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Towards an Automated Assessment of Musculoskeletal Insufficiencies

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Intelligent Decision Technologies 2019

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 142))

Abstract

The paper suggests a quantitative assessment of human movements using inexpensive 3D sensor technology and evaluates its accuracy by comparing it with human expert assessments. The two assessment methods show a high agreement. To achieve this, a novel sequence alignment algorithm was developed that works for arbitrary time series.

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Notes

  1. 1.

    https://www.qinematic.com.

  2. 2.

    https://kinetisense.com.

  3. 3.

    https://en.wikipedia.org/wiki/Kinect.

  4. 4.

    https://en.wikipedia.org/wiki/National_Academy_of_Sports_Medicine.

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Author information

Authors and Affiliations

  1. AIMO AB, Stockholm, Sweden

    Danny Dressler

  2. Softwerk AB, Växjö, Sweden

    Pavlo Liapota

  3. DISA, Linnaeus University, Växjö, Sweden

    Welf Löwe

Authors
  1. Danny Dressler
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  2. Pavlo Liapota
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  3. Welf Löwe
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Corresponding author

Correspondence to Welf Löwe .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Ireneusz Czarnowski

  2. Bournemouth University and KES International, Poole, Dorset, UK

    Robert J. Howlett

  3. University of Canberra, Canberra, ACT, Australia

    Lakhmi C. Jain

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Cite this paper

Dressler, D., Liapota, P., Löwe, W. (2020). Towards an Automated Assessment of Musculoskeletal Insufficiencies. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2019. Smart Innovation, Systems and Technologies, vol 142. Springer, Singapore. https://doi.org/10.1007/978-981-13-8311-3_22

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