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Towards Automatic Gait Analysis from an IT Perspective: A Kinesiology Case

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Information Systems and Technologies (WorldCIST 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 470))

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Abstract

Currently, kinesiologists who study the posture of people during walking rely on spreadsheets and visual posture assessment. Some technologies make it possible to include sensors in people's bodies to identify their movements. Today, artificial intelligence is supporting many medical processes. In this sense, our proposal focuses on developing software based on Computer Vision and Artificial Intelligence. The software is deployed in a robust architecture based on microservices to support the process of image analysis with high concurrency. This software assists specialists in the analysis and measurements of lower extremity angles and distances during gait. On this occasion, we are working with a local medical center, specialists in caring for high-performance athletes. One of its crucial kinesiology care activities is the performance of kinematic gait analysis.

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Funding

This work was supported by the FCT – Fundação para a Ciência e a Tecnologia, I.P. [Project UIDB/05105/2020].

Author information

Authors and Affiliations

  1. Depto. Cs. de la Computación e Informática, Universidad de la Frontera, Temuco, Chile

    Matías Córdova & Jaime Díaz

  2. Depto. de Sistemas e Informática, Universidad de Caldas, Manizales, Colombia

    Jeferson Arango-López

  3. Depto. Procesos Diagnósticos y Evaluación, Universidad Católica de Temuco, Temuco, Chile

    Danay Ahumada

  4. REMIT, IJP, Universidade Portucalense and IEETA, Universidade de Aveiro, Aveiro, Portugal

    Fernando Moreira

Authors
  1. Matías Córdova
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  2. Jaime Díaz
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  3. Jeferson Arango-López
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  4. Danay Ahumada
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  5. Fernando Moreira
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Corresponding author

Correspondence to Fernando Moreira .

Editor information

Editors and Affiliations

  1. ISEG, Universidade de Lisboa, Lisbon, Portugal

    Alvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

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Córdova, M., Díaz, J., Arango-López, J., Ahumada, D., Moreira, F. (2022). Towards Automatic Gait Analysis from an IT Perspective: A Kinesiology Case. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 470. Springer, Cham. https://doi.org/10.1007/978-3-031-04829-6_36

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