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Full-Body Mobility Data to Validate Inertial Measurement Unit Algorithms in Healthy and Neurological Cohorts

Author

Listed:
  • Elke Warmerdam

    (Department of Neurology, Kiel University, 24105 Kiel, Germany
    Division of Surgery, Saarland University, 66421 Homburg, Germany)

  • Clint Hansen

    (Department of Neurology, Kiel University, 24105 Kiel, Germany)

  • Robbin Romijnders

    (Department of Neurology, Kiel University, 24105 Kiel, Germany)

  • Markus A. Hobert

    (Department of Neurology, Kiel University, 24105 Kiel, Germany)

  • Julius Welzel

    (Department of Neurology, Kiel University, 24105 Kiel, Germany)

  • Walter Maetzler

    (Department of Neurology, Kiel University, 24105 Kiel, Germany)

Abstract

Gait and balance dysfunctions are common in neurological disorders and have a negative effect on quality of life. Regularly quantifying these mobility limitations can be used to measure disease progression and the effect of treatment. This information can be used to provide a more individualized treatment. Inertial measurement units (IMUs) can be utilized to quantify mobility in different contexts. However, algorithms are required to extract valuable parameters out of the raw IMU data. These algorithms need to be validated to make sure that they extract the features they should extract. This validation should be performed per disease since different mobility limitations or symptoms can influence the performance of an algorithm in different ways. Therefore, this dataset contains data from both healthy subjects and patients with neurological diseases (Parkinson’s disease, stroke, multiple sclerosis, chronic low back pain). The full bodies of 167 subjects were measured with IMUs and an optical motion capture (reference) system. Subjects performed multiple standardized mobility assessments and non-standardized activities of daily living. The data of 21 healthy subjects are shared online, data of the other subjects and patients can only be obtained after contacting the corresponding author and signing a data sharing agreement.

Suggested Citation

  • Elke Warmerdam & Clint Hansen & Robbin Romijnders & Markus A. Hobert & Julius Welzel & Walter Maetzler, 2022. "Full-Body Mobility Data to Validate Inertial Measurement Unit Algorithms in Healthy and Neurological Cohorts," Data, MDPI, vol. 7(10), pages 1-8, September.
    • Handle: RePEc:gam:jdataj:v:7:y:2022:i:10:p:136-:d:926159
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    References listed on IDEAS

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    1. Jason Shafrin & Jeff Sullivan & Dana P Goldman & Thomas M Gill, 2017. "The association between observed mobility and quality of life in the near elderly," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-13, August.
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