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Titel: Full-Body Mobility Data to Validate Inertial Measurement Unit Algorithms in Healthy and Neurological Cohorts
VerfasserIn: Warmerdam, Elke
Hansen, Clint
Romijnders, Robbin
Hobert, Markus A.
Welzel, Julius
Maetzler, Walter
Sprache: Englisch
Titel: Data
Bandnummer: 7
Heft: 10
Verlag/Plattform: MDPI
Erscheinungsjahr: 2022
Freie Schlagwörter: biomechanics
IMU
sensors
validation
algorithm
clinical cohort
neurogeriatrics
motion capture
DDC-Sachgruppe: 610 Medizin, Gesundheit
Dokumenttyp: Journalartikel / Zeitschriftenartikel
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.
DOI der Erstveröffentlichung: 10.3390/data7100136
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-377192
hdl:20.500.11880/34147
http://dx.doi.org/10.22028/D291-37719
ISSN: 2306-5729
Datum des Eintrags: 27-Okt-2022
Bezeichnung des in Beziehung stehenden Objekts: Supplementary Materials
In Beziehung stehendes Objekt: https://www.mdpi.com/article/10.3390/data7100136/s1
Fakultät: M - Medizinische Fakultät
Fachrichtung: M - Chirurgie
Professur: M - Prof. Dr. med. Bergita Ganse
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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