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Self-Organizing Maps and Fuzzy C-Means Algorithms on Gait Analysis Based on Inertial Sensors Data

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

Human gait corresponds to the physiological way of locomotion, which can be affected by several injuries. Thus, gait analysis plays an important role in observing kinematic and kinetic parameters of the joints involved with such movement pattern. Due to the complexity of such analysis, this paper explores the performance of two adaptive methods, Fuzzy c-means (FCM) and Self-organizing maps (SOM), to simplify the interpretation of gait data, provided by a secondary dataset of 90 subjects, subdivided into six groups. Based on inertial measurement units (IMU) data, two kinematic features, average cycle time and cadence, were used as inputs to the adaptive algorithms. Considering the similarities among the subjects of such database, our experiments show that FCM presented a better performance than SOM. Despite the misplacement of subjects into unexpected clusters, this outcome implies that FCM is rather sensitive to slight differences in gait analysis. Nonetheless, further trials with the aforementioned methods are necessary, since more gait parameters and a greater sample could reveal an undercover variation within the proper walking pattern.

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Acknowledgment

This work was supported by the Brazilian National Council for Scientific and Technological Development (CNPQ 207445/2014-1) through a doctoral scholarship granted to R.C.

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Authors and Affiliations

  1. Institute of General Mechanics, RWTH Aachen University, Aachen, North Rhine-Westphalia, 52062, Germany

    Rafael Caldas, Yabing Hu & Bernd Markert

  2. School of Engineering, University of Pernambuco, 50.720-001, Recife, Pernambuco, Brazil

    Fernando Buarque de Lima Neto

Authors
  1. Rafael Caldas
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  2. Yabing Hu
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  3. Fernando Buarque de Lima Neto
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  4. Bernd Markert
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Corresponding author

Correspondence to Rafael Caldas .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Caldas, R., Hu, Y., de Lima Neto, F.B., Markert, B. (2017). Self-Organizing Maps and Fuzzy C-Means Algorithms on Gait Analysis Based on Inertial Sensors Data. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_20

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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