Process / pipelineTime-series analysis

DTW Gait Analysis

Dynamic Time Warping (DTW) is a sequence alignment algorithm that measures similarity between time series of different lengths by allowing flexible temporal matching. Applied to gait analysis, DTW enables comparison of walking patterns across subjects and conditions despite variations in cadence or stride length.

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Sources

  1. Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43-49. DOI: 10.1109/TASSP.1978.1163055
  2. Wang, Z., Yan, W., & Oates, T. (2013). Time series classification from scratch with deep neural networks: A strong baseline. arXiv preprint arXiv:1611.06455. link

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Referenced by

ScholarGateDTW Gait Analysis (Dynamic Time Warping for Gait Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/biomechanics/dtw-gait-analysis