval signal sampling mechanism has normally been adopted when devising motion detection systems; however, dynamically capturing the particular motion patterns from the IMU motion sensor can be difficult. To this end, the DTW algorithm, as a kind of nonlinear pattern-matching approach, is able to optimally align motion signal sequences tending towards time-varying or speed-varying expressions, which is especially suitable to capturing exceptional motions. Thus, this paper evaluated this kind of abnormality detection using the proposed DTW algorithm on the basis of its theoretical fundamentals to significantly enhance the viability of the methodology. To validate the methodological viability, an artificial neural network (ANN) framework was intentionally introduced for performance comparison. By incorporating two types of designated preprocessors, i.e., a DFT interpolation preprocessor and a convolutional preprocessor, to equalize the unequal lengths of the matching sequences, two kinds of ANN frameworks were enumerated to compare the potential applicability. The comparison eventually confirmed that the direct template-matching DTW is excellent in practical application for the detection of time-varying or speed-varying abnormality, and reliably captures the consensus exceptions. View Full-Text
Keywords: dynamic time warping; remote abnormality detection; the inertial measurement unit dynamic time warping; remote abnormality detection; the inertial measurement unit
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Yang, C.-Y.; Chen, P.-Y.; Wen, T.-J.; Jan, G.E. IMU Consensus Exception Detection with Dynamic Time Warping—A Comparative Approach. Sensors 2019, 19, 2237.

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